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Last Updated :2024/11/07

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Master

Affiliation (Master)

  • Faculty of Environmental Earth Science　Integrated Environmental Science　Conservation on Natural Environments

Affiliation (Master)

  • Faculty of Environmental Earth Science　Integrated Environmental Science　Conservation on Natural Environments

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Profile and Settings

Degree

  • Ph D（University of Tokyo）

Profile and Settings

  • Profile

    I am working as an Associate Professor at the Faculty of Environmental Earth Science, Hokkaido University, Japan and Director of the Global Land Programme (GLP) Japan Nodal Office. I actively contribute to study land systems and co-design solutions for global sustainability as a part of GLP programme. I have worked at United Nations University, Institute for the Advanced Study of Sustainability (UNU-IAS) as a Research Fellow for four years (2012-2016). I hold a master’s degree in Environmental Science from Jawaharlal Nehru University, New Delhi, India and a doctorate in Civil Engineering from the University of Tokyo, Japan. I have developed methods for mapping natural resources using multi-sensor remote sensing techniques and scenario analysis for sustainable management of these resources. Currently, I am working on the synergistic use of remote sensing and Unmanned Aerial Vehicles (UAVs) techniques to monitor the environment more precisely to solve environmental issues from a global to local scale. I am interested in conducting research in the field of applications of Geospatial techniques and machine learning algorithms to monitor terrestrial ecosystems and climate change interface. The ultimate goal of my research is to use transdisciplinary research methods to promote research on vulnerability, resilience and sustainability.

    ​I have worked as a Lead Author in the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) expert group on Deliverable 3(c). I am a recipient of the prestigious Green Talents Award by the Federal Ministry of Education and Research (BMBF), Germany. I have published numerous publications in several international peer-reviewed journal articles (150+), two books of international repute, and presented my work at various international and national conferences. I led various research projects as a Principal Investigator (PI) as well as a team member such as Asia-Pacific Network for Global Change Research (APN-GCR), Grants-in-Aid for Scientific Research (KAKENHI), Belmont Forum, Hirose grant, Kurata grant, Kajima grant etc.

  • Name (Japanese)

    Ram

  • Name (Kana)

    Avtar

  • Name

    201601021421362786

Alternate Names

Achievement

Research Experience

  • Hokkaido University Faculty of Environmental Earth Science Associate Professor
  • United Nations University, (UNU-IAS) Tokyo, Japan Research Fellow

Awards

  • 2023/04 Federal Ministry of Education and Research (BMBF), Germany Global Young Academy (GYA) Award-2023
  • 2023/02 Hokkaido University, Japan Hokkaido University President Award-2022

Published Papers

  • Kaushik Mandvikar, Nirmal Kumar, Hitesh Supe, Deepak Singh, Ankita Gupta, Pankaj Kumar, Gowhar Meraj, Inam Danish Khan, Asma Kouser, Santosh Kumar Pandey, Ram Avtar
    World Development Sustainability 5 2024/12 
    India is home to 11 % of the global urban population and is ranks as the second-largest urban system in the world. This study introduces a Heat Health Risk Index (HHRI) rankings for 37 major Indian cities with more than one million residents, using geospatial and socio-ecological data to identify potential heat health risk areas. In this study, the Otsu method was employed to determine the critical parameters in the heat health index, considering factors such as Land Surface Temperature (LST), solar radiation, population density, mean temperature, urban green cover, rainfall, specific humidity, and wind speed. All data values were standardized to a uniform scale (0–1) for comparability. The standardized values, integrated with the assigned weights, formed the HHRI. Results indicate that cities such as Chennai, Mumbai, Kolkata, and Ahmedabad, each with populations exceeding 10 million, are deemed less livable due to their high HHRI (>0.50). Both Chennai and Mumbai stand out with highest hazard index as 0.66, followed by Kolkata (0.62) and Ahmedabad (0.56). Cities that lack sufficient green spaces are often more vulnerable, display elevated risk levels, and have decreased adaptability. In contrast, cities such as Ludhiana, Theni, Amritsar, and Nabarangpur are perceived as the most livable, with a mean HHRI of 0.21, owing to their higher adaptive capacity and lower exposure. Overall, this study serves as a foundation for conceiving future perspective plans for existing urban and peri‑urban areas, compared to living standards within the realms of sustainability.
  • Ram Avtar, Xinyu Chen, Jinjin Fu, Saleh Alsulamy, Hitesh Supe, Yunus Ali Pulpadan, Albertus Stephanus Louw, Nakaji Tatsuro
    Remote Sensing 16 (21) 4060 - 4060 2024/10/31 
    Effective forest management necessitates spatially explicit information about tree species composition. This information supports the safeguarding of native species, sustainable timber harvesting practices, precise mapping of wildlife habitats, and identification of invasive species. Tree species identification and geo-location by machine learning classification of UAV aerial imagery offer an alternative to tedious ground surveys. However, the timing (season) of the aerial surveys, input variables considered for classification, and the model type affect the classification accuracy. This work evaluates how the seasons and input variables considered in the species classification model affect the accuracy of species classification in a temperate broadleaf and mixed forest. Among the considered models, a Random Forest (RF) classifier demonstrated the highest performance, attaining an overall accuracy of 83.98% and a kappa coefficient of 0.80. Simultaneously using input data from summer, winter, autumn, and spring seasons improved tree species classification accuracy by 14–18% from classifications made using only single-season input data. Models that included vegetation indices, image texture, and elevation data obtained the highest accuracy. These results strengthen the case for using multi-seasonal data for species classification in temperate broadleaf and mixed forests since seasonal differences in the characteristics of species (e.g., leaf color, canopy structure) improve the ability to discern species.
  • Huynh Vuong Thu Minh, Pankaj Kumar, Gowhar Meraj, Lam Van Thinh, Nigel K. Downes, Tran Van Ty, Nguyen Dinh Giang Nam, Fei Zhang, Bin Liu, Le Thien Hung, Dinh Van Duy, Tran Thi Truc Ly, Nguyen Quoc Luat, Ram Avtar, Mansour Almazroui
    Irrigation and Drainage 1531-0353 2024 
    The Mekong Delta, South East Asia's ‘rice bowl’, sustains more than 18 million people through its agricultural output. This yield is secured by efficient water management systems but is susceptible to climatic changes. As Vietnam's policies aim to optimize the delta's semi-mountainous regions reliant on rain-fed agriculture, this study investigates drought risks and climate change impacts on runoff in the O Ta Soc and O Tuk Sa reservoirs, An Giang Province, Vietnam. Using simulation models, we determined runoff volumes for specific rainfall return periods and climate scenarios for the 2030s and 2050s. Using the storm water management model (SWMM), we simulated the reservoir water balance considering rainfall, evaporation and infiltration. Our findings suggest potentially increased runoff and reservoir storage due to intensified monsoons and reduced off-season rainfall. The 4.77 km2 drainage of the O Ta Soc reservoir could benefit from this, while the 2.55 km2 drainage of the O Tuk Sa watershed may require alternative water-sourcing strategies. This research offers insights for drought predictions, flood management and water strategies in An Giang. To refine these predictions, future research should consider upcoming rainfall patterns.
  • H. V.T. Minh, P. Kumar, N. K. Downes, N. V. Toan, G. Meraj, P. C. Nguyen, K. N. Le, T. V. Ty, K. Lavane, R. Avtar, M. Almazroui
    Natural Hazards 0921-030X 2024 
    The Vietnamese Mekong Delta (VMD) is highly vulnerable to drought, particularly in the context of climate change. Prolonged drought during the dry season has emerged as a significant natural disaster, severely affecting agriculture and socioeconomic development in the region. To enhance water resource management and agricultural productivity, this study examines the characteristics of meteorological droughts using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) in the upper Mekong Delta of Vietnam. The Mann–Kendall (MK) test and Sen’s slope were employed to assess trends in drought and hydrological conditions. The results reveal no significant trends in rainfall, while average temperatures have increased significantly in most months, especially during the dry season. Although water levels and discharge at the Tan Chau and Chau Doc stations have decreased, significant reductions were primarily observed at Chau Doc station from 2000 to 2021. These findings provide critical insights for sustainable water resource management and planning in the VMD, considering future climate variability and changes in hydrological regimes.
  • Geetha Mohan, Lakshmi Narayana Perarapu, Saroj Kumar Chapagain, A. Amarender Reddy, Indrek Melts, Ranjeeta Mishra, Ram Avtar, Kensuke Fukushi
    Current Research in Environmental Sustainability 7 2024/01 
    This study investigates the adoption of water-saving irrigation technologies, specifically drip and sprinklers, within India's semi-arid states. Utilizing a probit model and data sourced from the India Human Development Survey-II, the research scrutinizes a sample size of 2891 households while engaging in focus group discussions. The findings highlight several key factors significantly impacting technology adoption, including education, caste, employment status, household income, orchard ownership, landholding size, irrigation source, access to irrigation, the Kisan Credit Card scheme, and utilization of electric and diesel pumps. Moreover, the study uncovers state-specific variations driven by factors such as water resources, crop patterns, and government policies, ultimately shaping the adoption landscape of specific irrigation technologies. Focus group discussions conducted in Andhra Pradesh reveal prominent challenges faced, including limited subsidies, high costs associated with adoption, and crop-specific irrigation requirements. In light of these findings, the study emphasizes the necessity for a comprehensive approach to achieve water conservation and enhance livelihoods. This approach advocates for the integration of joint farming practices, water-sharing methods, supportive financial policies encompassing subsidies and accessible credit facilities, and the implementation of sustainable government social schemes. Such integrated efforts are deemed imperative for fostering resilient societies amidst evolving agricultural and environmental landscapes.
  • Juan Xiao, Ashwani Kumar Aggarwal, Nguyen Hong Duc, Abhinandan Arya, Uday Kiran Rage, Ram Avtar
    Remote Sensing Applications: Society and Environment 32 2023/11 
    In remote sensing (RS), use of single optical sensors is frequently inadequate for practical Earth observation applications (e.g., agricultural, forest, ecology monitoring) due to trade-offs between spatial and temporal resolution. The advent of spatiotemporal fusion (STF) of RS images has allowed the production of images with high resolution at both spatial and temporal scales. Despite the development of more than 100 STF models in the past two decades, many of these models have not been practically applied due to the possibility of limited understanding of the models. Therefore, this study aims to provide a comprehensive review of STF methods, including their conception, development, challenges, and applications. This study focuses primarily on deep learning-based STF models, which achieved superior performance and significantly increased the number of STF models. This review can guide the selection and design of STF models, as well as proposes future directions for STF modeling. The findings of this review facilitate further STF research to improve the accuracy and application of fused RS images in the field of agriculture, forestry, and ecological monitoring.
  • Sudha Suresh, Gowhar Meraj, Pankaj Kumar, Deepak Singh, Inam Danish Khan, Ankita Gupta, Tarun Kumar Yadav, Asma Kouser, Ram Avtar
    Environmental Monitoring and Assessment 195 (10) 0167-6369 2023/10 
    Climate change and shifts in land use/land cover (LULC) are critical factors affecting the environmental, societal, and health landscapes, notably influencing the spread of infectious diseases. This study delves into the intricate relationships between climate change, LULC alterations, and the prevalence of vector-borne and waterborne diseases in Coimbatore district, Tamil Nadu, India, between 1985 and 2015. The research utilised Landsat-4, Landsat-5, and Landsat-8 data to generate LULC maps, applying the maximum likelihood algorithm to highlight significant transitions over the years. This study revealed that built-up areas have increased by 67%, primarily at the expense of agricultural land, which was reduced by 51%. Temperature and rainfall data were obtained from APHRODITE Water Resources, and with a statistical analysis of the time series data revealed an annual average temperature increase of 1.8 °C and a minor but statistically significant rainfall increase during the study period. Disease data was obtained from multiple national health programmes, revealing an increasing trend in dengue and diarrhoeal diseases over the study period. In particular, dengue cases surged, correlating strongly with the increase in built-up areas and temperature. This research is instrumental for policy decisions in public health, urban planning, and climate change mitigation. Amidst limited research on the interconnections among infectious diseases, climate change, and LULC changes in India, our study serves as a significant precursor for future management strategies in Coimbatore and analogous regions.
  • Sudha Suresh, Gowhar Meraj, Pankaj Kumar, Deepak Singh, Inam Danish Khan, Ankita Gupta, Tarun Yadav, Asma Kouser, Ram Avtar
    2023/06/28 
    Abstract Climate change, which encompasses variations in rainfall and temperature patterns, coupled with changes in land use/land cover (LULC), significantly impacts both the environment and society. These two factors, climate change and LULC shifts, have markedly affected human health, both directly and indirectly. Monitoring regional climate patterns, LULC changes, and disease outbreaks is crucial to ensure healthy living standards through a sustainable environment. This study investigates the correlation between climate change, LULC change, and the prevalence of infectious diseases transmitted by vectors and waterborne pathogens in Coimbatore district, Tamil Nadu, India, from 1985 to 2015. The study used Landsat-4, Landsat-5 and Landsat-8 data to generate LULC maps of the study area. The maximum likelihood algorithm facilitated the creation of these maps and detected changes for the years 1985, 2000, 2009, and 2015. Rainfall and temperature data for the study area were sourced from APHRODITE's Water Resources, and statistical analysis was applied to analyse these time series data. Infectious disease data was obtained from the Indian Council of Medical Research (ICMR), the Integrated Disease Surveillance Programme (IDSP), the National Vector Borne Disease Control Programme (NVBDCP), and the National Health System Resource Centre. These data were examined to identify trends in the occurrence of infectious diseases. The key findings of the study include (1) an overall increase in temperature and minor variations in rainfall in the study area during the study period; (2) an evident increase in built-up areas, as depicted by the LULC maps, attributable to industrialisation and population growth; (3) an emergence of dengue during the study period. The increasing patterns of vector-borne and water-borne diseases could be associated with changes in LULC and climate change. Given that the relationship between infectious diseases and their links to climate change and LULC changes has not been extensively researched in the Indian context, this study intends to contribute to a deeper understanding and delineation of future strategies in Coimbatore, India.
  • Juan Xiao, Stanley Anak Suab, Xinyu Chen, Chander Kumar Singh, Dharmendra Singh, Ashwani Kumar Aggarwal, Alexius Korom, Wirastuti Widyatmanti, Tanjinul Hoque Mollah, Huynh Vuong Thu Minh, Khaled Mohamed Khedher, Ram Avtar
    Measurement: Journal of the International Measurement Confederation 214 0263-2241 2023/06/15 
    The advancement of unmanned aerial vehicles (UAVs) offers precise and accurate spectral and spatial information about crops and plays a pivotal role in precision agriculture. This study used UAVs, geographic information systems (GIS), and deep learning technology to monitor corn growth performance across different management practices. Two experimental corn fields were divided into four plots to evaluate the effects of varying corn management practices (i.e., seeding schedule, planting depth, and fertilization method) on corn growth performance. RGB and MicaSense multispectral cameras were mounted on UAVs to collect corn field images. YOLOv5 was investigated for counting corn plants. Plant height, Normalized Difference Vegetation Index (NDVI), Normalized Difference Red-Edge Index (NDRE), plant density, and plant volume were mapped based on UAV images. Additionally, the Otsu thresholding method was evaluated as an automatic method for separating plant height, NDVI, and NDRE values from the background. YOLOv5 and Otsu thresholding were efficient and accurate for automatically counting corn plants and extracting corn plant heights as well as VIs, respectively. The emergence rates of corn seeds were 40%, 33%, 41%, and 62% in plots A, B, C, and D, respectively. Variations in corn field management practices significantly affected the emergence rate, with fertilizer application close to seeds emerging as the optimal practice for achieving higher emergence rates across experimental plots. This study used deep learning and UAV to provide precise information and valuable insights into corn field practices, which can help farmers optimize corn cultivation. The techniques applied in this study could be extrapolated to improve cultivation processes for other crops.
  • Alton C. Byers, Marcelo Somos-Valenzuela, Dan H. Shugar, Daniel McGrath, Mohan B. Chand, Ram Avtar
    2023/05/24 
    Abstract. Beginning in December 2020, a series of small-to-medium, torrent-like pulses commenced upon a historic debris cone located within the Nupchu valley, Kanchenjunga Conservation Area (KCA), Nepal. Sometime between 16 and 21 August 2022 a comparatively large ice-debris avalanche event occurred, covering an area of 0.6 km2 with a total estimated volume of order 106 m3. Changing cryospheric conditions throughout the region suggest that the installation of preventative floodwater diversion mechanisms for vulnerable villages is warranted, improved reporting mechanisms to authorities, and early warning systems. More systematic monitoring via remote sensing platforms and hazard mapping by scientists is also indicated.
  • Ali P. Yunus, Xinyu Chen, Filippo Catani, Srikrishnan Siva Subramaniam, Xuanmei Fan, Dou Jie, K. S. Sajinkumar, Ankita Gupta, Ram Avtar
    SCIENTIFIC REPORTS 13 (1) 2045-2322 2023/05 
    Quantifying landslide volumes in earthquake affected areas is critical to understand the orogenic processes and their surface effects at different spatio-temporal scales. Here, we build an accurate scaling relationship to estimate the volume of shallow soil landslides based on 1 m pre- and post-event LiDAR elevation models. On compiling an inventory of 1719 landslides for 2018 M-w 6.6 Hokkaido-Iburi earthquake epicentral region, we find that the volume of soil landslides can be estimated by gamma = 1.15. The total volume of eroded debris from Hokkaido-Iburi catchments based on this new scaling relationship is estimated as 64-72 million m(3). Based on the GNSS data approximation, we noticed that the co-seismic uplift volume is smaller than the eroded volume, suggesting that frequent large earthquakes (and rainfall extremes) may be counterbalancing the topographic uplift through erosion by landslides, especially in humid landscapes such as Japan, where soil properties are rather weak.
  • Ai Hojo, Ram Avtar, Tatsuro Nakaji, Takeo Tadono, Kentaro Takagi
    Ecological Informatics 74 101973 - 101973 1574-9541 2023/05
  • Mamoru Ishikawa, Ram Avtar, Shixin Mo
    Land Degradation & Development 34 (9) 2707 - 2719 1085-3278 2023/04/05 
    Abstract Permafrost in Mongolia shows highly heterogeneous features in space and the contents of ground ice are dependent on the local geographies such as topography, ground wetness, and vegetation cover. Recent permafrost degradation would cause thawing and disappearance of ground ice, destabilizing and subsiding the ground surface. This study aimed to detect topographic deformation related to irreversibly changing ground ice over the permafrost terrain of Mongolia. To end this we used interferometric synthetic aperture RADAR (InSAR) technique, which is capable to measure vertical ground deformation on a centimeter scale. Advanced land observing satellite‐based phased array type L‐band synthetic aperture radar (PALSAR) images (June to September 2007 to 2010) and PALSAR‐2 images (June to September 2014 to 2017) quantified near‐year‐round displacement of the ground surface. The overall deformation was in a range of −3 to 3 cm (subsidence and uplift, respectively) between the image interval and relatively high subsidence occurred during warm years. The areas experiencing consecutive uplift and subsidence correspond to ground underlain by ice‐rich soils, indicating the dominant roles of thawing and growing ground ice for local deformation over permafrost terrain. We discuss the relation of observed ground deformation trends with regional climate and local geohydrology that influence ground ice formation.
  • Nabin Bhattarai, Bhaskar Singh Karky, Ram Avtar, Rajesh Bahadur Thapa, Teiji Watanabe
    Sustainability 15 (7) 6078 - 6078 2023/03/31 
    The Paris Agreement recognized the significant role of forests in climate change mitigating and adapting. It also emphasized the importance of the Reducing Emissions from Deforestation and forest Degradation (REDD+) mechanism as a vital tool for achieving the goal of limiting global warming to 1.5 °C above pre-industrial levels. This study aims to assess the REDD+ readiness of Bhutan, India, Myanmar, and Nepal in preparation for effectively implementing REDD+ at the national level. A total of 57 indicators across five categories were used to evaluate readiness: overall readiness, technical readiness, institutional readiness, financing readiness, and strategy and safeguard readiness. The indicator-based questionnaire was administered to government officials, NGOs, private sectors, and academics. The results showed that Nepal was slightly more advanced in overall readiness, owing in part to the longer readiness period of the World Bank-supported Terai Arc ER-P. India scored highly in technical readiness and has several sub-national programmes for REDD+ implementation. Bhutan had strong ratings for strategy and safeguard readiness but lower scores for institutional and financing readiness. Myanmar had consistent ratings across readiness areas, but a lower score for technical readiness. However, political and governance situations pose significant challenges to the effective implementation of REDD+ in Myanmar.
  • Vishal Mishra, Ram Avtar, A. P. Prathiba, Prabuddh Kumar Mishra, Anuj Tiwari, Surendra Kumar Sharma, Chandra Has Singh, Bankim Chandra Yadav, Kamal Jain
    Advances in Civil Engineering 2023 1687-8086 2023/02/06 
    Uncrewed aerial systems (UASs) are becoming very popular in the domain of water resource mapping and management (WRMM). Being a cheaper and quicker option capable of providing high temporal and spatial resolution data, UAS has become a much sought-after platform for remote sensing. Still, their application in the field is in its early stage. This paper encompasses basic concepts of UAS, different payloads and sensor technologies available, various methodologies for its application in WRMM, different software available, and challenges associated with them, thus presenting a comprehensive review of multiple applications of UAS in different sub-domains of water resources. From cryosphere, rivers and lakes, and coastal areas to sub-surface water, as well as from water quality to wastewater management, the authors have discussed various applications of uncrewed aerial vehicles. At the end of the paper, the authors have identified the issues posing problems in the wider implementation of UAS in WRMM. Also, the future scope of the UAS in WRMM has been discussed.
  • Chee Kong Yap, Bin Huan Pang, Wan Hee Cheng, Krishnan Kumar, Ram Avtar, Hideo Okamura, Yoshifumi Horie, Moslem Sharifinia, Mehrzad Keshavarzifard, Meng Chuan Ong, Abolfazl Naji, Mohamad Saupi Ismail, Wen Siang Tan
    Applied Sciences 13 (2) 1042 - 1042 2023/01/12 
    The present investigation focused on the toxicity test of cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn), utilizing two groups of juvenile and adult apple snail Pomacea insularum (Gastropod, Thiaridae) with mortality as the endpoint. For the adult snails, the median lethal concentrations (LC50) values based on 48 and 72 h decreased in the following order: Cu < Ni < Pb < Cd < Zn. For the juvenile snails, the LC50 values based on 48 and 72 h decreased in the following order: Cu < Cd < Ni < Pb < Zn. The mussel was more susceptible to Cu than the other four metal exposures, although the juveniles were more sensitive than the adults because the former had lower LC50 values than the latter. This study provided essential baseline information for the five metal toxicities using P. insularum as a test organism, allowing comparisons of the acute sensitivity in this species to the five metals. In conclusion, the present study demonstrated that P. insularum was a sensitive biomonitor and model organism to assess heavy metal risk factors for severe heavy metal toxicities. A comparison of the LC50 values of these metals for this species with those for other freshwater gastropods revealed that P. insularum was equally sensitive to metals. Therefore, P. insularum can be recommended as a good biomonitor for the five metals in freshwater ecosystems.
  • Anjar Dimara Sakti, Pitri Rohayani, Nurusshobah Ainul Izzah, Nur Afrizal Toya, Pradita Octoviandiningrum Hadi, Thanti Octavianti, Wendi Harjupa, Rezzy Eko Caraka, Yunho Kim, Ram Avtar, Nattapong Puttanapong, Chao-Hung Lin, Ketut Wikantika
    Scientific Reports 13 (1) 2023/01/07 
    Abstract Amid its massive increase in energy demand, Southeast Asia has pledged to increase its use of renewable energy by up to 23% by 2025. Geospatial technology approaches that integrate statistical data, spatial models, earth observation satellite data, and climate modeling can be used to conduct strategic analyses for understanding the potential and efficiency of renewable energy development. This study aims to create the first spatial model of its kind in Southeast Asia to develop multi-renewable energy from solar, wind, and hydropower, further broken down into residential and agricultural areas. The novelty of this study is the development of a new priority model for renewable energy development resulting from the integration of area suitability analysis and the estimation of the amount of potential energy. Areas with high potential power estimations for the combination of the three types of energy are mostly located in northern Southeast Asia. Areas close to the equator, have a lower potential than the northern countries, except for southern regions. Solar photovoltaic (PV) plant construction is the most area-intensive type of energy generation among the considered energy sources, requiring 143,901,600 ha (61.71%), followed by wind (39,618,300 ha; 16.98%); a combination of solar PV and wind (37,302,500 ha; 16%); hydro (7,665,200 ha; 3.28%); a combination of hydro and solar PV (3,792,500 ha; 1.62%); and a combination of hydro and wind (582,700 ha; 0.25%). This study is timely and important because it will inform policies and regional strategies for transitioning to renewable energy, with consideration of the different characteristics present in Southeast Asia.
  • Priyanka, Rajat, Ram Avtar, Rashmi Malik, M. Musthafa, Virendra S. Rathore, Praveen Kumar, Gulab Singh
    Remote Sensing Applications: Society and Environment 29 100924 - 100924 2352-9385 2023/01
  • Juan Xiao, Ashwani Kumar Aggarwal, Uday Kiran Rage, Vaibhav Katiyar, Ram Avtar
    IEEE Access 2023 
    Spatiotemporal fusion (STF) techniques play important roles in Earth observation analysis as they can produce images with both high spatial and temporal resolution. However, existing STF models often fuse images from various satellites, not satisfying the demand for precise crop monitoring. In contrast, unmanned aerial vehicle (UAV) images can deliver detailed data, and deep learning (DL)-based STF models have a high potential for automatically extracting abstract features. To this end, this study proposed a novel end-to-end DL-based STF model named UAV-Net, which can produce centimeter-scale UAV images. UAV-Net has an encoder-decoder architecture with Modified ResNet (MResNet), Feature Pyramid Network (FPN), and decoder modules. The encoder uses MResNet modules to extract input features, while the FPN module performs a multiscale fusion of these features before reconstructing UAV images using transposed convolution in the decoder module. Through the comparison and ablation experiments, this study evaluated the efficacies of the MResNet modules with 18, 34, and 50 layers, along with FPN module of UAV-Net. The experimental results on real-world datasets demonstrated that UAV-Net adequately produce UAV images both visually and quantitatively. Furthermore, Comparison with state-of-the-art STF models highlights the innovative and effective of UAV-Net for producing centimeter-scale images. The predicted centimeter-scale images have the potential to be useful for various environmental monitoring applications.
  • MAJID FAROOQ, Dr. Fayma Mushtaq, Gowhar Meraj, Suraj Kumar Singh, SHRUTI KANGA, Ankita Gupta, Pankaj Kumar, Deepak Singh, Ram Avtar
    Resources 11 (12) 2022/12 
    Rapid urbanization has led to the emergence of slums in many developing and industrialized nations. It degrades the quality of life and burdens the urban amenities resulting in uneven distribution of slums. The majority of people in the developing world live in squatter settlements and these random gatherings disrupt the economic and social developmental plans of the concerned country. No suitable planning framework has been created for replicability on a considerable scale, despite the fact that slum upgrading is acquiring worldwide importance as a political issue. In recent years Jammu City has witnessed high population growth rates resulting in an uneven provision of urban amenities and a surge in slum areas. This paper focuses on a method-based approach using Management Information System (MIS) and Geographic Information System (GIS) for upgrading slums and recommends a planning outline using the approach formulated by the Government of India under the scheme named “Rajiv Awas Yojna” (RAY). The aim of this study is to assess the status of slums, propose redevelopment plans, and highlight the roles of different planning agencies to accomplish the redevelopment goals. The study concludes by postulating several recommendations for upgrading slums and formulating a framework that can be used in other similar areas for development.
  • Hafeza Nujaira, Kumar Arun Prasad, Pankaj Kumar, Ali P. Yunus, Ali Kharrazi, L. N. Gupta, Tonni Agustiono Kurniawan, Haroon Sajjad, Ram Avtar
    PLoS ONE 17 (12 December) 2022/12 
    Despite Bangladesh being one of the leading countries in aquaculture food production worldwide, there is a considerable lack of updated scientific information about aquaculture activities in remote sites, making it difficult to manage sustainably. This study explored the use of geospatial and field data to monitor spatio-temporal changes in aquaculture production sites in the Satkhira district from 2017-2019. We used Shuttle Radar Topographic Mission digital elevation model (SRTM DEM) to locate aquaculture ponds based on the terrain elevation and slope. Radar backscatter information from the Sentinel-1 satellite, and different water indices derived from Sentinel-2 were used to assess the spatio-temporal extents of aquaculture areas. An image segmentation algorithm was applied to detect aquaculture ponds based on backscattering intensity, size and shape characteristics. Our results show that the highest number of aquaculture ponds were observed in January, with a size of more than 30,000 ha. Object-based image classification of Sentinel-1 data showed an overall accuracy above 80%. The key factors responsible for the variation in aquaculture were investigated using field surveys. We noticed that despite a significant number of aquaculture ponds in the study area, shrimp production and export are decreasing because of a lack of infrastructure, poor governance, and lack of awareness in the local communities. The result of this study can provide in-depth information about aquaculture areas, which is vital for policymakers and environmental administrators for successful aquaculture management in Satkhira, Bangladesh and other countries with similar issues.
  • Xinyu Chen, Ram Avtar, Deha Agus Umarhadi, Albertus Stephanus Louw, Sourabh Shrivastava, Ali P. Yunus, Khaled Mohamed Khedher, Tetsuya Takemi, Hideaki Shibata
    Weather and Climate Extremes 38 100494 - 100494 2212-0947 2022/12 
    The frequency and intensity of typhoons have increased due to climate change. These climate change-induced disasters have caused widespread damage to forests. Evaluation of the effects of typhoons on forest ecosystems is often complex and challenging, mainly because of their sporadic nature. In this paper, we compared existing forest damage estimation techniques with the goal of identifying their respective advantages and suitable use cases. We considered Hokkaido in northern Japan as a case study, where three typhoons successively struck in 2016 and led to forest destruction. Forest damage was estimated from Landsat 8 imagery by three approaches, namely using vegetation damage indices (DVDI, DNDVI and ΔEVI), using supervised classification with Random Forest (RF) and Support Vector Machines (SVM) and finally by using the commercial CLASlite software with built-in methods to detect forest disturbance. Machine learning classifiers obtained the highest damage assessment accuracy, but intensive computation and complex processing steps were required. The RF and SVM classifiers gave the highest accuracies when using Fractional Cover as a predictor variable (Overall Accuracy = 80.36% in both cases, and ROC AUC values of 0.89 and 0.88, respectively.) Among the vegetation damage indices, DNDVI produced the highest accuracy (AUC = 0.85, OA = 77.68%). The most damaged areas were on the windward slopes, where forest patches were exposed to the brunt of the typhoon winds. Forest damage also peaked at the highest elevations in the study area, possibly representing exposed hilltops. Methods and findings presented in this study can help stakeholders to implement more effective forest damage monitoring after typhoons and other extreme weather events in the future.
  • Pankaj Kumar, Ram Avtar
    Water 14 (21) 3490 - 3490 2022/11 
    For eternity, water resources have proven to be the key to inclusive social development and human well-being [...]
  • Huynh Vuong Thu Minh, Pankaj Kumar, Tran Van Ty, Duy Dinh Van, Tran Gia Han, Lavane Kim, Ram Avtar
    Hydrology 2022/11
  • Nguyen Van Xuan, Nguyen Ngoc Long Giang, Tran Van Ty, Pankaj Kumar, Nigel K. Downes, Nguyen Dinh Giang Nam, Nguyen Vo Chau Ngan, Lam Van Thinh, Dinh Van Duy, Ram Avtar, Huynh Vuong Thu Minh
    Water Supply 22 (11) 7945 - 7959 1606-9749 2022/10/12 
    Abstract This paper examines the impact of the dike systems on river flows in the Vietnamese Mekong Delta (VMD). The study combined a hydrological change index method and the Mann–Kendall test to assess the temporal dynamics of both discharge and water levels along the main rivers of the VMD. Results highlight that the system of rivers and canals helps facilitate waterway traffic and drainage during the flood season. However, the low elevation of the delta has created conditions suitable for saline water to increasingly penetrate upstream during the dry season. Observed changes in the hydrological indicators at the upstream stations of Tan Chau (Mekong River) and Chau Doc (Bassac River) are not only due to the dike system but also upstream alterations to the flow regime. More research is needed to consider the various drivers of flow-regime change associated with natural and human activities both inside and outside of the study area.
  • Manish Ramaiah, Ram Avtar, Pankaj Kumar
    Hydrology 2022/10
  • Huynh Vuong Thu Minh, Tran Van Ty, Ram Avtar, Pankaj Kumar, Kieu Ngoc Le, Nguyen Vo Chau Ngan, Luong Huy Khanh, Nguyen Cong Nguyen, Nigel K. Downes
    Environmental Monitoring and Assessment 194 (S2) 0167-6369 2022/09
  • Xuanmei Fan, Ali P. Yunus, Ying-Hui Yang, Srikrishnan Siva Subramanian, Chengbin Zou, Lanxin Dai, Xiangyang Dou, Allu Chinna Narayana, Ram Avtar, Qiang Xu, Runqui Huang
    Science of The Total Environment 836 155380 - 155380 0048-9697 2022/08
  • Albertus S. Louw, Jinjin Fu, Aniket Raut, Azim Zulhilmi, Shuyu Yao, Miki McAlinn, Akari Fujikawa, Muhammad Taimur Siddique, Xiaoxiao Wang, Xinyue Yu, Kaushik Mandvikar, Ram Avtar
    Remote Sensing Applications: Society and Environment 27 2022/08 
    Remotely sensed imagery is used as a tool to aid decision makers and scientists in a variety of fields. A recent world event in which satellite imagery was extensively relied on by a variety of stakeholders was the COVID-19 pandemic. In this article we aim to give an overview of the types of information offered through remote sensing (RS) to help address different issues related to the pandemic. We also discuss about the stakeholders that benefited from the data, and the value added by its availability. The content is presented under four sub-sections; namely (1) the use of RS in real-time decision-making and strategic planning during the pandemic; how RS revealed the (2) environmental changes and (3) social and economic impacts caused by the pandemic. And (4) how RS informed our understanding of the epidemiology of SARS-CoV-2, the pathogen responsible for the pandemic. High resolution optical imagery offered updated on-the-ground data for e.g., humanitarian aid organizations, and informed operational decision making of shipping companies. Change in the intensity of air and water pollution after reduced anthropogenic activities around the world were captured by remote sensing – supplying concrete evidence that can help inform improved environmental policy. Several economic indicators were measured from satellite imagery, showing the spatiotemporal component of economic impacts caused by the global pandemic. Finally, satellite based meteorological data supported epidemiological studies of environmental disease determinants. The varied use of remote sensing during the COVID-19 pandemic affirms the value of this technology to society, especially in times of large-scale disasters.
  • Ram Avtar, Apisai Vakacegu Rinamalo, Deha Agus Umarhadi, Ankita Gupta, Khaled Khedher, Ali P Yunus, Bhupendra P. Singh, Pankaj Kumar, Dr. Netrananda Sahu, Anjar Dimara Sakti
    Land 11 (8) 2022/08 
    This study examines land use changes and evaluates the past and projected forest carbon sequestration and its valuation in Viti Levu Island, Fiji, through a combination of remote sensing with a geospatial-based modeling approach. Land use classification was performed using Landsat 7 and Landsat 8 imageries of the years 2000 and 2020; then, cellular automata and artificial neural network (CA-ANN) modeling was conducted to predict the land use map of 2040. Carbon sequestration and the economic valuation were estimated using the land use maps of the past, present, and future (2000, 2020, and 2040) within the Integrated Valuation of Ecosystems Trade-off (InVEST) model. The results showed that deforestation occurred during the past two decades, and the forest area was predicted to keep decreasing in 2040, with the major contribution from the conversion to the agricultural area. Local communities’ perceptions confirmed that the forest conversion to croplands would persist due to the demand for fertile lands. This study estimated a loss of −7.337 megatonnes of forest carbon (Mt C) with an economic loss of USD −1369.38 million during 2000–2020 due to deforestation. If the business-as-usual scenario does not change in the near future, a potential carbon loss of −7.959 Mt C is predicted in the upcoming 20 years. The predicted results can be used to assist as a reference in establishing a national baseline and reference level for implementing the REDD+ mechanism in Fiji and sustainably managing the limited pristine forest by implementing forest-related programs.
  • Nabin Bhattarai, Sishir Dahal, Sunil Thapa, Saurav Pradhananga, Bhaskar Singh Karky, Ranjeet Sing Rawat, Kai Windhorst, Teiji Watanabe, Rajesh Bahadur Thapa, Ram Avtar
    Journal of Forest and Livelihood 21 (1) 14 - 31 1684-0186 2022/06/01 
    Forest fire has been one of the compelling issues in the Hindu Kush Himalayan (HKH) region. To promote regeneration, clearing fields for agriculture, hunting, and security reasons, local people deliberately set forests on fire. In this paper, active fire incidents, temperature, precipitation, and the changes of Aerosol Optical Depth (AOD) and Carbon monoxide (CO) value associated with forest fire were evaluated. The active forest fire incidents obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite are supplemented by the ERA5-land dataset to see the relation between precipitation and temperature with forest fires. MODIS and Tropospheric Monitoring Instrument (TROPOMI) sensor datasets were used to see the changes in AOD and CO in the region. MODIS sensor detected more than 30,462 active fires incidents in March and April 2021 in the study areas. Shan State of Myanmar recorded the maximum number of active fire incidents which is due to the practice of shifting cultivation and minimum in Bhutan due to the awareness campaigns and technology improvement. The temperature recorded in the study sites shows an increasing trend as compared to the reference period (2010-2020). Apart from Shan and Bago of Myanmar, precipitation in the study sites is also less during the study period. AOD and CO values show prominent peaks in a fire season which coincide with days of the maximum number of fire counts inferring the influence of forest fire on air quality. Developing countries like Nepal, India, Myanmar, and Bhutan are willing to take part in climate finance and are bound to accept expensive insurance premium due to forest fire incidents. Unless forest fires are effectively managed and mitigated, achieving Nationally Determined Contributions (NDCs) and global agendas, including United Nations Decade of Ecosystem Restoration is onerous.
  • Hao Chen, Ali P. Yunus, Sravanthi Nukapothula, Ram Avtar
    Physics and Chemistry of the Earth 126 1474-7065 2022/06 
    Numerous shallow thermokarst lakes in northern Alaska's Arctic coastal plains recently show a decline in lake abundance and area due to global warming. While in a few lakes, bathymetric surveys have been completed using sonar instruments, the majority of the lakes in the region have not been surveyed primarily because of logistical issues pertaining to the remoteness of these sites. Employing machine learning models together with Google Earth Engine (GEE), in this study, we mapped the bathymetry of hundreds of Arctic coastal lakes using Landsat-8 OLI images. Our results show that satellite-derived bathymetry is capable of retrieving depths up to 21 m, consistent with field data. Furthermore, the results show agreement to within 0.55 m mean absolute error (MAE) and 0.9 m root mean square error (RMSE), with an accuracy of over 88%. The average lake depth in the region was found to be 1.44 m. Among the various machine learning models employed, random forest (RF) outclassed both classification and regression trees (CART) and support vector machines (SVM) in estimating the depth values. High-resolution and spatially extensive bathymetric datasets developed in this study complement climate warming and degradation studies in the Arctic coastal plains.
  • Prof. Dr. Chee Kong Yap, Muhammad Saleem, Wen Siang Tan, Wan Mohd Syazwan, Noor Azrizal-Wahid, Rosimah Nulit, Mohd. Hafiz Ibrahim, Muskhazli Mustafa, Mohd Amiruddin Abd Rahman, Franklin Berandah Edward, Takaomi Arai, Wan Hee Cheng, Hideo Okamura, Mohamad Saupi Ismail, Krishnan Kumar, Ram Avtar, Khalid Al-Mutairi, Al-Shami S. A., Geetha Subramaniam, Ling Shing Wong
    Pollutants 2 (3) 269 - 288 2022/06 
    The ecological and children’s Health Risk Assessments (HRA) of Copper (Cu) in aquatic bodies ranging from rivers, mangrove, estuaries, and offshore areas were studied using the Cited Cu Data in The Sediments (CCDITS) from 125 randomly selected papers published from 1980 to 2022. The ecological and children’s HRA were assessed in all CCDITS. Generally, local point Cu sources (8%) and lithogenic sources were the main controlling factors of Cu concentrations. The present review revealed three interesting points. First, there were 11 papers (8%) documenting Cu levels of more than 500 mg/kg dw while China was the country with the highest number (26%) of papers published between 1980 and 2022, out of 37 countries. Second, with the Cu data cited from the literature not normally distributed, the maximum Cu level was higher than all the established guidelines. However, the median Cu concentration was lower than most of the established guidelines. The median values of the geoaccumulation index (Igeo) indicated a status of ‘unpolluted‘ and ‘moderate contamination’ for the contamination factor (CF), and ‘low potential ecological risk’ for the ecological risk (ER) of Cu. However, the Cu ER could be based at present on the above mentioned 8% of the literature in the present study. Third, the calculated hazard index (HI) values were found to be below 1, indicating no potential chance of Cu non–carcinogenic effects in both adults and children, except for children’s HI values from Lake Pamvotis of Greece, and Victoria Harbor in Hong Kong. Thus, regular monitoring (every 2 years), depending upon the available resources, is recommended to assess the ecological–health risk of Cu pollution in aquatic bodies to abate the risk of Cu exposure to children’s health and avoid injurious impacts on the biota. It can be concluded that there is always a need for the mitigation and management of a Cu exposure risk assessment that can be used successfully for screening purposes to detect important human health exposure routes. Consequently, any sediments contaminated with Cu require rapid sediment remediation techniques.
  • Raveena Raj, Ali P. Yunus, Padmini Pani, Ram Avtar
    Land Degradation & Development 33 (9) 1495 - 1510 1085-3278 2022/05/30 
    High-resolution multi-temporal digital elevation model (DEM) are key to accurate mapping of gully erosion volume change studies. Owing to the lack of multi-temporal DEM at a high spatial resolution, gully development rate, and gully erosion-fill volume change estimates in the Indian badlands are poorly studied. Our study explored the use of multi-temporal TerraSAR-X add-on for digital elevation measurement (TanDEM-X) derived elevation models to quantify the erosion volume and gully susceptibility mapping in the Chambal badlands, Central India. The average volume of gully erosion based on the DEM subtraction method in the study area was found to be 135 × 105 m3, and the estimated annual rate of soil erosion was ~284 t hr−1 yr−1. Using machine learning models, we trained these data for gully erosion susceptibilities and volume prediction for a larger study region; and validated the results with independent samples. The accuracy of the model in terms of area under the receiver operating curve (AUC) values has reached 0.85 for training and 0.87 for validation, indicating satisfactory model performance. After validation, the best fit model was implemented onto a testing site (no multi-temporal DEM available) in order to predict erosion zones and erosion volume estimation. The model predicted that about 40% of the area is highly affected by gully erosion, with the maximum gullying process in the north-Central and lowest in the southwest parts of the testing area. The research framework presented in this study can be useful in estimating the erosion rate in the badlands of the Chambal Valley and can be used effectively in ravine reclamation projects.
  • Nguyen Hong Duc, Pankaj Kumar, Pham Phuong Lan, Tonni Agustiono Kurniawan, Khaled Mohamed Khedher, Ali Kharrazi, Osamu Saito, Ram Avtar
    Natural Hazards 117 (3) 2573 - 2615 0921-030X 2022/05/26 
    Can Tho City is experiencing water stress driven by rapid global changes. This study assesses the spatiotemporal variation in surface water quality (SWQ) through a multivariate statistical approach to provide evidence-based scientific information supporting sustainable water resource management and contributing to achieving the city’s sustainable development goals (SDGs). The complex SWQ dataset with 14 monthly-measured parameters at 73 sampling sites throughout the city was collected and analyzed. The obtained results indicated that average concentrations of biochemical oxygen demand, chemical oxygen demand (COD), dissolved oxygen (DO), total coliform, turbidity, total suspended solids, and phosphate (PO43−) exceeded the permissible national levels. Spatially, cluster analysis had divided the city’s river basin into three different zones (mixed urban-industrial, agricultural, and mixed urban–rural zones). The key sources of SWQ pollution in these three zones were individually identified by principal component/factor analysis (PCA/FA), which were mainly related to domestic wastewater, industrial effluents, farming runoff, soil erosion, upstream sediment flows, and severe droughts. Discriminant analysis also explored that COD, DO, turbidity, nitrate (NO3−), and PO43− were the key parameters discriminating SWQ in the city among seasons and land-use zones. The temporally analyzed results from weighted arithmetic water quality index (WAWQI) estimation revealed the deterioration of SWQ conditions, whereby the total polluted monitoring sites of the city increased from 29% in 2013 to 51% in 2019. The key drivers of this deterioration were the expansion in built-up and industrial land areas, farming runoff, and droughts. Graphical abstract: [Figure not available: see fulltext.].
  • Tonni Agustiono Kurniawan, Mohd Hafiz Dzarfan Othman, Mohd Ridhwan Adam, Hui Hwang Goh, Ayesha Mohyudin, Ram Avtar, Tutuk Djoko Kusworo
    Chemical Papers 76 (8) 5001 - 5010 0366-6352 2022/04/30
  • Deha Agus Umarhadi, Wirastuti Widyatmanti, Pankaj Kumar, Ali P. Yunus, Khaled Mohamed Khedher, Ali Kharrazi, Ram Avtar
    SCIENCE OF THE TOTAL ENVIRONMENT 816 0048-9697 2022/04 
    Peatlands in Indonesia are subject to subsidence in recent years, resulting in significant soil organic carbon loss. Their degradation is responsible for several environmental issues; however, understanding the causes of peatland subsidence is of prime concern for implementing mitigation measures. Here, we employed time-series Small BAseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) using ALOS PALSAR-2 images to assess the relationship between subsidence rates and land use/land cover (LULC) change (including drainage periods) derived from decadal Landsat data (1972-2019). Overall, the study area subsided with a mean rate of -2.646 +/- 1.839 cm/year in 2018-2019. The subsidence rates slowed over time, with significant subsidence decreases in peatlands after being drained for 9 years. We found that the long-time persistence of vegetated areas leads to subsidence deceleration. The relatively lower subsidence rates are in areas that changed to rubber/mixed plantations. Further, the potential of subsidence prediction was assessed using Random Forest (RF) regression based on LULC change, distance from peat edge, and elevation. With an R-2 of 0.532 (RMSE = 0.594 cm/year), this machine learning method potentially enlarges the spatial coverage of InSAR method for the higher frequency SAR data (such as Sentinel-1) that mainly have limited coverage due to decorrelation in vegetated areas. According to feature importance in the RF model, the contribution of LULC change (including drainage period) to the subsidence model is comparable with distance from peat edge and elevation. Other uncertainties are from unexplained factors related to drainage and peat condition, which need to be accounted for as well. This work shows the significance of decadal LULC change analysis to supplement InSAR measurement in tropical peatland subsidence monitoring programs.
  • Bui Thi Bich Lien, Nguyen Thi Thanh Ngan, Pankaj Kumar, Trinh Trung Tri Dang, Tran Thi Kim Hong, Tran Van Ty, Ram Avtar, Huynh Vuong Thu Minh
    Urban Science 6 (1) 21 - 21 2022/03/09 
    Protected places such as nature reserves (NRs) are used to maintain ecological balance, biodiversity, and support surrounding ecosystems. However, the development and operation of infrastructure such as dikes and sluice gates in NRs, as seen in the Vietnamese Mekong Delta (VMD), often adversely affects the hydrological regime and water quality at both local and regional scales. This study analyzes the consequences of a constructed dike system on the hydrological regime and water quality in the NRs through an integrated approach including hydrochemical analysis (using descriptive statistics and weighted arithmetic water quality index (WAWQI) analysis), traditional interviews (face to face), using semi-structured questionnaires, field surveys, and secondary data. Results show that constructed infrastructure has helped maintain water supplies for both livelihoods and forest fire prevention. However, considerable impacts on the hydrological regime and water quality have occurred. From water quality assessments in three NRs, 29% of sampling sites in the My Phuoc melaleuca forest (MPMF) had WAWQI values over 100, while all sites in Lung Ngoc Hoang NR (LNHNR) and Mua Xuan Agriculture Center (MXAC) had WAWQI values over 100. This was to a large extent due to elevated concentration of chemical oxygen demand (COD), biological oxygen demand (BOD5), and phosphate (PO43−). Meanwhile, during the wet season, pollution was marginally reduced by dilution, with 42.86% of sites at Lung Ngoc Hoang NR, 28.57% of sites at MXAC, and 78.57% of sites at MPMF having WAWQI values of less than 100. These results show the issue of water pollution at spatio-temporal scales, and call for better holistic management options for improving the hydrological regime and water quality.
  • Atul Saini, Netrananda Sahu, Weili Duan, Manish Kumar, Ram Avtar, Manoranjan Mishra, Pankaj Kumar, Rajiv Pandey, Swadhin Behera
    Frontiers in Earth Science 10 2022/03/04 
    India observes the summer monsoon in June–July–August–September (JJAS) season, and the livelihood security of a huge population depends on it. The impact of the monsoon onset timing, length of monsoon season, rainfall amount, and related extreme events is huge on the Indian economy. Therefore, understanding the inherent intricacies needed a detailed investigation. In five homogenous monsoon regions of India, the trend of monsoon onset and the length of monsoon season are examined. The association between 1) monsoon onset ∼ rainfall amount, 2) length of monsoon season ∼ rainfall amount, and 3) monsoon onset ∼ length of monsoon season is investigated. Subsequently, the behavior of rainfall and extreme excess days in the ±1 standard deviation (SD) length of monsoon season is also examined in detail. The trend for monsoon onset shows late onset in all the homogenous monsoon regions except the northeast region. The length of monsoon season is found increasing significantly with high magnitude in west central and northwest regions. A significantly strong negative correlation (∼−0.6) for monsoon onset timing ∼ length of monsoon season is observed. Therefore, the change in rainfall anomaly, extreme excess days, and rainy days is done concerning the length of the monsoon season. In the cases of the −1 SD (+1 SD) length of monsoon season, rainfall anomaly and extreme excess days are low (high) in most parts of the homogenous monsoon regions. Extreme excess days showed a significant association with rainy days, which indicates a high possibility of rainy days converting into extreme excess days. However, the increase in extreme excess days in the +1 SD length of monsoon season is limited to a great extent in JJAS and June only. Morlet wavelet power spectrum shows the delay (advance) of power in −1SD (+1 SD) length of monsoon season.
  • Md Masroor, Haroon Sajjad, Sufia Rehman, Roshani Singh, Md Hibjur Rahaman, Mehebub Sahana, Raihan Ahmed, Ram Avtar
    Geoscience Frontiers 13 (2) 101312 - 101312 1674-9871 2022/03
  • Tonni Agustiono Kurniawan, Xue Liang, Elizabeth O’Callaghan, Huihwang Goh, Mohd Hafiz Dzarfan Othman, Ram Avtar, Tutuk Djoko Kusworo
    Sustainability 14 (4) 2022/02/18 
    In China, environmental pollution due to municipal solid waste (MSW) over‐generation is one of the country’s priority concerns. The increasing volume and complexity of the waste poses serious risks to the environment and public health. Currently, the annual growth of MSW generation is estimated to be approximately 8–10% and will increase to 323 million metric tons (Mt) by 2030. Based on the secondary data collected from a literature survey, this article critically evaluates the recent progress of MSW management (MSWM) in China and offers new insights into the waste sector in the era of Industry 4.0. This helps decision makers in China to plan a smooth transition nationwide to a circular economy (CE) in the waste sector. It is evident that digitalization is a driving force for China to move towards low‐carbon development strategies within the framework of CE. Through digitalization, the waste sector has promoted prevention, reduction, reuse, and recycling (3Rs) of waste before waste disposal in landfills. A proper implementation of digitalization‐based waste recycling has contributed to an efficient cooperation between the government and private sector, increased job opportunities, and promoted the conservation of resources. It is anticipated that this work not only contributes to the establishment of an integrated MSWM system in China, but also improves local MSWM through digitalization in the framework of a CE.
  • K.S. Sajinkumar, A. Arya, A. Rajaneesh, T. Oommen, Ali P. Yunus, V.R. Rani, Ram Avtar, K.P. Thrivikramji
    Science of The Total Environment 807 150842 - 150842 0048-9697 2022/02
  • Tonni Agustiono Kurniawan, Mohd Hafiz Dzarfan Othman, Deepak Singh, Ram Avtar, Goh Hui Hwang, Tjandra Setiadi, Wai hung Lo
    Annals of Nuclear Energy 166 0306-4549 2022/02 
    Nuclear power is an ideal option for sustainable energy sources from U-235 fission. However, this energy generates long-term radioactive waste such as partially used nuclear fuel (PUNF) during electricity production. This work reviews various technologies to provide viable, sustainable, and long-term solutions for the PUNF storage. They include vitrification, partitioning and transmutation (P&T), pyro-processing, and deep geological repository (DGR). Their benefits and drawbacks are evaluated and compared based on previous studies. How to deal with the public perception of DGR and its impacts on the future of nuclear energy and the business opportunities of nuclear storage technology in the global market are discussed. A perspective of recycling nuclear waste into usable fuel is also elaborated. Our literature survey of 160 published articles (1981–2021) showed that DGR is the most ideal solution for long-term storage of the PUNF, as it provides an ultimate destination in a deep underground that permanently isolates the waste from inhabitants and the environment. Although storing PUNF in a DGR maybe convenient and economical in the short-term, the waste must be stored in a retrievable form so that it can be recycled as a fuel. In the long-term, a complete recycling of used nuclear fuel is the best option. As technological solutions and sound radioactive waste management policy are important for the safe storage of PUNF, stakeholders in the nuclear industry should portray long-term radioactive waste management through viable, feasible, and permanent solutions to waste storage for the sake of public safety and the environment.
  • Mahendra Sethi, Li-Jing Liu, Eva Ayaragarnchanakul, Aki Suwa, Ram Avtar, Akhilesh Surjan, Shilpi Mittal
    Atmosphere 13 (2) 247 - 247 2022/01/31 
    While climate change has global causations and impacts, there is growing consensus on addressing the 2 °C challenge through local actions. However, at the local level, there is disintegrated knowledge on the following: (a) short-, mid-and long-term climate vulnerability, (b) economy and GHG structures and their future pathways, and (c) useful mitigation and adaptation undertaken elsewhere. We evaluate these gaps through a comprehensive review of scientific literature and policy approaches of urban-climate studies in the Asia-Pacific Region. Based on the research findings, we develop a collaborative research framework of an integrated climate action planning (ICLAP) model for evidence-based decision-making tool. It adopts an innovative methodology integrating knowledge and data from diverse analytics, as follows: (a) spatial: downscaling global/regional climate scenarios to forecast local climate variability (50 km × 50 km) for 2030 (SDG target) and 2050; (b) statistical: a meta-analysis of 49 five-million-plus cities to forecast economic, energy and GHG scenarios; (c) bibliometric: a systematic review of global urban climate interventions from Google Scholar that collectively aid cities on policy inputs for mid-term climate variability, GHG profiles and available solutions at their disposal. We conclude with a discussion on scientific and policy relevance of such a tool in fostering overall urban, regional and global sustainability.
  • Md Masroor, Ram Avtar, Haroon Sajjad, Pandurang Choudhari, Luc Cimusa Kulimushi, Khaled Mohamed Khedher, Akinola Adesuji Komolafe, Ali P. Yunus, Netrananda Sahu
    Sustainability 14 (2) 2022/01/07 
    Examining the influence of land use/land cover transformation on meteorological variables has become imperative for maintaining long-term climate sustainability. Rapid growth and haphazard expansion have caused the conversion of prime agricultural land into a built-up area. This study used multitemporal Landsat data to analyze land use/land cover (LULC) changes, and Terra Climate monthly data to examine the impact of land transformation on precipitation, mini-mum and maximum temperature, wind speed, and soil moisture in the Aurangabad district of Maharashtra state in India during 1999–2019. Multiple linear regression and correlation analysis were performed to determine the association among LULC classes and climatic variables. This study re-vealed rapid urbanization in the study area over the years. The built-up area, water bodies, and barren lands have recorded a steep rise, while the agricultural area has decreased in the district. Drastic changes were observed in the climatic variables over the years. The precipitation and wind speed have shown decreasing trends during the study period. A positive relationship between soil moisture and agricultural land was found through a correlation analysis. Conspicuous findings about the positive relationship between the agricultural land and maximum temperature need further investigation. A multiple linear regression analysis demonstrated a negative relationship between the built-up area and precipitation. The intensity of the precipitation has reduced as a conse-quence of the developmental activities in the study area. Moreover, a positive relationship was observed between the built-up area and maximum temperature. Thus, this study calls for policy implications to formulate a futuristic land-use plan considering climate change projection in the dis-trict.
  • Vipul Chhabra, R. Uday Kiran, Juan Xiao, P. Krishna Reddy, Ram Avtar
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 13343 LNAI 470 - 481 0302-9743 2022 
    Given a coarse satellite image and a fine satellite image of a particular location taken at the same time, the high-resolution spatiotemporal image fusion technique involves understanding the spatial correlation between the pixels of both images and using it to generate a finer image for a given coarse (or test) image taken at a later time. This technique is extensively used for monitoring agricultural land cover, forest cover, etc. The two key issues in this technique are: (i) handling missing pixel data and (ii) improving the prediction accuracy of the fine image generated from the given test coarse image. This paper tackles these two issues by proposing an efficient method consisting of the following three basic steps: (i) imputation of missing pixels using neighborhood information, (ii) cross-scale matching to adjust both the Point Spread Functions Effect (PSF) and geo-registration errors between the course and high-resolution images, and (iii) error-based modulation, which uses pixel-based multiplicative factors and residuals to fix the error caused due to modulation of temporal changes. The experimental results on the real-world satellite imagery datasets demonstrate that the proposed model outperforms the state-of-art by accurately producing the high-resolution satellite images closer to the ground truth.
  • Mmasabata Dolly Molekoa, Pankaj Kumar, Bal Krishan Choudhary, Ali P. Yunus, Ali Kharrazi, Khaled Mohamed Khedher, Mohammad Al Shaib, Bhupendra P. Singh, Huynh Vuong Thu Minh, Tonni Agustiono Kurniawan, Ram Avtar
    Current Research in Environmental Sustainability 4 2022/01 
    The problem of water scarcity and clean water in sub-Saharan Africa is a growing concern. This study aims to quantify the water quality on a temporal scale in the Doorndraai dam site in sub-Saharan Africa to design possible management options. Here, an integrated approach using both in-situ measurements of water quality parameters and remote sensing data was used to derive the water quality index (WQI) and inherent optical properties of water to deduce the factors governing seasonal and annual variability. The results show that all the water quality parameters analyzed fall under the permissible limit of the World Health Organization (WHO) for drinking water, except turbidity. The average value of turbidity for the dry and wet periods was 12.52 and 3.39 NTU, respectively. WQI value ranges from good to excellent during the wet season, and poor in the dry season owing to the high values of turbidity in the water samples. Both in-situ and remote sensing-based analysis shows that during the last five years, the value of suspended particulate matter (SPM) based on Landsat-8 increased gradually in the study area. The Sentinel-2 derived modified normalized difference water index (MNDWI) shows a decreasing trend in the water area due to encroachment. The strong correlation between in-situ and remote sensing data supports the usefulness of remote sensing techniques for water resource management, especially in data-scarce regions. Looking at the spatio-temporal trend of water quality evolution, the findings of this study will help local decision-makers design sustainable plans for water resource management of Doorndraai dam.
  • Deha Agus Umarhadi, Ram Avtar, Pankaj Kumar, Ali P. Yunus, Tonni Agustiono Kurniawan, Ali Kharrazi, Mamoru Ishikawa, Wirastuti Widyatmanti
    Radar Remote Sensing: Applications and Challenges 341 - 356 2022/01/01 
    Degraded peatlands encounter irreversible subsidence owing to the loss of carbon from their organic soils. Interferometric synthetic aperture radar (InSAR) has proven to estimate a regional scale of peat subsidence efficiently compared with extensive field measurement, although a trade-off with accuracy is inevitable. We reviewed studies that used traditional and time-series InSAR techniques to map peat subsidence in the tropical region. Small baseline subset (SBAS) InSAR is thought to be important to be applied considering its ability to dampen decorrelation and handle data variance. A case study was conducted to apply SBAS InSAR using ALOS phased array L-band synthetic aperture radar data (2007–9) in the peat areas of Sintang Regency, Indonesia. Results showed that an area that was converted to plantations had higher subsidence than undisturbed peat swamp forests. Carbon loss was estimated to reach 0.354Mt carbon/year derived from the subsidence estimate.
  • Huynh Vuong Thu Minh, Van Pham Dang Tri, Ut Vu Ngoc, Ram Avtar, Pankaj Kumar, Dang T.T. Trinh, Au Van Hoa, Tran Van Ty, Nigel K. Downes
    Water 14 (3) 412 - 412 2022/01 
    This study utilized MIKE 11 to quantify the spatio-temporal dynamics of water quality parameters (Biochemical Oxygen Demand (BOD5), Dissolved Oxygen (DO) and temperature) in the Long Xuyen Quadrangle area of the Vietnamese Mekong Delta. Calibrated for the year of 2019 and validated for the year of 2020, the developed model showed a significant agreement between the observed and simulated values of water quality parameters. Locations near to cage culture areas exhibited higher BOD5 values than sites close to pond/lagoon culture areas due to the effects of numerous point sources of pollution, including upstream wastewater and out-fluxes from residential and tourism activities in the surrounding areas, all of which had a direct impact on the quality of the surface water used for aquaculture. Moreover, as aquacultural effluents have intensified and dispersed over time, water quality in the surrounding water bodies has degraded. The findings suggest that the effective planning, assessment and management of rapidly expanding aquaculture sites should be improved, including more rigorous water quality monitoring, to ensure the long-term sustainable expansion and development of the aquacultural sector in the Long Xuyen Quadrangle in particular, and the Vietnamese Mekong Delta as a whole.
  • Maria E. Mondejar, Ram Avtar, Heyker Lellani Baños Diaz, Rama Kant Dubey, Jesús Esteban, Abigail Gómez-Morales, Brett Hallam, Nsilulu Tresor Mbungu, Chukwuebuka Christopher Okolo, Kumar Arun Prasad, Qianhong She, Sergi Garcia-Segura
    Science of the Total Environment 794 0048-9697 2021/11/10 
    Digitalization provides access to an integrated network of unexploited big data with potential benefits for society and the environment. The development of smart systems connected to the internet of things can generate unique opportunities to strategically address challenges associated with the United Nations Sustainable Development Goals (SDGs) to ensure an equitable, environmentally sustainable, and healthy society. This perspective describes the opportunities that digitalization can provide towards building the sustainable society of the future. Smart technologies are envisioned as game-changing tools, whereby their integration will benefit the three essential elements of the food-water-energy nexus: (i) sustainable food production; (ii) access to clean and safe potable water; and (iii) green energy generation and usage. It then discusses the benefits of digitalization to catalyze the transition towards sustainable manufacturing practices and enhance citizens' health wellbeing by providing digital access to care, particularly for the underserved communities. Finally, the perspective englobes digitalization benefits by providing a holistic view on how it can contribute to address the serious challenges of endangered planet biodiversity and climate change.
  • Sk Mithun, Mehebub Sahana, Subrata Chattopadhyay, Brian Alan Johnson, Khaled Mohamed Khedher, Ram Avtar
    Remote Sensing 13 (21) 2021/11/03 
    The mass accumulation of population in the larger cities of India has led to accelerated and unprecedented peripheral urban expansion over the last few decades. This rapid peripheral growth is characterized by an uncontrolled, low density, fragmented and haphazard patchwork of development popularly known as urban sprawl. The Kolkata Metropolitan Area (KMA) has been one of the fastest-growing metropolitan areas in India and is experiencing rampant suburbanization and peripheral expansion. Hence, understanding urban growth and its dynamics in these rapidly changing environments is critical for city planners and resource managers. Furthermore, understanding urban expansion and urban growth patterns are essential for achieving inclusive and sustainable urbanization as defined by the United Nations in the Sustainable Development Goals (e.g., SDGs, 11.3). The present research attempts to quantify and model the urban growth dynamics of large and diverse metropolitan areas with a distinct methodology considering the case of KMA. In the study, land use and land cover (LULC) maps of KMA were prepared for three different years (i.e., for 1996, 2006, and 2016) through the classification of Landsat imagery using a support vector machine (SVM) classification approach. Then, change detection analysis, landscape metrics, a concentric zone approach, and Shannon’s entropy approach were applied for spatiotemporal assessment and quantification of urban growth in KMA. The achieved classification accuracies were found to be 89.75%, 92.00%, and 92.75%, with corresponding Kappa values of 0.879, 0.904, and 0.912 for 1996, 2006, and 2016, respectively. It is concluded that KMA has been experiencing typical urban sprawl. The peri-urban areas (i.e., KMA-rural) are growing rapidly, and are characterized by leapfrogging and fragmented built-up area development, compared to the central KMA (i.e., KMA-urban), which has become more compact in recent years.
  • Shreedevi Moharana, B.V.N.P. Kambhammettu, Syam Chintala, Arjangi Sandhya Rani, Ram Avtar
    Remote Sensing Applications: Society and Environment 24 100630 - 100630 2352-9385 2021/11
  • Chen Hao, Ali P. Yunus, Srikrishnan Siva Subramanian, Ram Avtar
    Journal of Environmental Management 297 0301-4797 2021/11/01 
    Recent years recorded an increasing number of short duration – high-intensity rainfall events in the Indian subcontinent consequent with urban and riverine flash floods. Rapid assessments of flooded areas are key for effective mitigation strategies and disaster risk plans, as well as to prepare operative policies for future events. Herein, we present an integrated methodology for rapidly mapping the flood extent, and depths based on Synthetic Aperture Radar (SAR) images and a digital elevation model (DEM). Incessant rain during August 2019 brought heavy riverine flooding in southern India, killed at least 280 people, and displaced about one million inhabitants from low-lying areas. We used SAR images by Sentinel-1 before, and during the flooding, and the MERIT DEM which enabled us to map the flood extent and flood depth of the inundation zones. Because the coverage of Sentinel-1 scene was limited to the Kabini river section during the flood period, flood extent and depth maps for the adjacent basin was generated by mapping the susceptibility for flooding using the training set obtained from the flood time Sentinel-1 images, and a set of predictive variables derived from DEM using random forest model. Qualitative analysis and cross-comparison with a numerical flood model proved the proposed approach is highly reliable with an accuracy value of 90% and 86% respectively for training and validation data, thus allowing a precise, simple, and fast flood mapping. The methodology presented here could be applied to other flooded areas having incomplete inventory in the context of flood risk assessment.
  • Brian A. Johnson, Ronald C. Estoque, Xuecao Li, Pankaj Kumar, Rajarshi Dasgupta, Ram Avtar, Damasa B. Magcale-Macandog
    Computers, Environment and Urban Systems 90 0198-9715 2021/11 
    Many developing countries in Asia are experiencing rapid urban expansion in climate hazard prone areas. To support climate resilient urban planning efforts, here we present an approach for simulating future urban land-use changes and evaluating potential flood exposure at a high spatial resolution (30 m) and national scale. As a case study, we applied this model to the Philippines – a country frequently affected by extreme rainfall events. Urban land-use changes were simulated to the year 2050 using a trend-based logistic regression cellular automata model, considering three different scenarios of urban expansion (assuming low/medium/high population growth). Flood exposure assessment was then conducted by overlaying the land-use simulation results onto a global floodplain map. We found that approximately 6040–13,850 ha of urban land conversion is likely to be located in flood prone regions between 2019 and 2050 (depending on the scenario), affecting approximately 2.5–5.8 million additional urban residents. In locations with high rates of future urban development in flood prone areas (Mindanao Island, in particular), climate resilient land-use plans should be developed/enforced, and flood mitigation infrastructure protected (in the case of “nature-based” infrastructure) or constructed. The data selected for our land-use change modeling and flood exposure assessment were all openly and (near-)globally available, with the intention that our methodology can potentially be applied in other countries where rapid urban expansion is occurring. The 2050 urban land-use maps generated in this study are available for download at https://www.iges.or.jp/en/pub/ph-urban2050/en to allow for their use in future works.
  • Tran Van Ty, Huynh Vuong Thu Minh, Ram Avtar, Pankaj Kumar, Huynh Van Hiep, Masaaki Kurasaki
    Groundwater for Sustainable Development 15 100680 - 100680 2021/11 
    This study assesses qualitative and quantitative changes in groundwater resources and their impact on land subsidence in Can Tho, Vietnam, from 2000 to 2018. Can Tho city is characterized by scarce water resources and intense industrial, domestic, agricultural, and mining usage, creating water stress. The vertical compaction rates and thus land subsidence, resulting from a head drawdown in three aquifers, were calculated using 1D consolidation of compressible porous media. Experiments were conducted in 16 wells clusters consisting of a total of 48 shallow and deep wells. The three wells from every 16 well clusters from different aquifers, namely the Middle-Upper Pleistocene confined aquifer (qp2-3), the Upper-Pleistocence (qp3), and a well in Holocene (qh), respectively, were examined. The Mann Kendal test with Sen's slope was performed and for most of the wells, negative values of Kendall's tau were found, which indicated decreasing trend of groundwater level. A significant change in groundwater level were also detected during the last eighteen years from 2000 to 2018. The results show significant downward trends of groundwater level for all of the wells of aquifer qp3 and qp2-3 except for a few shallow wells. The trend of this dropdown groundwater level for these deep wells is highly associated with extraction rates. The average subsidence rate of 4.28 cm yr−1 were observed in the study area. Tra Noc Industrial zones (QT8, QT16) showed a high subsidence rate which ranges from 5 to 7 cm yr−1. The calculated subsidence rates indicate the ongoing groundwater overexploitation, which might place Can Tho at risk of increased flooding and saltwater intrusion in the context of climate change and sea-level rise. The findings of this study call for effective policy strategies for sustainable water resource management to limit further land subsidence.
  • SOURABH SHRIVASTAVA, RAM AVTAR, PRASANTA KUMAR BAL
    International Journal of Big Data Mining for Global Warming 03 (02) 2021/10/12
  • Nguyen Hong Duc, Ram Avtar, Pankaj Kumar, Pham Phuong Lan
    Mitigation and Adaptation Strategies for Global Change 26 (7) 1381-2386 2021/10 
    Rapid population growth, urbanization, industrialization, and climate change are the key drivers causing serious water pollution around the globe. Considering the impacts of these key drivers, this study employed the Water Evaluation and Planning (WEAP) simulation tool to simulate the future water quality in a nearly 60-km stretch of the Hau River, Vietnam. The business-as-usual (BAU) scenario; scenarios with measures (WM), i.e., wastewater treatment plants (WWTPs) for treating 75% (WM75) and 100% (WM100) of total future wastewater generated; and the optimistic scenario (WM_Opt., i.e., WM100 + additional treatment plants for river water (RWTPs)) to achieve the desired water quality, were applied to simulate the future Hau River water quality for the year 2030. Result suggests that the average values of biochemical oxygen demand (BOD), total coliform (TC), nitrate (NO3−), and phosphate (PO43−) in the wet season of 2030 under BAU scenario will be increased by 16.01%, 40.85%, 30.49%, and 20.22%, respectively, in comparison to those of the current year, i.e., 2018. In the dry season, these rates will be increased by 27.80%, 65.94%, 31.05%, and 20.64%, respectively. Under the scenario with measures (WM75 and WM100), although the Hau River water quality was improved but did not reach the desired limits, especially for BOD and PO43− levels in the downstream region. However, under the WM_Opt. scenario, the average simulated values of both BOD and PO43− will be significantly declined by 76.53% and 63.96%, respectively as compared to the current situation and help to achieve river water quality under class A. This study is providing policy-relevant scientific information, vital for sustainable water resource management.
  • Deha Agus Umarhadi, Ram Avtar, Wirastuti Widyatmanti, Brian Alan Johnson, Ali P. Yunus, Khaled Mohamed Khedher, Gulab Singh
    Land Degradation & Development 32 (16) 4779 - 4794 1085-3278 2021/08/10 
    Peatlands in tropical regions like Indonesia are undergoing irreversible subsidence due to changes in land use (e.g., deforestation) and land management practices (e.g., drainage alteration), resulting in massive amounts of soil carbon loss. Several satellite-borne synthetic aperture radar (SAR) sensors are operating concurrently at different frequencies, providing potentially useful data for monitoring surface motion over tropical peatlands. This study focused on the capability of C-band (SENTINEL-1) and L-band (PALSAR-2) SAR data to monitor the surface changes in the tropical peatlands area of Bengkalis Island, Indonesia, by applying time-series interferometric SAR (InSAR) with the small baseline subset (SBAS) technique. The average vertical velocity measured by SENTINEL-1 and PALSAR-2 for the period of 2018–2019 was −1.41 and −2.65 cm yr−1, respectively. We also explored the potential of groundwater level (GWL) data converted to vertical displacement for validating SBAS InSAR. PALSAR-2 performed the best, exhibiting lower RMSE values for each land use compared to SENTINEL-1, with an overall RMSE of 1.383 and 1.988 cm yr−1, respectively. Also, the subsidence rates of SENTINEL-1 were underestimated, showing a significantly lower mean subsidence difference (0.96 cm yr−1) than the reference. Our GWL-based subsidence data offered an alternative validation method for InSAR-based subsidence estimation. Therefore, the integration of time-series InSAR and GWL data can provide crucial information for monitoring the degradation of tropical peatlands.
  • Sufia Rehman, Mohd Sayeed Ul Hasan, Abhishek Kumar Rai, Ram Avtar, Haroon Sajjad
    Arabian Journal of Geosciences 14 (15) 1866-7511 2021/08 
    Climate change–induced disasters and anthropogenic influences are making the ecological environment vulnerable. Thus, assessment of ecological vulnerability and risk is essential for devising suitable adaptation and management strategies. The paper makes a concerted effort to analyze flood-induced ecological vulnerability and risk using site-specific parameters in Bhagirathi sub-basin of India. Analytical hierarchy process (AHP) was used to assign weightage to the selected parameters. Association of parameters with vulnerability was examined through multiple regression analysis. Findings revealed that most of the area in eastern, central, and deltaic sub-basin was found under high vulnerability and risk. Disturbance index, rainfall, temperature, SAVI, vegetation type, low biological richness, slope, and NDVI identified the potent factors for high vulnerability to flood, while high inundation was the prime determinant for very high flood risk in the study area. Evaluated findings may be helpful in prioritizing the areas for ecological restoration and conservation.
  • Himangana Gupta, Lakhvinder Kaur, Mahbooba Asra, Ram Avtar, C. Sudhakar Reddy
    Agriculture 11 (8) 724 - 724 2021/07/30 
    Apple cultivation in the Kinnaur district of the northern Indian State of Himachal Pradesh faces challenges from climatic changes and developmental activities. Farmers in the neighboring districts have already faced a major loss of livelihood due to seasonal changes. Therefore, it is important to study the extent of seasonal variations in the apple growing locations of this region. This study makes that attempt by assessing seasonality variations during a 15-year period from 2004 to 2018 when maximum construction activities occurred in this region. The study uses geospatial and statistical techniques in addition to farmer perceptions obtained during a field visit in November 2019. A temporal pattern using a normalized difference vegetation index (NDVI) based on Moderate Resolution Imaging Spectroradiometer (MODIS) was studied for seven apple-growing locations in the district. The results show high seasonal variations and reduced snowfall at lower elevations, resulting in less chilling hours, which are necessary for the healthy growth of apples. The normalized difference snow index (NDSI) and rainfall show a high correlation with apple growth. Local farmers are unprepared for future seasonal disturbances, as they lack early warning systems, insurance for apple crops, and alternative livelihood options.
  • Sufia Rehman, Mohd Sayeed Ul Hasan, Abhishek Kumar Rai, Ram Avtar, Haroon Sajjad
    Arabian Journal of Geosciences 14 (15) 1866-7511 2021/07/27
  • Md. Mustafizur Rahman, Ram Avtar, Sohail Ahmad, Luis Inostroza, Prakhar Misra, Pankaj Kumar, Wataru Takeuchi, Akhilesh Surjan, Osamu Saito
    Sustainability Science 16 (4) 1323 - 1340 1862-4065 2021/07/02 
    Zoning is an important tool to regulate the use of land and to characterize built form over land, and thus to facilitate urban sustainability. Availability of reliable data is crucial for monitoring land use zoning, which contributes directly to the success of the Sustainable Development Goals (SDGs) in general, and SDG Goal 11 for sustainable cities and communities in particular. However, obtaining this valuable information using traditional survey methods is both costly and time-consuming. Remote sensing technology overcomes these challenges and supports urban policymaking and planning processes. This study unveils a novel approach to developing a cost-effective method for identifying building types using Sentinel-2A, Visible Infrared Imaging Radiometer Suite (VIIRS)–based nighttime light (NTL) data, and TanDEM-X–based Digital Surface Model (DSM) data. A newly developed index for this study, the Normalized Difference Steel Structure Index (NDSSI), is useful for rapidly mapping industrial buildings with steel structures. The implementation status of Dhaka’s existing land use plan was evaluated by analyzing the spatial distribution of different types of building uses. This study classifies residential, commercial, and industrial buildings within Dhaka using building height, and nighttime light emission. The experimental results reveal that about 67% of commercial and 51% of industrial buildings within the Dhaka Metropolitan Area (DMA) do not comply with the land use zoning by the Detailed Area Plan (DAP). It also reveals that approximately 10% of commercial buildings, 9% of industrial buildings, and 6% of residential buildings have encroached upon conservation zones (such as open space, flood-prone zones, water bodies, and proposed areas for future road extension). A major constraint in the study was the low spatial resolution of the nighttime light dataset, which made it difficult to distinguish individual sources of light. Still, the methodological approaches proposed in this study are expected to promote reduced costs and efficacious decision-making in urban transformation and to help achieve SDG 11, especially in developing countries.
  • Tonni Agustiono Kurniawan, Deepak Singh, Ram Avtar, Mohd Hafiz Dzarfan Othman, Goh Hui Hwang, Ahmad B. Albadarin, Mashallah Rezakazemi, Tjandra Setiadi, Saeed Shirazian
    Chemosphere 274 0045-6535 2021/07 
    This work investigates the performances of coconut shell waste-based activated carbon (CSWAC) adsorption in batch studies for removal of ammoniacal nitrogen (NH3–N) and refractory pollutants (as indicated by decreasing COD concentration) from landfill leachate. To valorize unused resources, coconut shell, recovered and recycled from agricultural waste, was converted into activated carbon, which can be used for leachate treatment. The ozonation of the CSWAC was conducted to enhance its removal performance for target pollutants. The adsorption mechanisms of refractory pollutants by the adsorbent are proposed. Perspectives on nutrient recovery technologies from landfill leachate from the view-points of downstream processing are presented. Their removal efficiencies for both recalcitrant compounds and ammoniacal nitrogen were compared to those of other techniques reported in previous work. It is found that the ozonated CSWAC substantially removed COD (i.e. 76%) as well as NH3–N (i.e. 75%), as compared to the CSWAC without pretreatment (i.e. COD: 44%; NH3–N: 51%) with NH3–N and COD concentrations of 2750 and 8500 mg/L, respectively. This reveals the need of ozonation for the adsorbent to improve its performance for the removal of COD and NH3–N at optimized reactions: 30 g/L of CSWAC, pH 8, 200 rpm of shaking speed and 20 min of reaction time. Nevertheless, treatment of the leachate samples using the ozonated CSWAC alone was still unable to result in treated effluents that could meet the COD and NH3–N discharge standards below 200 and 5 mg/L, respectively, set by legislative requirements. This reveals that another treatment is necessary to be undertaken to comply with the requirement of their effluent limit.
  • Pankaj Kumar, Rajarshi Dasgupta, Shalini Dhyani, Rakesh Kadaverugu, Brian Alan Johnson, Shizuka Hashimoto, Netrananda Sahu, Ram Avtar, Osamu Saito, Shamik Chakraborty, Binaya Kumar Mishra
    Sustainability 13 (11) 6339 - 6339 2021/06/03 
    Widespread urban expansion around the world, combined with rapid demographic and climatic changes, has resulted in serious pollution issues in many coastal water bodies. To help formulate coastal management strategies to mitigate the impacts of these extreme changes (e.g., local land-use or climate change adaptation policies), research methodologies that incorporate participatory approaches alongside with computer simulation modeling tools have potential to be particularly effective. One such research methodology, called the “Participatory Coastal Land-Use Management” (PCLM) approach, consists of three major steps: (a) participatory approach to find key drivers responsible for the water quality deterioration, (b) scenario analysis using different computer simulation modeling tools for impact assessment, and (c) using these scientific evidences for developing adaptation and mitigation measures. In this study, we have applied PCLM approach in the Kendrapara district of India (focusing on the Brahmani River basin), a rapidly urbanizing area on the country’s east coast to evaluate current status and predict its future conditions. The participatory approach involved key informant interviews to determine key drivers of water quality degradation, which served as an input for scenario analysis and hydrological simulation in the next step. Future river water quality (BOD and Total coliform (Tot. coli) as important parameters) was simulated using the Water Evaluation and Planning (WEAP) tool, considering a different plausible future scenario (to 2050) incorporating diverse drivers and pressures (i.e., population growth, landuse change, and climate change). Water samples (collected in 2018) indicated that the Brahmani River in this district was already moderately-to-extremely polluted in comparison to the desirable water quality (Class B), and modeling results indicated that the river water quality is likely to further deteriorate by 2050 under all of the considered scenarios. Demographic changes emerged as the major driver affecting the future water quality deterioration (68% and 69% for BOD and Tot. coli respectively), whereas climate change had the lowest impact on river water quality (12% and 13% for BOD and Tot. coli respectively), although the impact was not negligible. Scientific evidence to understand the impacts of future changes can help in developing diverse plausible coastal zone management approaches for ensuring sustainable management of water resources in the region. The PCLM approach, by having active stakeholder involvement, can help in co-generation of the coastal management options followed by open access free software, and models can play a relevant cost-effective approach to enhance science-policy interface for conservation of natural resources.
  • Tonni Agustiono Kurniawan, Deepak Singh, Wenchao Xue, Ram Avtar, Mohd Hafiz Dzarfan Othman, Goh Hui Hwang, Tjandra Setiadi, Ahmad B. Albadarin, Saeed Shirazian
    Journal of Environmental Management 287 112265 - 112265 0301-4797 2021/06/01 
    This study investigated the feasibility of integrated ammonium stripping and/or coconut shell waste-based activated carbon (CSWAC) adsorption in treating leachate samples. To valorize unused biomass for water treatment application, the adsorbent originated from coconut shell waste. To enhance its performance for target pollutants, the adsorbent was pretreated with ozone and NaOH. The effects of pH, temperature, and airflow rate on the removal of ammoniacal nitrogen (NH3–N) and refractory pollutants were studied during stripping alone. The removal performances of refractory compounds in this study were compared to those of other treatments previously reported. To contribute new knowledge to the field of study, perspectives on nutrients removal and recovery like phosphorus and nitrogen are presented. It was found that the ammonium stripping and adsorption treatment using the ozonated CSWAC attained an almost complete removal (99%) of NH3–N and 90% of COD with initial NH3–N and COD concentrations of 2500 mg/L and 20,000 mg/L, respectively, at optimized conditions. With the COD of treated effluents higher than 200 mg/L, the combined treatments were not satisfactory enough to remove target refractory compounds. Therefore, further biological processes are required to complete their biodegradation to meet the effluent limit set by environmental legislation. As this work has contributed to resource recovery as the driving force of landfill management, it is important to note the investment and operational expenses, engineering applicability of the technologies, and their environmental concerns and benefits. If properly managed, nutrient recovery from waste streams offers environmental and socio-economic benefits that would improve public health and create jobs for the local community.
  • Juan Xiao, Teiji Watanabe, Xi Lu, Mohan Bahadur Chand, Deha Agus Umarhadi, Xinyu Chen, Ram Avtar
    Physics and Chemistry of the Earth, Parts A/B/C 126 103041 - 103041 1474-7065 2021/06 
    The boundaries of the East Dongting Lake National Nature Reserve's (EDLNNR) functional zones have been adjusted over time due to conditional changes. However, there is no systematic study being conducted on the EDLNNR's historical trend of land use/land cover (LULC). Therefore, it is crucial to understand the relationship between changes in functional zones' boundary and spatio-temporal changes in the LULC from pre-establishment to the present time for adequate protection. The objective of this study is to understand the spatio-temporal dynamics of LULC changes from 1979 to 2019 in the three functional zones of EDLNNR during the dry season. LULC transition matrix and landscape metrics at the landscape level were also used to investigate the land type dynamics and landscape fragmentation, respectively. An increase in the marsh area was observed in all three functional zones of EDLNNR. The built-up area was increased due to the conversion of agricultural land. The landscape metrics-based analysis showed that the EDLNNR was less fragmented in 2019 than the previous record in 2016, due to the adjustment action of the three functional zones' boundary of the EDLNNR in 2018. The excluded area of the EDLNNR was from its experimental zone, which includes densely populated areas and surrounding agricultural land and woodland. The spatio-temporal LULC change information can offer effective management and conservation of different functional zones of the EDLNNR. This study can also act as a case model for effective management of other protected areas worldwide.
  • Tonni Agustiono Kurniawan, Waihung Lo, Deepak Singh, Mohd Hafiz Dzarfan Othman, Ram Avtar, Goh Hui Hwang, Ahmad B. Albadarin, Axel Olaf Kern, Saeed Shirazian
    Environmental Pollution 277 0269-7491 2021/05/15 
    Recently Xiamen (China) has encountered various challenges of municipal solid waste management (MSWM) such as lack of a complete garbage sorting and recycling system, the absence of waste segregation between organic and dry waste at source, and a shortage of complete and clear information about the MSW generated. This article critically analyzes the existing bottlenecks in its waste management system and discusses the way forward for the city to enhance its MSWM by drawing lessons from Hong Kong's effectiveness in dealing with the same problems over the past decades. Solutions to the MSWM problem are not only limited to technological options, but also integrate environmental, legal, and institutional perspectives. The solutions include (1) enhancing source separation and improving recycling system; (2) improving the legislation system of the MSWM; (3) improvement of terminal disposal facilities in the city; (4) incorporating digitization into MSWM; and (5) establishing standards and definitions for recycled products and/or recyclable materials. We also evaluate and compare different aspects of MSWM in Xiamen and Hong Kong SAR (special administrative region) under the framework of ‘One Country, Two Systems’ concerning environmental policies, generation, composition, characteristics, treatment, and disposal of their MSW. The nexus of society, economics of the MSW, and the environment in the sustainability sphere are established by promoting local recycling industries and the standardization of recycled products and/or recyclable materials. The roles of digitization technologies in the 4th Industrial Revolution for waste reduction in the framework of circular economy (CE) are also elaborated. This technological solution may improve the city's MSWM in terms of public participation in MSW separation through reduction, recycle, reuse, recovery, and repair (5Rs) schemes. To meet top-down policy goals such as a 35% recycling rate for the generated waste by 2030, incorporating digitization into the MSWM provides the city with technology-driven waste solutions.
  • Dun Fu, Tonni Agustiono Kurniawan, Lan Lin, Yaqiong Li, Ram Avtar, Mohd Hafiz Dzarfan Othman, Feng Li
    Journal of Environmental Management 286 0301-4797 2021/05/15 
    This study tested the technical feasibility of pyrite and/or persulfate oxidation system for arsenic (As) removal from aqueous solutions. The effects of persulfate on As removal by the pyrite in the integrated treatment were also investigated. Prior to the persulfate addition into the reaction system, the physico-chemical interactions between As and the pyrite alone in aqueous solutions were explored in batch studies. The adsorption mechanisms of As by the adsorbent were also presented. At the same As concentration of 5 mg/L, it was found that As(III) attained a longer equilibrium time (8 h) than As(V) (2 h), while the pyrite worked effectively at pH ranging from 6 to 11. At optimum conditions (0.25 g/L of pyrite, pH 8.0 and 5 mg/L of As(III) concentration), the addition of persulfate (0.5 mM) into the reaction promoted a complete removal of arsenic from the solutions. Consequently, this enabled the treated effluents to meet the arsenic maximum contaminant limit (MCL) of <10 μg/L according to the World Health Organization (WHO)'s requirements. The redox mechanisms, which involved electron transfer from the S22− of the pyrite to Fe3+, supply Fe2+ for persulfate decomposition, oxidizing As(III) to As(V). The sulfur species played roles in the redox cycle of the Fe3+/Fe2+ of the pyrite by giving its electrons, while the As(III) oxidation to As(V) was attributed to the pyrite. Overall, this work reveals the applicability of the pyrite as an adsorbent for water treatment and the importance of persulfate addition to promote a complete As removal from aqueous solutions.
  • Sushila Paudel, Pankaj Kumar, Rajarshi Dasgupta, Brian Alan Johnson, Ram Avtar, Rajib Shaw, Binaya Kumar Mishra, Sakiko Kanbara
    Water 13 (10) 1365 - 1365 2021/05/14 
    Water scarcity, together with the projected impacts of water stress worldwide, has led to a rapid increase in research on measuring water security. However, water security has been conceptualized under different perspectives, including various aspects and dimensions. Since public health is also an integral part of water security, it is necessary to understand how health has been incorporated as a dimension in the existing water security frameworks. While supply–demand and governance narratives dominated several popular water security frameworks, studies that are specifically designed for public health purposes are generally lacking. This research aims to address this gap, firstly by assessing the multiple thematic dimensions of water security frameworks in scientific disclosure; and secondly by looking into the public health dimensions and evaluating their importance and integration in the existing water security frameworks. For this, a systematic review of the Scopus database was undertaken using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A detailed review analysis of 77 relevant papers was performed. The result shows that 11 distinct dimensions have been used to design the existing water security framework. Although public health aspects were mentioned in 51% of the papers, direct health impacts were considered only by 18%, and indirect health impacts or mediators were considered by 33% of the papers. Among direct health impacts, diarrhea is the most prevalent one considered for developing a water security framework. Among different indirect or mediating factors, poor accessibility and availability of water resources in terms of time and distance is a big determinant for causing mental illnesses, such as stress or anxiety, which are being considered when framing water security framework, particularly in developing nations. Water quantity is more of a common issue for both developed and developing countries, water quality and mismanagement of water supply-related infrastructure is the main concern for developing nations, which proved to be the biggest hurdle for achieving water security. It is also necessary to consider how people treat and consume the water available to them. The result of this study sheds light on existing gaps for different water security frameworks and provides policy-relevant guidelines for its betterment. Also, it stressed that a more wide and holistic approach must be considered when framing a water security framework to result in sustainable water management and human well-being.
  • Andi Besse Rimba, Geetha Mohan, Saroj Kumar Chapagain, Andi Arumansawang, Carolyn Payus, Kensuke Fukushi, Husnayaen, Takahiro Osawa, Ram Avtar
    Environmental Science and Pollution Research 28 (20) 25920 - 25938 0944-1344 2021/05 
    This paper aims to assess the influence of land use and land cover (LULC) indicators and population density on water quality parameters during dry and rainy seasons in a tourism area in Indonesia. This study applies least squares regression (OLS) and Pearson correlation analysis to see the relationship among factors, and all LULC and population density were significantly correlated with most of water quality parameter with P values of 0.01 and 0.05. For example, DO shows high correlation with population density, farm, and built-up in dry season; however, each observation point has different percentages of LULC and population density. The concentration value should be different over space since watershed characteristics and pollutions sources are not the same in the diverse locations. The geographically weighted regression (GWR) analyze the spatially varying relationships among population density, LULC categories (i.e., built-up areas, rice fields, farms, and forests), and 11 water quality indicators across three selected rivers (Ayung, Badung, and Mati) with different levels of tourism urbanization in Bali Province, Indonesia. The results explore that compared with OLS estimates, GWR performed well in terms of their R2 values and the Akaike information criterion (AIC) in all the parameters and seasons. Further, the findings exhibit population density as a critical indicator having a highly significant association with BOD and E. Coli parameters. Moreover, the built-up area has correlated positively to the water quality parameters (Ni, Pb, KMnO4 and TSS). The parameter DO is associated negatively with the built-up area, which indicates increasing built-up area tends to deteriorate the water quality. Hence, our findings can be used as input to provide a reference to the local governments and stakeholders for issuing policy on water and LULC for achieving a sustainable water environment in this region.
  • Dun Fu, Tonni Agustiono Kurniawan, Ram Avtar, Pan Xu, Mohd Hafiz Dzarfan Othman
    Chemosphere 271 0045-6535 2021/05 
    This work incorporated technological values into Zn2Cr-layered double hydroxide (LDH), synthesized from unused resources, for removal of pyrophosphate (PP) in electroplating wastewater. To adopt a resource recovery for the remediation of the aquatic environment, the Zn2Cr-LDH was fabricated by co-precipitation from concentrated metals of plating waste that remained as industrial by-products from metal finishing processes. To examine its applicability for water treatment, batch experiments were conducted at optimum M2+/M3+, pH, reaction time, and temperature. To understand the adsorption mechanisms of the PP by the adsorbent, the Zn2Cr-LDH was characterized using Brunauer-Emmett-Teller (BET), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDS), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) analyses before and after adsorption treatment. An almost complete PP removal was attained by the Zn2Cr-LDH at optimized conditions: 50 mg/L of PP, 1 g/L of adsorbent, pH 6, and 6 h of reaction. Ion exchange controlled the PP removal by the adsorbent at acidic conditions. The PP removal well fitted a pseudo-second-order kinetics and/or the Langmuir isotherm model with 79 mg/g of PP adsorption capacity. The spent Zn2Cr-LDH was regenerated with NaOH with 86% of efficiency for the first cycle. The treated effluents could comply with the discharge limit of <1 mg/L. Overall, the use of the Zn2Cr-LDH as a low-cost adsorbent for wastewater treatment has contributed to national policy that promotes a zero-waste approach for a circular economy (CE) through a resource recovery paradigm.
  • Hala I. Al-Daghistani, Balsam Talal Mohammad, Tonni Agustiono Kurniawan, Deepak Singh, Alexander D. Rabadi, Wenchao Xue, Ram Avtar, Mohd Hafiz Dzarfan Othman, Saeed Shirazian
    Process Biochemistry 104 171 - 181 1359-5113 2021/05 
    We identified and investigated the biological activities of Thermomonas hydrothermalis, isolated bacteria strains present in Jordan's hot springs, based on their morphological, biochemical, and physiological characteristics. The colonies exhibited light brown with a diameter ranging from 0.5 to 2.0 mm. For screening their metabolic activities, API 50CHB strips and esculin were used. We phylogenetically typified the isolated bacteria by applying 16S ribosomal DNA gene amplification and sequencing followed by the Basic Local Alignment Search Tool (BLAST) tests. About 100 μL of the enriched sample was streaked on nutrient agar using a calibrated wire loop, while 20 μg crude powder was mixed with dimethyl sulfoxide (DMSO) to test their activities against standard pathogenic bacterial strains (ATCC). The water samples collected from the hot springs had temperatures ranging between 44–56 °C, pH between 7.11–8.51, and electrical conductivity between 1.06–1.41 ms/cm. To utilize their isolate for characterization and applications, pH, temperature, and generation time were optimized. It was found that the Gram-negative isolated bacteria strain exhibited an optimum growth at 55 °C, pH 8.5, and 30 min of generation time (GT). The BLAST results showed a 99 % of similar identity of the sample to Thermomonas hydrothermalis. Due to their antibacterial effects against Gram-positive and Gram-negative bacteria, bioactive compounds identified using gas chromatography–mass spectroscopy (GC–MS) had novel features such as 4(3 H)-pyrimidinone, dihydroxy-1,5- naphthyridine, actinomycine-D, and pyrrolo [1,2-a]pyrazine-1,4-dione hygrazides. Screening of cytotoxic activity tests using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay was conducted toward their water extract, which exerted cytostimulatory effects on human lung fibroblasts (MRC-5) with an IC50 of 5.109 μg/mL and accelerated wound closure. Overall, the implications of this study provided new insights into the bioproducts of Thermomonas hydrothermalis and offered opportunities to utilize their isolate for biotechnological and medicinal applications.
  • Chander Kumar Singh, Anand Kumar, Satyanarayan Shashtri, Alok Kumar, Javed Mallick, Amit Singh, Ram Avtar, Ravi Prakash Singh, Pankaj Kumar, Shyam Ranjan
    Groundwater for Sustainable Development 13 100569 - 100569 2021/05 
    Lower rainfall coupled with higher evapotranspiration leads to enhanced salinity and inorganic contamination of groundwater in arid and semi-arid regions. In this study, 100 groundwater samples were collected from a part of the Thar Desert of India and analysed for various physico-chemical water quality parameters for quality assurance for potable water supply. The electrical conductivity of the samples showed an ion-enriched aquifer environment with high alkalinity. The concentration of Na+, SO42−, Cl−, NO3− and F− ions in most of the samples were above the World Health Organization (WHO) guidelines for drinking water, posing a major public health concern. Saturation indices (SI) indicates that the dissolution of calcite bearing minerals and ion-exchange were major processes controlling the groundwater chemistry in the region. Most of the samples are oversaturated with aragonite, calcite, chalcedony, and dolomite while undersaturated with anhydrite, gypsum, halite. The results suggest that weathering of aquifer minerals and salinization due to high evaporation controls the quality and origin of major ions. The Na–Cl and Na–HCO3 water facies indicates the influence of evaporation and thus conducive condition for F− enrichment in groundwater while NO3− is mostly due to anthropogenic activities. The health index (HI) for risk assessment suggests both F− and NO3− contribute to the health risk of the residing population as the HI values were found to be > 1 in 97% and 93% for children and adults, respectively. The treatment technologies should be adopted to remove the multiple contaminants present in the groundwater of this region.
  • Zhu Mengting, Tonni Agustiono Kurniawan, Ram Avtar, Mohd Hafiz Dzarfan Othman, Tong Ouyang, Huang Yujia, Zhang Xueting, Tjandra Setiadi, Iswanto Iswanto
    Journal of Hazardous Materials 405 0304-3894 2021/03/05 
    We test the feasibility of TiO2(B)@carbon composites as adsorbents, derived from wheat straws, for tetracycline (TC) adsorption from aqueous solutions. Hydrochar (HC), biochar (BC), and hydrochar-derived pyrolysis char (HDPC) are synthesized hydrothermally from the waste and then functionalized with TiO2(B), named as ‘Composite-1′, ‘Composite-2′, and ‘Composite-3′, respectively. A higher loading of TiO2(B) into the HC was also synthesized for comparison, named as ‘Composite-4′. To compare their physico-chemical changes before and after surface modification, the composites are characterized using FESEM-EDS, XRD, BET, FRTEM, and FTIR. The effects of H2O2 addition on TC removal are investigated. Adsorption kinetics and isotherms of TC removal are studied, while TC adsorption mechanisms are elaborated. We found that the Composite-4 has the highest TC removal (93%) at pH 7, 1 g/L of dose, and 4 h of reaction time at 50 mg/L of TC after adding H2O2 (10 mM). The TC adsorption capacities of the Composite-1 and Composite-4 are 40.65 and 49.26 mg/g, respectively. The TC removal by the Composite-1 follows the pseudo-second order. Overall, this suggests that converting the wheat straw into HC and then functionalizing its surface with TiO2(B) as a composite has added values to the waste as an adsorbent for wastewater treatment.
  • Swee Keong Yeap, Norlaily Mohd Ali, Muhammad Nadeem Akhtar, Nursyamirah Abd Razak, Zhi Xiong Chong, Wan Yong Ho, Lily Boo, Seema Zareen, Tonni Agustiono Kurniawan, Ram Avtar, Stephanie Y. L. Ng, Alan Han Kiat Ong, Noorjahan Banu Alitheen
    Molecules 26 (5) 1277 - 1277 2021/02/26 
    2E,6E)-2,6-bis-(4-hydroxy-3-methoxybenzylidene)-cyclohexanone (BHMC) is a synthetic curcumin analogue, which has been reported to possess anti-tumor, anti-metastatic, and anti-invasion properties on estrogen receptor (ER) negative breast cancer cells in vitro and in vivo. However, the cytotoxic effects of BHMC on ER positive breast cancer cells were not widely reported. This study was aimed to investigate the cytotoxic potential of BHMC on MCF-7 cells using cell viability, cell cycle, and apoptotic assays. Besides, microarray and quantitative polymerase chain reaction (qPCR) were performed to identify the list of miRNAs and genes, which could be dysregulated following BHMC treatment. The current study discovered that BHMC exhibits selective cytotoxic effects on ER positive MCF-7 cells as compared to ER negative MDA-MB-231 cells and normal breast cells, MCF-10A. BHMC was shown to promote G2/M cell cycle arrest and apoptosis in MCF-7 cells. Microarray and qPCR analysis demonstrated that BHMC treatment would upregulate several miRNAs like miR-3195 and miR-30a-3p and downregulate miRNAs such as miR-6813-5p and miR-6132 in MCF-7 cells. Besides, BHMC administration was also found to downregulate few tumor-promoting genes like VEGF and SNAIL in MCF-7. In conclusion, BHMC induced apoptosis in the MCF-7 cells by altering the expressions of apoptotic-regulating miRNAs and associated genes.
  • Tonni Agustiono Kurniawan, Ram Avtar, Deepak Singh, Wenchao Xue, Mohd Hafiz Dzarfan Othman, Goh Hui Hwang, Iswanto Iswanto, Ahmad B. Albadarin, Axel Olaf Kern
    Journal of Cleaner Production 284 0959-6526 2021/02/15 
    Over the past years, Indonesia, the world's fourth most populous country, has confronted environmental problems due to uncontrolled generation of municipal solid waste (MSW). While the integrated solid waste management (ISWM) represents a critical strategy for Indonesia to control its production, it is also recognized that economic approaches also need to be promoted to address the waste problem concertedly. In this case study, empirical approaches are developed to understand how a volume-based waste fee could be incorporated into MSW collection services and how to apply a zero-waste approach in Indonesia by adapting resource recovery initiatives, adapted from Germany's mature experiences in integrating the CE paradigm into the latter's MSWM practices. Currently, Sukunan village (Yogyakarta, Indonesia) promotes waste reduction at sources in the framework of community-based solid waste management (CBSWM) by mobilizing the local community for waste separation (organic and non-organic) and waste recycling. As a result, about 0.2 million Mt of CO2-eq emissions was avoided annually from local landfills. The economic benefits of recycling activities by the village's community also resulted in 30% reduction of the waste generated. This CBSWM scheme not only saves the government budget on waste collection, transport and disposal, but also extends the lifetime of local landfills as the final disposal sites. By integrating the CE paradigm into its MSWM practices through the implementation of economic instruments and adherence to the rule of law in the same way as Germany does, Indonesia could make positive changes to its environmental policy and regulation of MSW. A sound MSWM in Indonesia could play important roles in promoting the effectiveness of urban development with resource recovery approaches to facilitate its transition towards a CE nationwide in the long-term.
  • Leonid N. Vladimirov, Grigory N. Machakhtyrov, Varvara A. Machakhtyrova, Albertus S. Louw, Netrananda Sahu, Ali P. Yunus, Ram Avtar
    Atmosphere 12 (2) 233 - 233 2021/02/08 
    Climate change is affecting human health worldwide. In particular, changes to local and global climate parameters influence vector and water-borne diseases like malaria, dengue fever, and tick-borne encephalitis. The Republic of Sakha in northern Russia is no exception. Long-term trends of increasing annual temperatures and thawing permafrost have corresponded with the northward range expansion of tick-species in the Republic. Indigenous communities living in these remote areas may be severely affected by human and livestock diseases introduced by disease vectors like ticks. To better understand the risk of vector-borne diseases in Sakha, we aimed to describe the increase and spatial spread of tick-bite cases in the Republic. Between 2000 and 2018, the frequency of tick bite cases increased 40-fold. At the start of the period, only isolated cases were reported in southern districts, but by 2018, tick bites had been reported in 21 districts in the Republic. This trend coincides with a noticeable increase in the average annual temperature in the region since the 2000s by an average of 1 °C. Maps illustrate the northward spread of tick-bite cases. A negative binomial regression model was used to correlate the increase in cases with a number of climate parameters. Tick bite case frequency per district was significantly explained by average annual temperature, average temperature in the coldest month of the year, the observation year, as well as Selyaninov’s hydrothermal coefficient. These findings contribute to the growing literature that describe the relationship between tick abundance and spread in Northern Latitudes and changes in temperatures and moisture. Future studies might use these and similar results to map and identify areas at risk of infestation by ticks, as climates continue to change in Sakha.
  • Ram Avtar, Asma Kouser, Ashwani Kumar, Deepak Singh, Prakhar Misra, Ankita Gupta, Ali P. Yunus, Pankaj Kumar, Brian Alan Johnson, Rajarshi Dasgupta, Netrananda Sahu, Andi Besse Rimba
    Remote Sensing 13 (3) 439 - 439 2021/01/27 
    Remote sensing technology has seen a massive rise in popularity over the last two decades, becoming an integral part of our lives. Space-based satellite technologies facilitated access to the inaccessible terrains, helped humanitarian teams, support complex emergencies, and contributed to monitoring and verifying conflict zones. The scoping phase of this review investigated the utility of the role of remote sensing application to complement international peace and security activities owing to their ability to provide objective near real-time insights at the ground level. The first part of this review looks into the major research concepts and implementation of remote sensing-based techniques for international peace and security applications and presented a meta-analysis on how advanced sensor capabilities can support various aspects of peace and security. With key examples, we demonstrated how this technology assemblage enacts multiple versions of peace and security: for refugee relief operations, in armed conflicts monitoring, tracking acts of genocide, providing evidence in courts of law, and assessing contravention in human rights. The second part of this review anticipates future challenges that can hinder the applicative capabilities of remote sensing in peace and security. Varying types of sensors pose discrepancies in image classifications and issues like cost, resolution, and difficulty of ground-truth in conflict areas. With emerging technologies and sufficient secondary resources available, remote sensing plays a vital operational tool in conflict-affected areas by supporting an extensive diversity in public policy actions for peacekeeping processes.
  • Mmasabata Molekoa, Ram Avtar, Pankaj Kumar, Huynh Thu Minh, Rajarshi Dasgupta, Brian Johnson, Netrananda Sahu, Ram Verma, Ali Yunus
    Water 13 (2) 220 - 220 2021/01/18 
    Considering the well-documented impacts of land-use change on water resources and the rapid land-use conversions occurring throughout Africa, in this study, we conducted a spatiotemporal analysis of surface water quality and its relation with the land use and land cover (LULC) pattern in Mokopane, Limpopo province of South Africa. Various physico-chemical parameters were analyzed for surface water samples collected from five sampling locations from 2016 to 2020. Time-series analysis of key surface water quality parameters was performed to identify the essential hydrological processes governing water quality. The analyzed water quality data were also used to calculate the heavy metal pollution index (HPI), heavy metal evaluation index (HEI) and weighted water quality index (WQI). Also, the spatial trend of water quality is compared with LULC changes from 2015 to 2020. Results revealed that the concentration of most of the physico-chemical parameters in the water samples was beyond the World Health Organization (WHO) adopted permissible limit, except for a few parameters in some locations. Based on the calculated values of HPI and HEI, water quality samples were categorized as low to moderately polluted water bodies, whereas all water samples fell under the poor category (>100) and beyond based on the calculated WQI. Looking precisely at the water quality’s temporal trend, it is found that most of the sampling shows a deteriorating trend from 2016 to 2019. However, the year 2020 shows a slightly improving trend on water quality, which can be justified by lowering human activities during the lockdown period imposed by COVID-19. Land use has a significant relationship with surface water quality, and it was evident that built-up land had a more significant negative impact on water quality than the other land use classes. Both natural processes (rock weathering) and anthropogenic activities (wastewater discharge, industrial activities etc.) were found to be playing a vital role in water quality evolution. This study suggests that continuous assessment and monitoring of the spatial and temporal variability of water quality in Limpopo is important to control pollution and health safety in the future.
  • Ram Avtar, Deepak Singh, Deha Agus Umarhadi, Ali P. Yunus, Prakhar Misra, Pranav N. Desai, Asma Kouser, Tonni Agustiono Kurniawan, KBVN Phanindra
    Remote Sensing 13 (2) 183 - 183 2021/01/07 
    The COVID-19 related lockdowns have brought the planet to a standstill. It has severely shrunk the global economy in the year 2020, including India. The blue economy and especially the small-scale fisheries sector in India have dwindled due to disruptions in the fish catch, market, and supply chain. This research presents the applicability of satellite data to monitor the impact of COVID-19 related lockdown on the Indian fisheries sector. Three harbors namely Mangrol, Veraval, and Vankbara situated on the north-western coast of India were selected in this study based on characteristics like harbor’s age, administrative control, and availability of cloud-free satellite images. To analyze the impact of COVID in the fisheries sector, we utilized high-resolution PlanetScope data for monitoring and comparison of “area under fishing boats” during the pre-lockdown, lockdown, and post-lockdown phases. A support vector machine (SVM) classification algorithm was used to identify the area under the boats. The classification results were complemented with socio-economic data and ground-level information for understanding the impact of the pandemic on the three sites. During the peak of the lockdown, it was found that the “area under fishing boats” near the docks and those parked on the land area increased by 483%, 189%, and 826% at Mangrol, Veraval, and Vanakbara harbor, respectively. After phase-I of lockdown, the number of parked vessels decreased, yet those already moved out to the land area were not returned until the south-west monsoon was over. A quarter of the annual production is estimated to be lost at the three harbors due to lockdown. Our last observation (September 2020) result shows that regular fishing activity has already been re-established in all three locations. PlanetScope data with daily revisit time has a higher potential to be used in the future and can help policymakers in making informed decisions vis-à-vis the fishing industry during an emergency situation like COVID-19.
  • Ram Avtar, Miliana Navia, Jone Sassen, Masahiko Fujii
    Coastal Engineering Journal 2166-4250 2021 
    Despite the expected importance, the changes in mangrove ecosystems and the main causes in Fiji have not been well addressed. To address the issues, we collected data from multiple sources to assess mangrove ecosystem variation due to both natural factors and human impacts in the Ba and Rewa deltas, Fiji. Landsat satellite data were used to map the land use and cover of the study area from 2000 to 2020. Questionnaire surveys were conducted to identify the main uses of mangroves that could influence mangrove ecosystems. Over the period investigated, the mangrove area increased by 572 ha (by 12%) in Ba and decreased by 697 ha (by 9%) in Rewa. The social survey revealed that 45% of respondents in the Ba delta and 20% in the Rewa delta visited the mangrove area daily in search of food resources. The net annual economic loss and lost functioning of mangroves as an anthropogenic CO2 reservoir caused by mangrove degradation in the two deltas were estimated to be 335,000 USD and 202 t-C, respectively. Because local livelihoods are strongly linked with mangroves, the outcomes of this study will provide preliminary information for policy interventions to ensure the sustainability of the mangrove ecosystem.
  • Rajarshi Dasgupta, Shalini Dhyani, Mrittika Basu, Rakesh Kadaverugu, Shizuka Hashimoto, Pankaj Kumar, Brian Alan Johnson, Yasuo Takahashi, Bijon K. Mitra, Ram Avtar, Priyanka Mitra
    Environmental Management 0364-152X 2021 
    Globally, shifting cultivation is known to be an important driver of tropical deforestation. However, in this paper, we argue that it can be sustainably managed if the environmental boundary conditions, laid by the traditional customs and practices, are fully respected. We narrate an empirical study from the Zunheboto district of Nagaland, India, where we deployed a mixed research method to explore the Indigenous and Local Knowledge and Practices (ILKPs) associated with shifting cultivation (aka Jhum), particularly concerning farm-level practices, forest and biodiversity conservation, and disaster risk reduction measures. The research method included analysis of primary data obtained through Focus Group discussions (FGDs), key informant interviews (n = 21), and a questionnaire survey (n = 153) with Jhum farmers from two different age groups, i.e., below 50 years (middle-aged farmers) and above 50 years (older farmers). From the qualitative inquiry, we identified 15 ILKPs, which were then validated from survey responses. We used the Mann–Whitney U test to examine differences in agreement between two groups of framers. Based on this analysis, we conclude that upholding of the ILKPs holds strong potential for the local implementation of several Sustainable Development Goals (SDGs), particularly, SDG-1(No poverty), SDG-2 (Zero hunger), and SDG-15 (Life on land). However, eight of the identified ILKPs showed a statistically significant difference between older and middle-aged farmers, underlining a declining trend. Finally, we suggest suitable policy measures to mainstream ILKPs to balance the trade-offs in food production and biodiversity conservation, and to ensure the future sustainability of Jhum cultivation in the region and beyond.
  • Md Masroor, Sufia Rehman, Ram Avtar, Mehebub Sahana, Raihan Ahmed, Haroon Sajjad
    Weather and Climate Extremes 30 2212-0947 2020/12 
    Godavari middle sub-basin covering one district of Telangana state and eleven districts of Maharashtra state in India has been experiencing severe drought due to climate variability over the past several decades. Lying in the rain shadow zone of Western Ghats (mountain pass), it receives scant rainfall. Therefore, monitoring and assessing of drought is essential for lessening the impact on communities' livelihood and environment. We utilized forty grid points data from global weather data for SWAT portal during 1979–2013 for assessing drought conditions. Trends in important meteorological variables namely precipitation, temperature, wind speed, solar radiation and relative humidity were analyzed to examine the climate variability in the study area. Standardized precipitation index (SPI) was determined for one, three, six and twelve month drought. Mann Kendall test and Sen's slope were used to analyze trend in precipitation.Multiple linear regression was performed to establish relationship between meteorological variables and drought. Interpolation method of geographical information system (GIS) was utilized for spatial analyses of climate variability, drought and trend in precipitation in the study area. Findings revealed that watersheds located in south-western part of the sub-basin experienced decreasing trend in precipitation and consequent frequent droughts. The study further reveals that the meteorological variables have more impact on short-term drought.
  • Rajarshi Dasgupta, Mrittika Basu, Pankaj Kumar, Brian Alan Johnson, Bijon K. Mitra, Ram Avtar, Rajib Shaw
    International Journal of Disaster Risk Reduction 51 2212-4209 2020/12 
    The paper narrates a pilot study to understand disaster preparedness among foreign residents living in Japan, using typhoon Hagibis as a reference. We empirically evaluated an individual disaster preparedness framework following the 72-h golden rule of disaster survival. The framework consisted of 14 variables, and responses were collected over a five-point Likert scale. In addition, six perceptive variables, which provided a self-evaluation of disaster preparedness against the native Japanese population, were also administered to 133 foreign residents. The data were subjected to exploratory factor analysis and multiple linear regression modeling to understand the thematic dimensions and association of perceptive variables that contribute towards disaster preparedness. Our results indicated three interlinked dimensions, namely, (a) Emergency preparation and awareness (b) Experiential learning, and (c) Training and exposure. Of these, ‘Emergency preparation and awareness’ and “Training and exposure” showed a statistically significant and positive association with several perceptive variables (particularly, the ability to seek neighborhood help, participation in community events, and the ability to receive local level disaster information). The paper concludes with several recommendations, of which, building a local support network for foreign residents and to disseminate local disaster-related information remains critical.
  • Pankaj Kumar, Ram Avtar, Rajarshi Dasgupta, Brian Alan Johnson, Abhijit Mukherjee, Md Nasif Ahsan, Duc Cong Hiep Nguyen, Hong Quan Nguyen, Rajib Shaw, Binaya Kumar Mishra
    Progress in Disaster Science 8 2020/12 
    Rapid global changes (population growth, urbanization and frequent extreme weather conditions) have cumulatively affected local water bodies and resulted in unfavorable hydrological, ecological, and environmental changes in the major river systems. Particularly, communities in isolated riverine islands are heavily affected due to their poor adaptive capacities, which is well documented in the contemporary literature. The focal point for the vulnerability of these people lies in the water resources (drinking water availability, agricultural water quality, salt-water intrusion, flooding etc.) and the future interaction between human and water systems. This paper advocates the importance of socio-hydrological research in the context of enhancing social adaptive capacity as well as for developing a resilient water environment in three very large riverine islands in Asia: Fraserganj (India), Dakshin Bedkashi (Bangladesh) (both from the Ganges-Brahaputra-Meghna Delta) and Con Dao Island (Mekong River, Vietnam). It also explores how the nexus of human–water relations could be applied to improve adaptive measures to manage local water needs while mitigating undesirable changes to the hydrological cycle. Socio-hydrological models as an integrated tool can be used to quantify the feedbacks between water resources and society at multiple scales, with the aim of expediting stakeholder participation for sustainable water resource management. The proposed idea in this study will be helpful to sketch projections of alternatives that explicitly account for plausible and co-evolving trajectories of the socio-hydrological system, which will yield both insights into cause–effect relationships and help stakeholders to identify safe functioning space.
  • Ram Avtar, Akinola Adesuji Komolafe, Asma Kouser, Deepak Singh, Ali P. Yunus, Jie Dou, Pankaj Kumar, Rajarshi Das Gupta, Brian Alan Johnson, Huynh Vuong Thu Minh, Ashwani Kumar Aggarwal, Tonni Agustiono Kurniawan
    Remote Sensing Applications: Society and Environment 20 2020/11 
    The Earth's ecosystems face severe environmental stress from unsustainable socioeconomic development linked to population growth, urbanization, and industrialization. Governments worldwide are interested in sustainability measures to address these issues. Remote sensing allows for the measurement, integration, and presentation of useful information for effective decision-making at various temporal and spatial scales. Scientists and decision-makers have endorsed extensive use of remote sensing to bridge gaps among disciplines and achieve sustainable development. This paper presents an extensive review of remote sensing technology used to support sustainable development efforts, with a focus on natural resource management and assessment of natural hazards. We further explore how remote sensing can be used in a cross-cutting, interdisciplinary manner to support decision-making aimed at addressing sustainable development challenges. Remote sensing technology has improved significantly in terms of sensor resolution, data acquisition time, and accessibility over the past several years. This technology has also been widely applied to address key issues and challenges in sustainability. Furthermore, an evaluation of the suitability and limitations of various satellite-derived indices proposed in the literature for assessing sustainable development goals showed that these older indices still perform reasonably well. Nevertheless, with advancements in sensor radiometry and resolution, they were less exploited and new indices are less explored.
  • Atul Saini, Dr. Netrananda Sahu, Pankaj Kumar, Sridhara Nayak, Weili DUAN, Ram Avtar, Swadhin Behera
    Atmosphere 11 (11) 1225 - 1225 2020/11 
    In this paper, the rainfall trend of the West Coast Plain and Hill Agro-Climatic Region is analyzed for 117 years (1901–2017). This region is a globally recognized biodiversity hotspot and known for one of the highest rainfall receiving regions in India. Rainfall grid dataset is used for the analysis of rainfall trends on monthly, seasonal, and decadal time scales. Modified Mann–Kendall’s test, Linear Regression, Innovative Trend Analysis, Sen’s Slope test, Weibull’s Recurrence Interval, Pearson’s Coefficient of Skewness, Consecutive Disparity Index, Kurtosis, and some other important statistical techniques are employed for trend analysis. Results indicate that the rainfall trend is significant in January, July, August, September as well as the Winter season. Among all the significant trends, January and July showed a decreasing rainfall trend. July has the highest contribution (30%) among all the obtained monotonic trend to annual rainfall and coincidentally has the highest trend magnitude. August and September months with a combined contribution of 30% to annual rainfall, show an increasing monotonic trend with high magnitude whereas Winter season shows a monotonic decreasing rainfall trend with comparatively low magnitudes. Decadal analysis along with the study of recurrence interval of excess and deficit years helps to understand the decadal rhythm of trend and the magnitude of extreme monthly and seasonal events. Skewness reveals that rainfall dataset of all the periodic results is right-skewed and the recurrence interval also supports the skewness results. Sharply decreasing rainfall in July and rising rainfall in August and September is predictive of the impact on agriculture, biodiversity and indicates the rainfall regime shift in the region.
  • Ram Avtar, Stanley Anak Suab, Mohd Shahrizan Syukur, Alexius Korom, Deha Agus Umarhadi, Ali P. Yunus
    Remote Sensing 12 (18) 2020/09/17 
    The information on biophysical parameters-such as height, crown area, and vegetation indices such as the normalized difference vegetation index (NDVI) and normalized difference red edge index (NDRE)-are useful to monitor health conditions and the growth of oil palm trees in precision agriculture practices. The use of multispectral sensors mounted on unmanned aerial vehicles (UAV) provides high spatio-temporal resolution data to study plant health. However, the influence of UAV altitude when extracting biophysical parameters of oil palm from a multispectral sensor has not yet been well explored. Therefore, this study utilized the MicaSense RedEdge sensor mounted on a DJI Phantom-4 UAV platform for aerial photogrammetry. Three different close-range multispectral aerial images were acquired at a flight altitude of 20 m, 60 m, and 80 m above ground level (AGL) over the young oil palm plantation area in Malaysia. The images were processed using the structure from motion (SfM) technique in Pix4DMapper software and produced multispectral orthomosaic aerial images, digital surface model (DSM), and point clouds. Meanwhile, canopy height models (CHM) were generated by subtracting DSM and digital elevation models (DEM). Oil palm tree heights and crown projected area (CPA) were extracted from CHM and the orthomosaic. NDVI and NDRE were calculated using the red, red-edge, and near-infrared spectral bands of orthomosaic data. The accuracy of the extracted height and CPA were evaluated by assessing accuracy from a different altitude of UAV data with ground measured CPA and height. Correlations, root mean square deviation (RMSD), and central tendency were used to compare UAV extracted biophysical parameters with ground data. Based on our results, flying at an altitude of 60 m is the best and optimal flight altitude for estimating biophysical parameters followed by 80 m altitude. The 20 m UAV altitude showed a tendency of overestimation in biophysical parameters of young oil palm and is less consistent when extracting parameters among the others. The methodology and results are a step toward precision agriculture in the oil palm plantation area.
  • Zhu Mengting, Tonni Agustiono Kurniawan, You Yanping, Mohd Hafiz Dzarfan Othman, Ram Avtar, Dun Fu, Goh Hui Hwang
    Journal of Environmental Management 270 0301-4797 2020/09/15 
    We aim at fabricating a ternary magnetic recyclable Bi2WO6/BiOI@Fe3O4 composite that could be applied for photodegradation of tetracycline (TC) from synthetic wastewater. To identify any changes with respect to the composite's morphology and crystal structure properties, ΧRD, FTIR, FESEM-EDS, PL and VSM analyses are carried out. The effects of Fe3O4 loading ratio on the Bi2WO6/BiOI for TC photodegradation are evaluated, while operational parameters such as pH, reaction time, TC concentration, and photocatalyst's dose are optimized. Removal mechanisms of the TC by the composite and its photodegradation pathways are elaborated. With respect to its performance, under the same optimized conditions (1 g/L of dose; 5 mg/L of TC; pH 7; 3 h of reaction time), the Bi2WO6/BiOI@5%Fe3O4 composite has the highest TC removal (97%), as compared to the Bi2WO6 (63%). After being saturated, the spent photocatalyst could be magnetically separated from solution for subsequent use. In spite of three consecutive cycles with 71% of efficiency, the spent composite still has reasonable photocatalytic activities for reuse. Overall, this suggests that the composite is a promising photocatalyst for TC removal from aqueous solutions.
  • Tonni Agustiono Kurniawan, Zhu Mengting, Dun Fu, Swee Keong Yeap, Mohd Hafiz Dzarfan Othman, Ram Avtar, Tong Ouyang
    Journal of Environmental Management 270 110871 - 110871 0301-4797 2020/09/15 
    Methylene blue is a refractory pollutant commonly present in textile wastewater. This study tests the feasibility of TiO2/graphene oxide (GO) composite in enhancing photocatalytic degradation of MB in synthetic wastewater with respect to scientific and engineering aspects. To enhance its removal, we vary the composition of the composite based on the TiO2 weight. Under UV–vis irradiation, the effects of photocatalyst's dose, pH, and reaction time on MB removal by the composites are evaluated under optimum conditions, while any changes in their physico-chemical properties before and after treatment are analyzed by using TEM, SEM, XRD, FTIR and BET. The photodegradation pathways of the target pollutant by the composite and its removal mechanisms are also elaborated. It is found that the same composite with a 1:2 wt ratio of GO/TiO2 has the largest surface area of 104.51 m2/g. Under optimum reactions (0.2 g/L of dose, pH 10, and 5 mg/L of pollutant's concentration), an almost complete MB removal could be attained within 4 h. This result is higher than that of the TiO2 alone (30%) under the same conditions. Since the treated effluents could meet the strict discharge standard limit of ≤0.2 μg/L set by China's regulation, subsequent biological treatments are unnecessary for completing biodegradation of remaining oxidation by-products in the wastewater effluents.
  • Ram Avtar, Pankaj Kumar, Hitesh Supe, Dou Jie, Netranada Sahu, Binaya Mishra, Ali Yunus
    Water 12 (9) 2020/09/15 
    The novel coronavirus pandemic (COVID-19) has brought countries around the world to a standstill in the early part of 2020. Several nations and territories around the world insisted their population stay indoors for practicing social distance in order to avoid infecting the disease. Consequently, industrial activities, businesses, and all modes of traveling have halted. On the other hand, the pollution level decreased 'temporarily' in our living environment. As fewer pollutants are supplied in to the hydrosphere, and human recreational activities are stopped completely during the lockdown period, we hypothesize that the hydrological residence time (HRT) has increased in the semi-enclosed or closed lake bodies, which can in turn increase the primary productivity. To validate our hypothesis, and to understand the effect of lockdown on primary productivity in aquatic systems, we quantitatively estimated the chlorophyll-a (Chl-a) concentrations in different lake bodies using established Chl-a retrieval algorithm. The Chl-a monitored using Landsat-8 and Sentinel-2 sensor in the lake bodies of Wuhan, China, showed an elevated concentration of Chl-a. In contrast, no significant changes in Chl-a are observed for Vembanad Lake in India. Further analysis of different geo-environments is necessary to validate the hypothesis.
  • Prakhar Misra, Ryoichi Imasu, Sachiko Hayashida, Ardhi Adhary Arbain, Ram Avtar, Wataru Takeuchi
    ISPRS International Journal of Geo-Information 9 (9) 544 - 544 2020/09/11 
    Cities lying in the Indo-Gangetic plains of South Asia have the world’s worst anthropogenic air pollution, which is often attributed to urban growth. Brick kilns, facilities for producing fired clay-bricks for construction are often found at peri-urban region of South Asian cities. Although brick kilns are significant air pollutant emitters, their contribution in under-represented in air pollution emission inventories due to unavailability of their distribution. This research overcomes this gap by proposing publicly available remote sensing dataset based approach for mapping brick-kiln locations using object detection and pixel classification. As brick kiln locations are not permanent, an open-dataset based methodology is advantageous for periodically updating their locations. Brick kilns similar to Bull Trench Kilns were identified using the Sentinel-2 imagery around the state of Delhi in India. The unique geometric and spectral features of brick kilns distinguish them from other classes such as built-up, vegetation and fallow-land even in coarse resolution imagery. For object detection, transfer learning was used to overcome the requirement of huge training datasets, while for pixel-classification random forest algorithm was used. The method achieved a recall of 0.72, precision of 0.99 and F1 score of 0.83. Overall 1564 kilns were detected, which are substantially higher than what was reported in an earlier study over the same region. We find that brick kilns are located outside urban areas in proximity to outwardly expanding built-up areas and tall built structures. Duration of brick kiln operation was also estimated by analyzing the time-series of normalized difference vegetation index (NDVI) over the brick kiln locations. The brick kiln locations can be further used for updating land-use emission inventories to assess particulate matter and black carbon emissions.
  • Netrananda Sahu, Atul Saini, Swadhin Behera, Takahiro Sayama, Sridhara Nayak, Limonlisa Sahu, Weili Duan, Ram Avtar, Masafumi Yamada, R. B. Singh, Kaoru Takara
    Sustainability (Switzerland) 12 (17) 2020/09 
    The impact of Indo-Pacific climate variability in the South Asian region is very pronounced and their impact on agriculture is very important for the Indian subcontinent. In this study, rice productivity, climatic factors (Rainfall, Temperature and Soil Moisture) and associated major Indo-Pacific climate indices in Bihar were investigated. Bihar is one of the major rice-producing states of India and the role of climate variability and prevailing climate indices in six events (between 1991-2014) with severer than-10% rice productivity are analyzed. The Five-year moving average, Pearson's Product Moment Correlation, Partial Correlation, Linear Regression Model, Mann Kendall Test, Sen's Slope and some other important statistical techniques were used to understand the association between climatic variables and rice productivity. Pearson's Product Moment Correlation provided an overview of the significant correlation between climate indices and rice productivity. Whereas, Partial Correlation provided the most refined results on it and among all the climate indices, Nino 3, Ocean Nino Index and Southern Oscillation Index are found highly associated with years having severer than-10% decline in rice productivity. Rainfall, temperature and soil moisture anomalies are analyzed to observe the importance of climate factors in rice productivity. Along with the lack of rainfall, lack of soil moisture and persistent above normal temperature (especially maximum temperature) are found to be the important factors in cases of severe loss in rice productivity. Observation of the dynamics of ocean-atmosphere coupling through the composite map shows the Pacific warming signals during the event years. The analysis revealed a negative (positive) correlation of rice productivity with the Nino 3 and Ocean Nino Index (Southern Oscillation Index).
  • Ram Avtar, Kenichi Tsusaka, Srikantha Herath
    Environmental Monitoring and Assessment 192 (9) 0167-6369 2020/09 
    Forests hold significant potential for carbon sequestration and climate change mitigation. Forest biomass estimation is vital for sustainable forest management, providing critical input data for implementing the United Nations Reducing Emissions from Deforestation and forest Degradation-plus (REDD+) mechanism. This study investigates the total carbon pools—aboveground biomass (AGB), belowground biomass (BGB), forest floor biomass, and soil carbon—using field-based information in the muyong forest management system, which is native to Ifugao in the Philippines. This study reveals that a difference may be observed between the total carbon stock of the private woodlots (muyong) and that of the communal forest (bilid). The results indicate that the bilid forest has trees with a small diameter at breast height (DBH) and high tree density in contrast to the muyong, which has trees with high DBH and low tree density. The average carbon stock per unit area is higher in muyong (150.8 tC/ha) than in bilid (126.1 tC/ha). These findings are valuable in determining whether Ifugao’s muyong forest system should be included under the REDD+ framework. Human mediation and management helps forests to sequester a greater amount of carbon than they would without human intervention. Implementation of REDD+ should promote Ifugao’s ecosystem and biodiversity conservation and agroforestry practices in addition to protecting traditional agricultural practices and livelihoods in relation to rice terraces.
  • Manish Ramaiah, Ram Avtar, Md. Mustafizur Rahman
    Land 9 (9) 292 - 292 2020/08/24 
    Elucidating the impact of Land Surface Temperature (LST) is an important aspect of urban studies. The impact of urbanization on LST has been widely studied to monitor the Urban Heat Island (UHI) phenomenon. However, the sensitivity of various urban factors such as urban green spaces (UGS), built-up area, and water bodies to LST is not sufficiently resolved for many urban settlements. By using remote sensing techniques, this study aimed to quantify the influence of urban factors on LST in the two traditional cities (i) Panaji and (ii) Tumkur of India, proposed to be developed as smart cities. Landsat data were used to extract thematic and statistical information about urban factors using the Enhanced Built-up and Bareness Index (EBBI), Modified Normalized Difference Water Index (MNDWI), and Soil Adjusted Vegetation Index (SAVI). The multivariate regression model revealed that the value of adjusted R2 was 0.716 with a standard error of 1.97 for Tumkur city, while it was 0.698 with a standard error of 1.407 for Panaji city. The non-parametric correlation test brought out a strong negative correlation between MNDWI and LST with a value of 0.83 for Panaji, and between SAVI and LST with a value of 0.77 for Tumkur. The maximum percentage share of cooling surfaces are water bodies in Panaji with 35% coverage and green spaces in Tumkur with 25% coverage. Apparently, the UGS and water bodies can help in bringing down the LST, as well as facilitating healthy living conditions and aesthetic appeal. Therefore, the significance of ecosystem services (green spaces and water bodies) should be given priority in the decision-making process of sustainable and vibrant city development.
  • Stanley Anak Suab, Yuichi Hayakawa, Shogo Kume, Yuji Yamaguchi, Bakyt Amanbaeva, Abdynaby Kadyrov, Ram Avtar, Takuro Ogura
    IOP Conference Series: Earth and Environmental Science 540 (1) 012014 - 012014 1755-1307 2020/08/04 
    Geospatial technologies such as Unmanned Aerial Vehicle (UAV) and Global Navigation Satellite Systems (GNSS) are becoming popular in various applications also for archaeological purposes. This is due to the abilities also the usefulness of UAV and GNSS technologies for digitally documenting and recording archaeological sites in great detail. Such information is crucial for the efforts of preserving and protecting historical sites. This paper demonstrates the workflows and results of mapping techniques using consumer-grade UAV for aerial survey and low-cost Post-Processing Kinematics (PPK) GNSS ground survey for documentation of two archaeological sites in Batken State, Kyrgyzstan in Central Asia. Both UAV and PPK GNSS data were acquired simultaneously during the fieldworks in early winter while processing were explicitly done using currently available commercial and open-source software. Results of the UAV and PPK GNSS was combined and qualitatively evaluated. Despite advantages and disadvantages identified in both UAV and PPK GNSS results, it was learned that the combination of both techniques found to be very beneficial for mapping of archaeological sites.
  • Abdelaziz Merghadi, Ali P. Yunus, Jie Dou, Jim Whiteley, Binh ThaiPham, Dieu Tien Bui, Ram Avtar, Boumezbeur Abderrahmane
    Earth-Science Reviews 207 0012-8252 2020/08 
    Landslides are one of the catastrophic natural hazards that occur in mountainous areas, leading to loss of life, damage to properties, and economic disruption. Landslide susceptibility models prepared in a Geographic Information System (GIS) integrated environment can be key for formulating disaster prevention measures and mitigating future risk. The accuracy and precision of susceptibility models is evolving rapidly from opinion-driven models and statistical learning toward increased use of machine learning techniques. Critical reviews on opinion-driven models and statistical learning in landslide susceptibility mapping have been published, but an overview of current machine learning models for landslide susceptibility studies, including background information on their operation, implementation, and performance is currently lacking. Here, we present an overview of the most popular machine learning techniques available for landslide susceptibility studies. We find that only a handful of researchers use machine learning techniques in landslide susceptibility mapping studies. Therefore, we present the architecture of various Machine Learning (ML) algorithms in plain language, so as to be understandable to a broad range of geoscientists. Furthermore, a comprehensive study comparing the performance of various ML algorithms is absent from the current literature, making an assessment of comparative performance and predictive capabilities difficult. We therefore undertake an extensive analysis and comparison between different ML techniques using a case study from Algeria. We summarize and discuss the algorithm's accuracies, advantages and limitations using a range of evaluation criteria. We note that tree-based ensemble algorithms achieve excellent results compared to other machine learning algorithms and that the Random Forest algorithm offers robust performance for accurate landslide susceptibility mapping with only a small number of adjustments required before training the model.
  • Netrananda Sahu, Arpita Panda, Sridhara Nayak, Atul Saini, Manoranjan Mishra, Takahiro Sayama, Limonlisa Sahu, Weili Duan, Ram Avtar, Swadhin Behera
    Water 12 (7) 2020/07/09 
    The potential impact of climate variability on the hydrological regime in the Mahanadi river basin is of great importance for sustainable water resources management. The impact of climate variability on streamflow is analyzed in this study. The impact of climate variability modes on extreme events of Mahanadi basin during June, July, and August (JJA), and September, October, and November (SON) seasons were analyzed, with daily streamflow data of four gauge stations for 34 years from 1980 to 2013 found to be associated with the sea surface temperature variations over Indo-Pacific oceans and Indian monsoon. Extreme events are identified based on their persistent flow for six days or more, where selection of the stations was based on the fact that there was no artificially regulated streamflow in any of the stations. Adequate scientific analysis was done to link the streamflow variability with the climate variability and very significant correlation was found with Indian Ocean Dipole (IOD), El Nino Southern Oscillation (ENSO), El Nino Modoki Index (EMI), and Indian monsoon. Agriculture covers major portion of the basin; hence, the streamflow is very much essential for agriculture as well as population depending on it. Any disturbances in the general flow of the river has subjected an adverse impact on the inhabitants' livelihood. While analyzing the correlation values, it was found that all stations displayed a significant positive correlation with Indian Monsoon. The respective correlation values were 0.53, 0.38, 0.44, and 0.38 for Andhiyarkore, Baronda, Rajim, and Kesinga during JJA season. Again in the case of stepwise regression analysis, Monsoon Index for the June, July, and August (MI-JJA) season (0.537 for Andhiyarkore) plays significant role in determining streamflow of Mahanadi basin during the JJA season and Monsoon Index for July, August, and September (MI-JAS) season (0.410 for Baronda) has a strong effect in affecting streamflow of Mahanadi during the SON season. Flood frequency analysis with Weibull's plotting position method indicates future floods in the Mahanadi river basin in JJA season.
  • Huynh Vuong Thu Minh, Ram Avtar, Pankaj Kumar, Kieu Ngoc Le, Masaaki Kurasaki, Tran Van Ty
    Water 12 (6) 1710 - 1710 2020/06/15 
    A few studies have evaluated the impact of land use land cover (LULC) change on surface water quality in the Vietnamese Mekong Delta (VMD), one of the most productive agricultural deltas in the world. This study aims to evaluate water quality parameters inside full-and semi-dike systems and outside of the dike system during the wet and dry season in An Giang Province. Multivariable statistical analysis and weighted arithmetic water quality index (WAWQI) were used to analyze 40 water samples in each seasons. The results show that the mean concentrations of conductivity (EC), phosphate (PO43-), ammonium (NH4+), chemical oxygen demand (COD), and potassium (K+) failed to meet theWorld Health Organization (WHO) and Vietnamese standards for both seasons. The NO2- concentration inside triple and double rice cropping systems during the dry season exceeds the permissible limit of the Vietnamese standard. The high concentration of COD, NH4+ were found in the urban area and the main river (Bassac River). TheWAWQI showed that 97.5 and 95.0% of water samples fall into the bad and unsuitable, respectively, for drinking categories. The main reason behind this is direct discharge of untreated wastewater from the rice intensification and urban sewerage lines. The finding of this study is critically important for decision-makers to design different mitigation or adaptation measures for water resource management in lieu of rapid global changes in a timely manner in An Giang and the VMD.
  • Jie Dou, Ali P. Yunus, Abdelaziz Merghadi, Ataollah Shirzadi, Hoang Nguyen, Yawar Hussain, Ram Avtar, Yulong Chen, Binh Thai Pham, Hiromitsu Yamagishi
    Science of The Total Environment 720 137320 - 137320 0048-9697 2020/06 [Refereed][Not invited]
     
    © 2020 Elsevier B.V. Predictive capability of landslide susceptibilities is assumed to be varied with different sampling techniques, such as (a) the landslide scarp centroid, (b) centroid of landslide body, (c) samples of the scrap region representing the scarp polygon, and (d) samples of the landslide body representing the entire landslide body. However, new advancements in statistical and machine learning algorithms continuously being updated the landslide susceptibility paradigm. This paper explores the predictive performance power of different sampling techniques in landslide susceptibility mapping in the wake of increased usage of artificial intelligence. We used logistic regression (LR), neural network (NNET), and deep learning neural network (DNN) model for testing and validation of the models. The tests were applied to the 2018 Hokkaido Earthquake affected areas using a set of 11 predictor variables (seismic, topographic, and hydrological). We found that the prediction rates are inconsequential with the DNN model irrespective of the sampling technique (AUC: 0.904 – 0.919). Whereas, testing with LR (AUC: 0.825 – 0.785) and NNET (AUC: 0.882 – 0.858) produces larger differences in the accuracies between the four datasets. Nonetheless, the highest success rates were obtained for samples within the landslide scarp area. The analogy was then validated with a published landslide inventory from the 2015 Gorkha earthquake. We, therefore, suggest that DNN models as an appropriate technique to increase the predictive performance of landslide susceptibilities if the landslide scarp and body are not characterized properly in an inventory.
  • Hitesh Supe, Ram Avtar, Deepak Singh, Ankita Gupta, Ali P. Yunus, Jie Dou, Ankit A. Ravankar, Geetha Mohan, Saroj Kumar Chapagain, Vivek Sharma, Chander Kumar Singh, Olga Tutubalina, Ali Kharrazi
    Remote Sensing 12 (9) 1466  2020/05/05 [Refereed][Not invited]
     
    The soiling of solar panels from dry deposition affects the overall efficiency of power output from solar power plants. This study focuses on the detection and monitoring of sand deposition (wind-blown dust) on photovoltaic (PV) solar panels in arid regions using multitemporal remote sensing data. The study area is located in Bhadla solar park of Rajasthan, India which receives numerous sandstorms every year, carried by westerly and north-westerly winds. This study aims to use Google Earth Engine (GEE) in monitoring the soiling phenomenon on PV panels. Optical imageries archived in the GEE platform were processed for the generation of various sand indices such as the normalized differential sand index (NDSI), the ratio normalized differential soil index (RNDSI), and the dry bare soil index (DBSI). Land surface temperature (LST) derived from Landsat 8 thermal bands were also used to correlate with sand indices and to observe the pattern of sand accumulation in the target region. Additionally, high-resolution PlanetScope images were used to quantitatively validate the sand indices. Our study suggests that the use of freely available satellite data with semiautomated processing on GEE can be a useful alternative to manual methods. The developed method can provide near real-time monitoring of soiling on PV panels cost-effectively. This study concludes that the DBSI method has a comparatively higher potential (89.6% Accuracy, 0.77 Kappa) in the detection of sand deposition on PV panels as compared to other indices. The findings of this study can be useful to solar energy companies in the development of an operational plan for the cleaning of PV panels regularly.
  • Pankaj Kumar, Brian Alan Johnson, Rajarshi Dasgupta, Ram Avtar, Shamik Chakraborty, Masayuki Kawai, Damasa B. Magcale-Macandog
    Water 12 (4) 2020/04/19 
    Due to the cumulative effects of rapid urbanization, population growth and climate change, many inland and coastal water bodies around the world are experiencing severe water pollution. To help make land-use and climate change adaptation policies more effective at a local scale, this study used a combination of participatory approaches and computer simulationmodeling. Thismethodology (called the "ParticipatoryWatershed Land-use Management" (PWLM) approach) consist of four major steps: (a) Scenario analysis, (b) impact assessment, (c) developing adaptation and mitigation measures and its integration in local government policies, and (d) improvement of land use plan. As a test case, we conducted PWLM in the Santa Rosa Sub-watershed of the Philippines, a rapidly urbanizing area outside Metro Manila. The scenario analysis step involved a participatory land-use mapping activity (to understand future likely land-use changes), as well as GCM precipitation and temperature data downscaling (to understand the local climate scenarios). For impact assessment, the Water Evaluation and Planning (WEAP) tool was used to simulate future river water quality (BOD and E. coli) under a Business as Usual (BAU) scenario and several alternative future scenarios considering different drivers and pressures (to 2030). Water samples from the Santa Rosa River in 2015 showed that BOD values ranged from 13 to 52 mg/L; indicating that the river is already moderately to extremely polluted compared to desirable water quality (class B). In the future scenarios, we found that water quality will deteriorate further by 2030 under all scenarios. Population growth was found to have the highest impact on future water quality deterioration, while climate change had the lowest (although not negligible). After the impact assessment, different mitigation measures were suggested in a stakeholder consultation workshop, and of them (enhanced capacity of wastewater treatment plants (WWTPs), and increased sewerage connection rate) were adopted to generate a final scenario including countermeasures. The main benefit of the PWLM approach are its high level of stakeholder involvement (through co-generation of the research) and use of free (for developing countries) software and models, both of which contribute to an enhanced science-policy interface.
  • Md. Mustafizur Rahman, Ram Avtar, Ali P. Yunus, Jie Dou, Prakhar Misra, Wataru Takeuchi, Netrananda Sahu, Pankaj Kumar, Brian Alan Johnson, Rajarshi Dasgupta, Ali Kharrazi, Shamik Chakraborty, Tonni Agustiono Kurniawan
    Remote Sensing 12 (7) 1191 - 1191 2020/04/08 [Refereed][Not invited]
     
    Spatial urban growth and its impact on land surface temperature (LST) is a high priority environmental issue for urban policy. Although the impact of horizontal spatial growth of cities on LST is well studied, the impact of the vertical spatial distribution of buildings on LST is under-investigated. This is particularly true for cities in sub-tropical developing countries. In this study, TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-XDEM), Advanced Spaceborne Thermal Emission and Reflection (ASTER)-Global Digital Elevation Model (GDEM), and ALOSWorld 3D-30m (AW3D30) based Digital Surface Model (DSM) data were used to investigate the vertical growth of the Dhaka Metropolitan Area (DMA) in Bangladesh. Thermal Infrared (TIR) data (10.6-11.2μm) of Landsat-8 were used to investigate the seasonal variations in LST. Thereafter, the impact of horizontal and vertical spatial growth on LST was studied. The result showed that: (a) TanDEM-X DSM derived building height had a higher accuracy as compared to other existing DSM that reveals mean building height of the Dhaka city is approximately 10 m, (b) built-up areas were estimated to cover approximately 94%, 88%, and 44% in Dhaka South City Corporation (DSCC), Dhaka North City Corporation (DNCC), and Fringe areas, respectively, of DMA using a Support Vector Machine (SVM) classification method, (c) the built-up showed a strong relationship with LST (Kendall tau coefficient of 0.625 in summer and 0.483 in winter) in comparison to vertical growth (Kendall tau coefficient of 0.156 in the summer and 0.059 in the winter), and (d) the 'low height-high density' areas showed high LST in both seasons. This study suggests that vertical development is better than horizontal development for providing enough open spaces, green spaces, and preserving natural features. This study provides city planners with a better understating of sustainable urban planning and can promote the formulation of action plans for appropriate urban development policies.
  • John Mawenda, Teiji Watanabe, Ram Avtar
    Sustainability 12 (6) 2020/03/18 
    Rapid and unplanned urban growth has adverse environmental and social consequences. This is prominent in sub-Saharan Africa where the urbanisation rate is high and characterised by the proliferation of informal settlements. It is, therefore, crucial that urban land use/land cover (LULC) changes be investigated in order to enhance effective planning and sustainable growth. In this paper, the spatial and temporal LULC changes in Blantyre city were studied using the integration of remotely sensed Landsat imageries of 1994, 2007 and 2018, and a geographic information system (GIS). The supervised classification method using the support vector machine algorithm was applied to generate the LULC maps. The study also analysed the transition matrices derived from the classified map to identify prominent processes of changes for planning prioritisation. The results showed that the built-up class, which included urban structures such as residential, industrial, commercial and public installations, increased in the 24-year study period. On the contrary, bare land, which included vacant lands, open spaces with little or no vegetation, hilly clear-cut areas and other fallow land, declined over the study period. This was also the case with the vegetation class (i.e., forests, parks, permanent tree-covered areas and shrubs). The post-classification results revealed that the LULC changes during the second period (2007-2018) were faster compared to the first period (1994-2007). Furthermore, the results revealed that the increase in built-up areas systematically targeted the bare land and avoided the vegetated areas, and that the vegetated areas were systematically cleared to bare land during the study period (1994-2018). The findings of this study have revealed the pressure of human activities on the land and natural environment in Blantyre and provided the basis for sustainable urban planning and development in Blantyre city.
  • Zhu Mengting, Tonni Agustiono Kurniawan, You Yanping, Ram Avtar, Mohd Hafiz Dzarfan Othman
    Materials Science and Engineering C 108 0928-4931 2020/03 
    Bisphenol A (BPA) is a refractory pollutant presents in water body that possesses serious threats to living organisms. To deal with it, we investigate and evaluate the effectiveness of GO@BiOI/Bi2WO6 composite as a novel photocatalyst for BPA removal from aqueous solutions under UV–vis irradiation. To enhance its removal for BPA, the surface of BiOI/Bi2WO6 is modified with graphene oxide (GO). This composite is named as ‘GO@BiOI/Bi2WO6’. Changes in its physico-chemical properties after surface modification with GO are characterized by XRD, FTIR, FESEM-EDS, XPS, PL, and BET methods. Optimized conditions of BPA degradation by the composite are determined under identical conditions. Photodegradation pathways of BPA and its removal mechanisms by the same composite are presented. It is obvious that the GO@BiOI/Bi2WO6 has demonstrated its potential as a promising photocatalyst for BPA removal under UV–vis irradiation. About 81% of BPA removal is attained by the GO@BiOI/Bi2WO6 under optimized conditions (10 mg/L of BPA, 0.5 g/L of dose, pH 7 and 5 h of reaction time). The oxidation by-products of BPA degradation include p-hydroquinone or 4-(1-hydroxy-1-methyl-ethyl)-phenol. In spite of its performance, the treated effluents are still unable to meet the maximum discharge limit of <1 mg/L set by national legislation. Therefore, subsequent biological processes are essential to maximize its biodegradation in the wastewater samples before their discharge into waterbody.
  • Ram Avtar, Ali P. Yunus, Osamu Saito, Ali Kharrazi, Pankaj Kumar, Kazuhiko Takeuchi
    Geocarto International 37 (2) 1 - 17 1010-6049 2020/02/11 
    Operational monitoring of vegetation and its response to climate change involves the use of vegetation indices (VIs) in relation to relevant climatic data. This study analyses the temporal variations of vegetation indices in response to climatic data (temperature and precipitation) to better understand the phenological changes in the Wa-West and Tolon districts of Ghana during 1999–2011. This study also examines the inter-annual variation of vegetation indices and lag effects of climate variables (temperature and precipitation) using simple regression and correlation approaches. Results indicate that the mean Normalized Difference Vegetation Index (NDVI) and Normalized Difference Soil Index (NDSI) were significantly correlated with the mean temperature, whereby the value of NDVI increases with a decrease in temperature and value of NDSI increases with an increase in temperature. On examining seasonal variations, our findings indicated that the months of August and September have the highest mean NDVI values. This study confirms that consistently rising temperature and altered precipitation patterns have exerted a strong influence on temporal distributions and productivities of the terrestrial ecosystems of the Tolon and Wa-West districts of Ghana. Furthermore, this research demonstrates how vegetation indices can be used as an indicator to monitor phenological changes in the terrestrial ecosystem.
  • Ai Hojo, Kentaro Takagi, Ram Avtar, Takeo Tadono, Futoshi Nakamura
    Remote Sensing 12 (3) 349 - 349 2020/01/21 
    In this study, we compared the accuracies of above-ground biomass (AGB) estimated by integrating ALOS (Advanced Land Observing Satellite) PALSAR (Phased-Array-Type L-Band Synthetic Aperture Radar) data and TanDEM-X-derived forest heights (TDX heights) at four scales from 1/4 to 25 ha in a hemi-boreal forest in Japan. The TDX heights developed in this study included nine canopy height models (CHMs) and three model-based forest heights (ModelHs); the nine CHMs were derived from the three digital surface models (DSMs) of (I) TDX 12 m DEM (digital elevation model) product, (II) TDX 90 m DEM product and (III) TDX 5 m DSM, which we developed from two TDX-TSX (TerraSAR-X) image pairs for reference, and the three digital terrain models (DTMs) of (i) an airborne Light Detection and Ranging (LiDAR)-based DTM (LiDAR DTM), (ii) a topography-based DTM and (iii) the Shuttle Radar Topography Mission (SRTM) DEM; the three ModelHs were developed from the two TDX-TSX image pairs used in (III) and the three DTMs (i to iii) with the Sinc inversion model. In total, 12 AGB estimation models were developed for comparison. In this study, we included the C-band SRTM DEM as one of the DTMs. According to Walker et al. (2007), the SRTM DEM serves as a DTM for most of the Earth's surface, except for the areas with extensive tree and/or shrub coverage, e.g., the boreal and Amazon regions. As our test site is located in a hemi-boreal zone with medium forest cover, we tested the ability of the SRTM DEM to serve as a DTM in our test site. This study especially aimed to analyze the capability of the two TDX DEM products (I and II) to estimate AGB in practice in the hemi-boreal region, and to examine how the different forest height creation methods (the simple DSM and DTM subtraction for the nine CHMs and the Sinc inversion model-based approach for the three ModelHs) and the different spatial resolutions of the three DSMs and three DTMs affected the AGB estimation results. We also conducted the slope-class analysis to see how the varying slopes influenced the AGB estimation accuracies. The results show that the combined use of the PALSAR data and the CHM derived from (I) TDX 12 m DEM and (i) LiDAR DTM achieved the highest AGB estimation accuracies across the scales (R2 ranged from 0.82 to 0.97), but the CHMs derived from (I) TDX 12 m DEM and another two DTMs, (ii) and (iii), showed low R2 values at any scales. In contrast, the two CHMs derived from (II) TDX 90 m DEM and both (i) LiDAR DTM and (iii) SRTM DEM showed high R2 values > 0.87 and 0.78, respectively, at the scales > 9.0 ha, but they yielded much lower R2 values at smaller scales. The three ModelHs gave the lowest R2 values across the scales (R2 ranged from 0.39 to 0.60). Analyzed by slope class at the 1.0 ha scale, however, all the 12 AGB estimation models yielded high R2 values > 0.66 at the lowest slope class (0° to 9.9°), including the three ModelHs (R2 ranged between 0.68 to 0.69). The two CHMs derived from (II) TDX 90 m DEM and both (i) LiDAR DTM and (iii) SRTM DEM showed R2 values of 0.80 and 0.71, respectively, at the lowest slope class, while the CHM derived from (I) TDX 12 m DEM and (i) LiDAR DTM showed high R2 values across the slope classes (R2 > 0.82). The results show that (I) TDX 12 m DEM had a high capability to estimate AGB, with a high accuracy across the scales and the slope classes in the form of CHM, but the use of (i) LiDAR DTM was required. On the other hand, (II) TDX 90 m DEM was able to achieve high AGB estimation accuracies not only with (i) LiDAR DTM, but also with (iii) SRTM DEM in the form of CHM, but it was limited to large scales > 9.0 ha; however, all the models developed in this study have the possibility to achieve higher AGB estimation accuracies at the 1.0 ha scale in flat terrains with slope < 10°. The analysis showed the strengths and limitations of each model, and it also indicates that the data creation methods, the spatial resolutions of datasets and topographic features affects the effective spatial scales for AGB mapping, and the optimal combinations of these features should be chosen to obtain high AGB estimation accuracies.
  • Ram Avtar, Ridhika Aggarwal, Ali Kharrazi, Pankaj Kumar, Tonni Agustiono Kurniawan
    Environmental Monitoring and Assessment 192 (1) 0167-6369 2020/01 
    It is more than 4 years since the 2030 agenda for sustainable development was adopted by the United Nations and its member states in September 2015. Several efforts are being made by member countries to contribute towards achieving the 17 Sustainable Development Goals (SDGs). The progress which had been made over time in achieving SDGs can be monitored by measuring a set of quantifiable indicators for each of the goals. It has been seen that geospatial information plays a significant role in measuring some of the targets, hence it is relevant in the implementation of SDGs and monitoring of their progress. Synoptic view and repetitive coverage of the Earth’s features and phenomenon by different satellites is a powerful and propitious technological advancement. The paper reviews robustness of Earth Observation data for continuous planning, monitoring, and evaluation of SDGs. The scientific world has made commendable progress by providing geospatial data at various spatial, spectral, radiometric, and temporal resolutions enabling usage of the data for various applications. This paper also reviews the application of big data from earth observation and citizen science data to implement SDGs with a multi-disciplinary approach. It covers literature from various academic landscapes utilizing geospatial data for mapping, monitoring, and evaluating the earth’s features and phenomena as it establishes the basis of its utilization for the achievement of the SDGs.
  • Shamik Chakraborty, Ram Avtar, Raveena Raj, Huynh Vuong Thu Minh
    Land 8 (12) 2019/12/01 
    This study investigates different provisioning services in the peri-urban landscapes of Manila conurbation through a case study of two villages in the Jala-Jala municipality of the Laguna de Bay area in the Philippines. Laguna de Bay is an ecologically productive and important watershed for the urban and peri-urban areas of Manila for the provision of food, freshwater, and other materials. However, the lake and its ecosystem are under threat because of rapid urbanization and associated land-use changes. This study is based on a semi-quantitative survey conducted with 90 households in two villages: Special District and Paalaman. It was aimed to capture how provisioning services in the locality are connected with local livelihoods. The results obtained from the study suggest that landscapes in this peri-urban area still has considerable provisioning ecosystem services associated with local biodiversity and that this dependence on provisioning services and their relationship to peri-urban landscapes and biodiversity should be addressed for sustainable landscape management. The results have important implications for the conservation potential of biodiversity on which local livelihoods depend, in urban and peri-urban ecosystems.
  • Huynh Thi Cam Hong, Ram Avtar, Masahiko Fujii
    Tropical Ecology 60 (4) 552 - 565 0564-3295 2019/12/01 
    Mangroves are one of the most valuable and productive coastal ecosystems. Previous studies show a severe loss of mangroves around the world over the last several decades due to natural and anthropogenic activities. Mangroves located in the southeastern part of the Mekong River Delta (MRD) are also affected by these activities. Shrimp farming is considered as one of the main drivers causing the rapid loss and degradation of mangroves. The goal of this study is to assess the spatiotemporal changes in land use and distribution of mangroves in the Soc Trang and Bac Lieu provinces of the southeastern part of the MRD. Multi-temporal Landsat data were used for land use and land cover (LULC) classification using the maximum-likelihood classification algorithm. The changes in mangrove forest areas were monitored using medium spatial resolution (Landsat-5 Thematic Mapper and Landsat-8 Operational Land Imager) satellite imageries from 1988 to 2018. In the study area, there were seven major LULC types namely, dense mangroves, sparse mangroves, aquaculture farms, arable land with crop cover, arable land without crop cover, settlements, and water bodies. The overall accuracies of the LULC maps in 1988, 1998, 2008, and 2018 were 81.2%, 83.3%, 78.3%, and 81.9%, respectively. This study reveals that dense and sparse mangrove forests have decreased by 90% from 5495 hectares (ha) to 515 ha and by 55% from 14,105 to 6289 ha, respectively from 1988 to 2018. On the other hand, the aquaculture farm has increased at the rate of 5024 ha/year for a period of 30 years. This rapid growth of aquaculture farming activities caused the rapid loss and degradation of mangroves in the MRD. Quantitative information about mangrove change obtained by this study is considered to be useful for future coastal management and relevant policies in the MRD.
  • Pankaj Kumar, Rajarshi Dasgupta, Manish Ramaiah, Ram Avtar, Brian Alan Johnson, Binaya Kumar Mishra
    International Journal of Environmental Research and Public Health 16 (23) 1661-7827 2019/12/01 [Refereed][Not invited]
     
    © 2019 by the authors. Licensee MDPI, Basel, Switzerland. Just a few decades ago, Adyar River in India’s city of Chennai was an important source of water for various uses. Due to local and global changes (e.g., population growth and climate change), its ecosystem and overall water quality, including its aesthetic value, has deteriorated, and the water has become unsuitable for commercial uses. Adverse impacts of excessive population and changing climate are expected to continue in the future. Thus, this study focused on predicting the future water quality of the Adyar river under “business as usual” (BAU) and “suitable with measures” scenarios. The water evaluation and planning (WEAP) simulation tool was used for this study. Water quality simulation along a 19 km stretch of the Adyar River, from downstream of the Chembarambakkam to Adyar (Bay of Bengal) was carried out. In this analysis, clear indication of further deterioration of Adyar water quality by 2030 under the BAU scenario was evidenced. This would be rendering the river unsuitable for many aquatic species. Due to both climate change (i.e., increased temperature and precipitation) and population growth, the WEAP model results indicated that by 2030, biochemical oxygen demand (BOD) and Escherichia coli concentrations will increase by 26.7% and 8.3%, respectively. On the other hand, under the scenario with measures being taken, which assumes that “all wastewater generated locally will be collected and treated in WWTP with a capacity of 886 million liter per day (MLD),” the river water quality is expected to significantly improve by 2030. Specifically, the model results showed largely reduced concentrations of BOD and E. coli, respectively, to the tune of 74.2% and 98.4% compared to the BAU scenario. However, even under the scenario with measures being taken, water quality remains a concern, especially in the downstream area, when compared with class B (fishable surface water quality desirable by the national government). These results indicate that the current management policies and near future water resources management plan (i.e., the scenario including mitigating measures) are not adequate to check pollution levels to within the desirable limits. Thus, there is a need for transdisciplinary research into how the water quality can be further improved (e.g., through ecosystem restoration or river rehabilitation).
  • Ram Avtar, Kenichi Tsusaka, Srikantha Herath
    Land 8 (11) 2019/11/05 [Refereed][Not invited]
     
    Ifugao province of the Philippines has a traditional muyong forest system that supplies water and prevents soil erosion of the world-famous Ifugao rice terraces. The socio-political structure of Ifugao has been the key to the maintenance and communal use of land, as well as the muyong forest, without causing excessive damage to the land. Recently, the Ifugao is facing various challenges viz. deforestation, slash-and-burn, introduction of commercial rice, and climate change. The aim of the study is to qualitatively assess the forest management practices in the muyong forest and the way forward to implement the United Nations-Reducing Emissions from Deforestation and Forest Degradation (REDD+) mechanism. Community forestry can be an interesting option to reduce CO2 emissions from deforestation in Ifugao. This study qualitatively explores the societal problems in the area using focus group discussion (FGD) and key informant interviews (KII). The results show that the terracing lifestyle is at risk, due to mounting economic pressures from the domestic economy. Societal changes are altering the perceptions of the youth in terms of muyong sustainable management. They are threatening the sustainability of the terraces in the long-term because of outward migration and less value given to traditional practices. Furthermore, integration of commercial rice is changing the traditional agricultural system and placing less focus on forest maintenance. This study also discusses potential challenges and opportunities of REDD+ intervention and the role of REDD+ to foster sustainable muyong forest management as well as to find new innovative ways to maintain the Ifugao traditional system while coping with the modernization of the Ifugao economy.
  • Arpita Panda, Netrananda Sahu, Swadhin Behera, Takahiro Sayama, Limonlisa Sahu, Ram Avtar, R.B. Singh, Masafumi Yamada
    Climate 7 (11) 2019/10/28 [Refereed][Not invited]
     
    Most tropical regions in the world are vulnerable to climate variability, given their dependence on rain-fed agricultural production and limited adaptive capacity owing to socio-economic conditions. The Kalahandi, Bolangir, and Koraput districts of the south-western part of Odisha province of India experience an extreme sub-humid tropical climate. Based on the observed changes in the magnitude and distribution of rainfall and temperature, this study evaluates the potential impact of climate variation on agricultural yield and production in these districts. The study is conducted by taking into account meteorological data like rainfall and temperature from 1980 to 2017 and crop productivity data from 1980-81 to 2016-17. Additionally, climate variability indices like Monsoon Index, Oceanic Nino Index, and NINO-3 and NINO 3.4 are used. To analyse the data, various statistical techniques like correlation and multiple linear regression are used. The amount of monsoon rainfall is found to have a significant impact on crop productivity, compared to temperature, in the study area, and as a result the Monsoon Index has a determining impact on crop yield among various indices.
  • S. A. Suab, M. S. Syukur, R. Avtar, A. Korom
    The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W16 611 - 614 2019/10/01 
    Abstract. Malaysia currently is one of the biggest global producers and exporters of palm oil. The world’s expanding oil palm plantation areas contribute to climate change and in-return, climate is change also affecting the health of oil palms through a range of abiotic and biotic stresses. Current advancements in Precision Agriculture research using UAV gives an advantage to detect the health conditions of oil palm at early stages. Thus, remedial actions can be taken to prolong the life and increase oil palms productivity. This paper explores the use of UAV derived NDVI and CPA of young oil palm to detect the health conditions. NDVI of individual oil palm were extracted using ground masking layer from the dense point clouds and visual on-screen manual editing was done for removing trees other than oil palm in ENVI software. The classified individual crown NDVI were then processed to extract the mean NDVI also conversion to vector to obtain the individual crown outline. Extracted mean NDVI was classified into un-healthy and healthy trees while the CPA was classified into small, medium and big size classes. These classes of NDVI and CPA were analysed using GIS overlay method thus revealing the spatial patterns of individual oil palm trees and its health conditions. Overall, the majority of oil palm trees of the study area are healthy but average performing. However, few oil palm trees detected having health problems which has low NDVI and small CPA. This study demonstrates that biophysical parameters such as the CPA can be used to detect individual young oil palm trees health conditions and problems when combined with vegetation indices such as NDVI.
  • Mmasabata Molekoa, Ram Avtar, Pankaj Kumar, Huynh Minh, Tonni Kurniawan
    Water 11 (9) 1891 - 1891 2019/09/11 [Not refereed][Not invited]
     
    © 2019 by the authors. Despite being a finite resource, both the quality and quantity of groundwater are under tremendous pressure due to rapid global changes, viz. population growth, land-use/land-cover changes (LULC), and climate change. The 6th Sustainable Development Goal (SDG) aims to "Ensure availability and sustainable management of water and sanitation for all". One of the most significant dimensions of the SDG agenda is the emphasis on data and governance. However, the lack of good governance coupled with good observed data cannot ensure the achievement of SDG6. Therefore, this study strives to evaluate water quality status and hydrochemical processes governing it in the data-scarce Mokopane area of South Africa. Groundwater is the main source of fresh water supply for domestic usage, intensive agriculture, and mining activities in Mokopane. In this study, hydrogeochemical analysis of groundwater samples was employed to calculate the water quality index (WQI) and evaluate factors governing water quality evolution in the study area. Statistical and spatial analysis techniques were carried out to divide sampling sites into clusters and delineate principal factors responsible for determining water quality of the sampled groundwater. Results suggest that most of the physico-chemical parameters are within permissible limits for drinking water set by the World Health Organization (WHO), except for high fluoride in some samples. Na-HCO3 is the most abundant water type followed by Mg-HCO3, which indicates dominance of Na+, Mg2+, and HCO3±. Rock-water interaction is the prime factor responsible for fluoride enrichment in water. The alkaline nature of groundwater favors the release of exchangeable F- from minerals like muscovite. The WQI suggests that 80% of water samples fall into the good and excellent categories. Poor management of untreated domestic sewage and agricultural runoff is a main factor for the bad/very bad categories of water samples. As the area lacks any credible scientific/government work to report water quality and its management aspects, the findings of this study will definitely help both scientific communities and policy makers to do what is needed for sustainable water resource management in a timely manner.
  • Manish Ramaiah, Ram Avtar
    Urban Science 3 (3) 94 - 94 2019/08/25 [Refereed][Not invited]
     
    Urbanization offers several opportunities for the growth of economic, social, and technology sectors, offering benefits to society in terms of better living and healthcare facilities, as well as employment opportunities. However, some major downsides of urbanization are overcrowding and environmental degradation. In order to realize sustainable and environmentally friendly urbanization, there is an urgent need for comprehensive land use planning and of urban settlements by giving due consideration to create and sustain urban green spaces (UGS) such as parks, gardens, roadside vegetation, etc. UGS play a vital role in reducing air pollution, mitigating climate change, and providing various ecosystem services. UGS are being deteriorated substantially due to booming urbanization in developing countries such as India. This review is focused on highlighting the many challenges in creating and maintaining UGS in the Indian context. It is a compilation of available reports on problems linked with poor land use and/or planning of urban settlements. The challenges associated with the management and maintenance of UGS are described. The poor and irregular watering of many existing UGS is one of the major issues among several others requiring immediate attention to resolve the problem of deteriorating UGS in some cities of India. As the groundwater resources are rapidly depleting because of ever increasing water demand, UGS are being dispensed with poor and irregular watering resulting in their deterioration. A list of possible solutions and prospects of UGS in cities aiming to become smart cities soon are discussed in this review. Efficient wastewater treatment and a non-potable reuse system are possible solutions for better prospects of UGS, and therefore, optimism of better cities with low to null urban heat island effect.
  • Ram Avtar
    Resources 8 (3) 2079-9276 2019/08/19 [Not refereed][Not invited]
     
    Renewable energy has received noteworthy attention during the last few decades. This is partly due to the fact that fossil fuels are depleting and the need for energy is soaring because of the growing population of the world. This paper attempts to provide an idea of what is being done by researchers in remote sensing and geographical information system (GIS) field for exploring the renewable energy resources in order to get to a more sustainable future. Several studies related to renewable energy resources viz. geothermal energy, wind energy, hydropower, biomass, and solar energy, have been considered in this paper. The focus of this review paper is on exploring how remote sensing and GIS-based techniques have been beneficial in exploring optimal locations for renewable energy resources. Several case studies from different parts of the world which use such techniques in exploring renewable energy resource sites of different kinds have also been included in this paper. Though each of the remote sensing and GIS techniques used for exploration of renewable energy resources seems to efficiently sell itself in being the most effective among others, it is important to keep in mind that in actuality, a combination of different techniques is more efficient for the task. Throughout the paper, many issues relating to the use of remote sensing and GIS for renewable energy are examined from both current and future perspectives and potential solutions are suggested. The authors believe that the conclusions and recommendations drawn from the case studies and the literature reviewed in the present study will be valuable to renewable energy scientists and policymakers.
  • Huynh Vuong Thu Minh, Avtar Ram, Kumar Pankaj, Tran Dat Q, Tran Van Ty, Behera Hari Charan, Kurasaki Masaaki
    GEOSCIENCES 9 (8) 2019/08 [Refereed][Not invited]
     
    Along with rapid population growth in Vietnam, there is an increasing dependence on groundwater for various activities. An Giang province is known to be one of the agricultural intensification areas of The Vietnamese Mekong Delta (VMD). This study aimed to evaluate the spatiotemporal variation of groundwater quality for a period of ten years from 2009 to 2018 in An Giang. The weighted groundwater quality index (GWQI) was developed based on the fuzzy analytic hierarchy process (Fuzzy-AHP) for assigning weighted parameters. The results show that that shallow wells in the Northeast and Southeast regions of An Giang were mostly categorized under “bad water” quality with high arsenic (As) concentration over the years partly due to huge amounts of sediment deposition in monsoon season. Overall, the reason for the poor groundwater quality in An Giang was the combined effect of both natural and human activities. On the other hand, we detected high values of GWQI links with high As concentration in areas where people extract more groundwater for irrigation. Temporal variation of GWQI suggested that groundwater quality at eight wells has improved from 2009 to 2018 in the wet season as compared to the dry season. The reason behind the improvement of groundwater quality during wet season was the decrease in river discharge, which causes less deposition of suspended solids near the flood plains. Moreover, the filling of unused wells can reduce the movement of pollutants from unused wells to groundwater aquifers. Although there was not sufficient evidence to show the relationship between As and sediment concentration, the temporal reduction trend in river discharge and suspended solids was detected in An Giang. The understanding of groundwater quality can help policymakers protect and manage limited water resources in the long-term.
  • Ram Avtar, Saurabh Tripathi, Ashwani Kumar Aggarwal, Pankaj Kumar
    Resources 8 (3) 136 - 136 2019/07/30 [Not refereed][Not invited]
     
    © 2019 by the authors. Energy expansion and security in the current world scenario focuses on increasing the energy generation capacity and if possible, adopting cleaner and greener energy in that development process. However, too often this expansion and planning alters the landscape and human influence on its surroundings through a very complex mechanism. Resource extraction and land management activity involved in energy infrastructure development and human management of such development systems have long-term and sometimes unforeseen consequences. Although alternative energy sources are being explored, energy production is still highly dependent on fossil fuel, especially in most developing countries. Further, energy production can potentially affect land productivity, land cover, human migration, and other factors involved in running an energy production system, which presents a complex integration of these factors. Thus, land use, energy choices, infrastructure development and the population for which such facilities are being developed must be cognizant of each other, and the interactions between them need to be studied and understood closely. This study strives to analyze the implications of linkages between the energy industry, urbanization, and population and especially highlights processes that can be affected by their interaction. It is found that despite advancement in scientific tools, each of the three components, i.e., population growth, urbanization, and energy production, operates in silos, especially in developing countries, and that this complex issue of nexus is not dealt with in a comprehensive way.
  • Ali P. Yunus, Jie Dou, Xuan Song, Ram Avtar
    Sensors 19 (12) 1424-8220 2019/06/21 [Refereed][Not invited]
     
    The bathymetry of nearshore coastal environments and lakes is constantly reworking because of the change in the patterns of energy dispersal and related sediment transport pathways. Therefore, updated and accurate bathymetric models are a crucial component in providing necessary information for scientific, managerial, and geographical studies. Recent advances in satellite technology revolutionized the acquisition of bathymetric profiles, offering new vistas in mapping. This contribution analyzed the suitability of Sentinel-2 and Landsat-8 images for bathymetric mapping of coastal and lake environments. The bathymetric algorithm was developed using an empirical approach and a random forest (RF) model based on the available high-resolution LiDAR bathymetric data for Mobile Bay, Tampa Bay, and Lake Huron regions obtained from the National Oceanic and Atmospheric Administration (NOAA) National Geophysical Data Center (NGDC). Our results demonstrate that the satellite-derived bathymetry is efficient for retrieving depths up to 10 m for coastal regions and up to 30 m for the lake environment. While using the empirical approach, the root-mean-square error (RMSE) varied between 1.99 m and 4.74 m for the three regions. The RF model, on the other hand, provided an improved bathymetric model with RMSE between 1.13 m and 1.95 m. The comparative assessment suggests that Sentinel-2 has a slight edge over Landsat-8 images while employing the empirical approach. On the other hand, the RF model shows that Landsat-8 retrieves a better bathymetric model than Sentinel-2. Our work demonstrated that the freely available Sentinel-2 and Landsat-8 imageries proved to be reliable data for acquiring updated bathymetric information for large areas in a short period.
  • Akinola Adesuji Komolafe, Srikantha Herath, Ram Avtar, Jean Francois Vuillaume
    Environment Systems and Decisions 39 (2) 229 - 246 2194-5403 2019/06/15 [Not refereed][Not invited]
     
    © 2018, Springer Science+Business Media, LLC, part of Springer Nature. The use of different approaches in the development of flood damage models in various countries is expected to affect flood damage modelling at a regional or global scale. Since these models are often used as tools for disaster management and decision making, it is very needful to understand the comparative similarity and differences in countries’ loss models; this can help in the overall integration for developing regional risk models and cross-country risk assessment. In this study, empirically generated generalised loss models in three Asian countries (Sri Lanka, Thailand and Japan) were compared and applied to estimate potential flood damages in two different urban river basins. For each case study, each model was normalised using cost prices and floor areas (as applied to each country) and were integrated within the Geographic Information Systems (GIS) to estimate damages for the flood events. Using the mean vulnerability index of corresponding building types for the selected countries, a single model for regional flood risk assessment was created. However, the study showed that there are variations in the vulnerability and the potential flood damage estimates of similar global building types from the three countries, despite being developed by the same approach. These are attributed to the country’s specific conditions such as building regulations and codes, GDP per capita, cost price of building materials. Our results suggest that the average vulnerability index from the countries however reduced potential errors in the estimates. Moreover, it is proposed that the average regional vulnerability model derived with empirical data inputs from all the countries for regional risk assessment and cross-country comparison. Therefore, it can predict near accurate potential flood damages, which can serve as measures for regional flood disaster risk management plans.
  • Saraswat Chitresh, Kumar Pankaj, Dasgupta Rajarshi, Avtar Ram, Bhalani Prashant
    APPLIED WATER SCIENCE 9 (4) 2190-5487 2019/06 [Refereed][Not invited]
  • Huynh Vuong Thu Minh, Masaaki Kurasaki, Tran Van Ty, Dat Quoc Tran, Kieu Ngoc Le, Ram Avtar, Md. Mostafizur Rahman, Mitsuru Osaki
    Water 11 (5) 1010 - 1010 2073-4441 2019/05/14 [Refereed][Not invited]
     
    The Vietnamese Mekong Delta (VMD) is one of the largest rice-growing areas in Vietnam, and exports a huge amount of rice products to destinations around the world. Multi-dike protection systems have been built to prevent flooding, and have supported agricultural intensification since the early 1990s. Semi-dike and full-dike systems have been used to grow double and triple rice, respectively. Only a small number of studies have been conducted to evaluate the water quality in the VMD. This study aimed to analyze the spatiotemporal variation of water quality inside the dike-protected area. Surface water samples were collected in the dry and wet seasons at 35 locations. We used multivariate statistical analyses to examine various water quality parameters. The mean concentrations of COD, NH4+, NO3-, PO43-, EC, and turbidity were significantly higher in water samples inside the full-dike system than in water samples from outside the full-dike systems and inside the semi-dike systems in both seasons. High concentrations of PO43- were detected in most of the primary canals along which residential, tourist areas and local markets were settled. However, NO3- was mainly found to be higher in secondary canals, where chemical fertilizers were used for rice intensification inside the dike system. Water control infrastructures are useful for preventing flood hazards. However, this has an adverse effect on maintaining water quality in the study area.
  • Huynh Vuong Thu Minh, Ram Avtar, Geetha Mohan, Prakhar Misra, Masaaki Kurasaki
    ISPRS International Journal of Geo-Information 8 (5) 211 - 211 2019/05/07 [Refereed][Not invited]
     
    Cropping intensity is one of the most important decisions made independently by farmers in Vietnam. It is a crucial variable of various economic and process-based models. Rice is grown under irrigated triple- and double-rice cropping systems and a rainfed single-rice cropping system in the Vietnamese Mekong Delta (VMD). These rice cropping systems are adopted according to the geographical location and water infrastructure. However, little work has been done to map triple-cropping of rice using Sentinel-1 along with the effects of water infrastructure on the rice cropping intensity decision. This study is focused on monitoring rice cropping patterns in the An Giang province of the VMD from March 2017 to March 2018. The fieldwork was carried out on the dates close to the Sentinel-1A acquisition. The results of dual-polarized (VV and VH) Sentinel-1A data show a strong correlation with the spatial patterns of various rice growth stages and their association with the water infrastructure. The VH backscatter (σ°) is strongly correlated with the three rice growth stages, especially the reproductive stage when the backscatter is less affected by soil moisture and water in the rice fields. In all three cropping patterns, σ°VV and σ°VH show the highest value in the maturity stage, often appearing 10 to 12 days before the harvesting of the rice. A rice cropping pattern map was generated using the Support Vector Machine (SVM) classification of Sentinel-1A data. The overall accuracy of the classification was 80.7% with a 0.78 Kappa coefficient. Therefore, Sentinel-1A can be used to understand rice phenological changes as well as rice cropping systems using radar backscattering.
  • Komolafe Akinola Adesuji, Herath Srikantha, Avtar Ram
    GEOMATICS NATURAL HAZARDS & RISK 10 (1) 633 - 650 1947-5705 2019/01/19 [Refereed][Not invited]
     
    The continuous increase in damages to flood disasters globally has informed the need to assess vulnerability of built-up exposures for future flood risk reduction. The aim of this paper is to understand the contributions of some important variables in flood damage processes and develop loss functions for global building types, for the estimation of flood economic damages in Chao Phraya river basin, Thailand. We obtained empirical damage data (118 samples) through questionnaire survey in the study area for analysis. Using multiple linear regressions analysis, we generated loss functions for the aggregated residential building incorporating multiple damage factors. Further, disaggregated vulnerability curves (as a function of water depth) were established using logarithm function for three global building types in the study area. Results showed that, under flood condition in the study area, water depths and building age are very important damage factors, other variables are also emphasized. The loss models show maximum predicted vulnerability indices of 0.36, 0.30 and 0.10 for wooden, concrete frame and unreinforced masonry, and reinforced concrete moment frame, respectively. These functions can be used for modeling flood damage, for future disaster risk reduction and for risk comparison across countries.
  • Avtar, R., Tripathi, S., Aggarwal, A.K.
    Land 8 (8) 124 - 124 2019 [Refereed][Not invited]
     
    The demand for energy has been growing worldwide, especially in India partly due to the rapid population growth and urbanization of the country. To meet the ever-increasing energy requirement while maintaining an ecological balance is a challenging task. However, the energy industry-induced effect on population and urbanization has not been addressed before. Therefore, this study investigates the linkages between energy, population, and urbanization. The study also aims to find the quantifiable indicators for the population growth and rate of urbanization due to the expanding energy industry. The integrated framework uses a multi-temporal Landsat data to analyze the urbanization pattern, a census data for changes in population growth, night time light (NTL) data as an indicator for economic development and energy production and consumption data for energy index. Multi-attribute model is used to calculate a unified metric, termed as the energy-population-urbanization (EPU) nexus index. The proposed approach is demonstrated in the National Thermal Power Corporation (NTPC) Dadri power plant located in Uttar Pradesh, India. Landsat and NTL data clearly shows the urbanization pattern, economic development, and electrification in the study area. A comparative analysis based on various multi-attribute decision model assessment techniques suggests that the average value of EPU nexus index is 0.529, which significantly large compared to other studies and require special attention by policymakers because large EPU index indicates stronger correlation among energy, population, and urbanization. The authors believe that it would help the policymakers in planning and development of future energy projects, policies, and long-term strategies as India is expanding its energy industry.
  • Misra Prakhar, Avtar Ram, Takeuchi Wataru
    REMOTE SENSING 10 (12) 2072-4292 2018/12 [Refereed][Not invited]
     
    Vertical urban growth in the form of urban volume or building height is increasingly being seen as a significant indicator and constituent of the urban environment. Although high-resolution digital surface models can provide valuable information, various places lack access to such resources. The objective of this study is to explore the feasibility of using open digital surface models (DSMs), such as the AW3D30, ASTER, and SRTM datasets, for extracting digital building height models (DBHs) and comparing their accuracy. A multidirectional processing and slope-dependent filtering approach for DBH extraction was used. Yangon was chosen as the study location since it represents a rapidly developing Asian city where urban changes can be observed during the acquisition period of the aforementioned open DSM datasets (2001-2011). The effect of resolution degradation on the accuracy of the coarse AW3D30 DBH with respect to the high-resolution AW3D5 DBH was also examined. It is concluded that AW3D30 is the most suitable open DSM for DBH generation and for observing buildings taller than 9 m. Furthermore, the AW3D30 DBH, ASTER DBH, and SRTM DBH are suitable for observing vertical changes in urban structures.
  • Lin Yanyan, Kurniawan Tonni Agustiono, Zhu Mengting, Ouyang Tong, Avtar Ram, Othman Moh, Hafiz Dzarfan, Mohammad Balsam T, Albadarin Ahmad B
    JOURNAL OF ENVIRONMENTAL MANAGEMENT 226 365 - 376 0301-4797 2018/11/15 [Refereed][Not invited]
     
    Acetaminophen (Ace) is a trace pollutant widely found in sewage treatment plant (STP) wastewater. We test the feasibility of coconut shell waste, a low cost adsorbent from coconut industry, for removing Ace from synthetic solution in a fixed-bed column adsorption. To enhance its performance, the surface of granular activated carbon (GAC) was pre-treated with NaOH, HNO3, ozone, and/or chitosan respectively. The results show that the chemical modification of the GAC's surface with various chemicals has enhanced its Ace removal during the column operations. Among the modified adsorbents, the ozone-treated GAC stands out for the highest Ace adsorption capacity (38.2 mg/g) under the following conditions: 40 mg/L of Ace concentration, 2 mL/min of flow rate, 45 cm of bed depth. Both the Thomas and the Yoon-Nelson models are applicable to simulate the experimental results of the column operations with their adsorption capacities: ozone-treated GAC (20.88 mg/g) > chitosan-coated GAC (16.67 mg/g) > HNO3-treated GAC (11.09 mg/g) > NaOH-treated GAC (7.57 mg/g) > as-received GAC (2.84 mg/g). This suggests that the ozone-treated GAC is promising and suitable for Ace removal in a fixed-bed reactor.
  • Shoyama K, Braimoh AK, Avtar R, Saito O
    Environmental management 62 (5) 892 - 905 0364-152X 2018/11 [Refereed][Not invited]
     
    Cropland expansion to meet the growing demand for food and fuel is a driving factor in forest degradation. Over the next few decades, increases in the area of agricultural land are expected to be concentrated in sub-Saharan Africa, which still has large tracts of unexploited land suitable for agricultural production. We analyzed land-cover change in northern Ghana between 1984 and 2015 and compared it with background social factors associated with land change. Maps from three points in time were analyzed to identify the impact of cropland expansion on the distribution of natural vegetation. Three-level intensity analysis revealed that the overall rate of change for the 31-year period was less than that of the first time interval (1984–1999); however, the overall impact on natural vegetation was substantial, and grassland in particular was reduced to a very small proportion of the area over the period. Cropland replaced only grassland during the first time interval, but also began to replace open woodland during the second interval (1999–2015). The in-depth assessment revealed that cropland expansion continued at a steady rate, but the impact on natural vegetation was not uniform across vegetation types; grassland was more vulnerable than woodland, and woodland became increasingly targeted with continual expansion of the agricultural frontier as population increased. Further validation of the socio-cultural factors associated with the observed transitions will help to identify the explicit implications and assist in developing strategies to minimize the impacts of land-use change on regional livelihoods.
  • P. Kumar, R. Prasad, D. K. Gupta, V. N. Mishra, A. K. Vishwakarma, V. P. Yadav, R. Bala, A. Choudhary, R. Avtar
    Geocarto International 33 (9) 942 - 956 1010-6049 2018/09/02 [Not refereed][Not invited]
     
    In the present study, Sentinel-1A Synthetic Aperture Radar analysis of time series data at C-band was carried out to estimate the winter wheat crop growth parameters. Five different date images were acquired during January 2015–April 2015 at different growth stages from tillering to ripening in Varanasi district, India. The winter wheat crop parameters, i.e. leaf area index, vegetation water content (VWC), fresh biomass (FB), dry biomass (DB) and plant height (PH) were estimated using random forest regression (RFR), support vector regression (SVR), artificial neural network regression (ANNR) and linear regression (LR) algorithms. The Ground Range Detected products of Interferometric Wide (IW) Swath were used at VV polarization. The three different subplots of 1 m2 area were taken for the measurement of crop parameters at every growth stage. In total, 73 samples were taken as the training data-sets and 39 samples were taken as testing data-sets. The highest sensitivity (adj. R2= 0.95579) of backscattering with VWC was found using RFR algorithm, whereas the lowest sensitivity (adj. R2= 0.66201) was found for the PH using LR algorithm. Overall results indicate more accurate estimation of winter wheat parameters by the RFR algorithm followed by SVR, ANNR and LR algorithms.
  • Akiyama Tomohiro, Kubota Jumpei, Fujita Koji, Tsujimura Maki, Nakawo Masayoshi, Avtar Ram, Kharrazi Ali
    ENVIRONMENTS 5 (5) 1 - 15 2076-3298 2018/05 [Refereed][Not invited]
     
    The groundwater recharge mechanism in the hyper-arid Gobi Desert of Northwestern China was analyzed using water balance and tracer-based approaches. Investigations of evaporation, soil water content, and their relationships with individual rainfall events were conducted from April to August of 2004. Water sampling of rainwater, groundwater, and surface water was also conducted. During this period, 10 precipitation events with a total amount of 41.5 mm, including a maximum of 28.9 mm, were observed. Evaporation during the period was estimated to be 33.1 mm. Only the soil water, which was derived from the heaviest precipitation, remained in the vadose zone. This is because a dry surface layer, which was formed several days after the heaviest precipitation event, prevented evaporation. Prior to that, the heaviest precipitation rapidly infiltrated without being affected by evaporation. This is corroborated by the isotopic evidence that both the heaviest precipitation and the groundwater retained no trace of significant kinetic evaporation. Estimated δ-values of the remaining soil water based on isotopic fractionation and its mass balance theories also demonstrated no trace of kinetic fractionation in the infiltration process. Moreover, stable isotopic compositions of the heaviest precipitation and the groundwater were very similar. Therefore, we concluded that the high-intensity precipitation, which rapidly infiltrated without any trace of evaporation, was the main source of the groundwater.
  • Akinola Adesuji Komolafe, Srikantha Herath, Ram Avtar
    Natural Hazards Review 19 (2) 05018001 - 05018001 1527-6988 2018/05/01 [Refereed][Not invited]
     
    Frequencies of extreme precipitation are likely to increase under changing climate, which may result in more damage to exposed properties in the future. This study presents a methodological framework for estimating potential economic damages to flood hazards based on current and future climatic information using loss functions. Loss functions for Sri Lanka's residential structure categories were derived from empirical data through a questionnaire survey in Kelani River basin, Sri Lanka. Flood prediction was done using a bias-corrected 5-year time series of the Japanese Meteorological Research Institute (MRI)'s Regional Climate Model (RCM) precipitation data for current (1985-1989) and near future climate (2028-2032), and a hypothetical future climate projection using a 10% increase in current high rainfall events. The authors simulated extreme river discharges and inundation depths for potential current and future flood events using similar hydrologic element response (SHER) and geographic information system (GIS) grid-based models, respectively. Simulated extreme flood hazards were integrated with the established loss functions and exposures to simulate the potential damages using a raster-based spatial model. Results revealed a little reduction in the MRI projected near future discharges and flood damages, but an increase in the frequency of flood events compared to the current projection. However, the hypothetical projection showed a 10.2% increase in potential damages in the future climate compared with the current climate. Future adaptation measures in the river basin are suggested.
  • Akinola Adesuji Komolafe, Srikantha Herath, Ram Avtar
    Applied Geomatics 10 (1) 13 - 30 1866-928X 2018/03/01 [Refereed][Not invited]
     
    Assessment of infrastructural vulnerability to natural hazards, and subsequent economic loss, can make important contributions to future disaster risk minimization. The recent endeavor is to ascertain and evaluate risk globally, which can provide a framework to identify unique regional vulnerabilities, the mobilization of international investments, and cross-country risk comparison. This would require a concerted effort for the detailed classification of building exposures and vulnerability models. This study presents the design and efficacy of flood-vulnerability models for structural building types. The study uses an empirical approach, with data gathered from survey questionnaire, for direct estimation of flood damages in the Kelani River basin in Sri Lanka. Survey questionnaires were administered in the flood-prone areas of the basin, and depth-damage functions were established for four (4) structural building types that were identified based on the relationship between inundation depths and flood damage ratio. Event-based flood hazards were simulated using the Flo-2D model. Building exposures and densities were derived from remote sensing data, using integrated thematic land cover feature indices and supervised image classification. A modified mathematical loss model was employed to simulate flood damages to each building category for a disastrous flood event in the Kelani River basin. Simulated damages and post-flood survey showed reasonable comparativeness. The models can be employed for loss estimation of future damages and risk-reduction planning for flood disaster in Sri Lanka.
  • A. A. Komolafe, S. Herath, R. Avtar
    Journal of Flood Risk Management 11 S370 - S381 1753-318X 2018/01/01 [Not refereed][Not invited]
     
    Flood damage estimation is an important element in flood risk assessment it is useful for mobilizing investment and developing policies for flood loss prevention since most flood risk reduction measures are based on cost benefit analysis. From a global or regional view-point, it is necessary to understand relative impacts on economies of countries to mobilize international support and develop response strategies. This requires a unified approach to flood damage estimation across countries and over large spatial extents. Spatial resolutions used in the assessment have a direct impact on the estimation of potential flood heights as well as representation of property exposure and, consequently, the flood damage estimates. Using Ichinomiya river basin, Japan, as a case study, the sensitivity of spatial scale in estimating potential flood economic damages is investigated and approaches are delineated to reduce errors arising from coarse spatial resolutions. [Correction added on 5 May 2016, after first online publication: in the first sentence of the abstract the word “is” has been inserted between “it” and “useful”.].
  • Tomohiro Akiyama, Ali Kharrazi, Jia Li, Ram Avtar
    Environmental Monitoring and Assessment 190 (1) 9  1573-2959 2018/01/01 [Refereed][Not invited]
     
    Water resources are essential for agricultural production in the grain-producing region of China, and water shortage could significantly affect the production and international trade of agricultural products. China is placing effort in new policies to effectively respond to changes in water resources due to changes in land use/land cover as well as climatic variations. This research investigates the changes in land, water, and the awareness of farmer vis-à-vis the implementation of water-saving policies in Zhangye City, an experimental site for pilot programs of water resources management in China. This research indicates that the water saved through water-saving programs and changes in cropping structure (2.2 × 108 m3 a−1) is perhaps lower than the newly increased water withdrawal through corporate-led land reclamation (3.7 × 108 m3 a−1). Most critically, the groundwater withdrawal has increased. In addition, our survey suggests that local government is facing a dilemma of water conservation and agricultural development. Therefore, the enforcement of the ban on farmland reclamation and irrigation water quotas in our study area is revealed to be relatively loose. In this vein, the engagement of local stakeholders in water governance is essential for the future sustainable management of water resources.
  • Kumar Pankaj, Saraswat Chitresh, Mishra Binaya Kumar, Avtar Ram, Patel Hiral, Patel Asha, Sharma Tejal, Patel Roshni
    APPLIED WATER SCIENCE 7 (5) 2597 - 2606 2190-5487 2017/09 [Refereed][Not invited]
  • Pankaj Kumar, Maki Tsujimura, Chitresh Saraswat, Prashant K. Srivastava, Manish Kumar, Ram Avtar
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES INDIA SECTION A-PHYSICAL SCIENCES 87 (3) 423 - 432 0369-8203 2017/09 [Refereed][Not invited]
     
    The work assessed effect of diurnal tidal fluctuation on transient groundwater dynamics with special focus on trace metal mobilization using tide-aquifer interaction technique in the Saijo plain, Japan. Fluctuation of trace metal concentration in groundwater during intertidal phase obtained through geochemical analysis is validated with numerical simulation using two different codes (PHREEQC and SEEP/W) to observe saturation index for different minerals in aquifers and dynamics of submarine groundwater discharge (SGD) respectively. Result for saturation index shows that most of the samples are strongly undersaturated with respect to FeS, goethite, siderite and scorodite, unlike pyrite where it approaches towards saturation. Also during lower low tide situation, water samples relatively getting more undersaturated with pyrite suggesting it as a source for dissolved iron. For numerical simulation, problem domain consists of 368 elements and 3 layers, is an anisotropic unconfined aquifer with horizontal hydraulic conductivities (K-X) ranging from 0.00001 to 0.01 m/P. Coastal side of the domain considered as variable head boundary keeping different diurnal tidal amplitude into account. Simulation result shows that during low tide situation, value of SGD is maximum i.e. 2.1644e-005 and 3.3704e-005 m(3)/s for lower boundary towards sea at 2 and 4 m below mean sea level respectively. It suggests that tidal height affects the amount and position of SGD to play a positive role for trace metal mobilization through oxidation-reduction process. Strong relation between diurnal fluctuations of the simulated results (SGD) versus observed result oxidation-reduction potential firmly supports and validates the results from chemical analysis.
  • Hasi Bagan, Ram Avtar, Hajime Seya, Huade Guan
    MATHEMATICAL PROBLEMS IN ENGINEERING 2017 1 - 3 1024-123X 2017 [Refereed][Not invited]
  • Kharrazi Ali, Kumar Pankaj, Saraswat Chitresh, Avtar Ram, Mishra Binaya Kumar
    JOURNAL OF CLIMATE CHANGE 3 (2) 81 - 94 2395-7611 2017 [Refereed][Not invited]
  • Pankaj Kumar, Srikantha Herath, Ram Avtar, Kazuhiko Takeuchi
    Sustainable Water Resources Management 2 (4) 419 - 430 2363-5037 2016/12/01 
    Groundwater is a vital natural capital for the consistent and economic provision of potable water supply for both rural and urban environments. There is now a strong consensus that climate change poses a fundamental challenge to the well-being of all countries, with potential of being the harshest on countries already suffering from water scarcity. Dry zone of Killinochi basin in Northern Sri Lanka, which was devastated by civil war for last 25 years, is again being revitalized by human settlement and urbanization in last couple of years. However, the decreasing trend in the rainfall regime of the dry zones and the increase in population size (temporary inflow) and, hence, the demand for water for irrigation and other livelihood requirements, calls for a sustainable exploitation of the groundwater resources in the region. The development of a reasonable model for groundwater potential is need for the present time. This work strives to generate groundwater potential zonation map using integrated use of remote sensing and geographic information system (GIS) for Killinochi area, Northern Sri Lanka. Five different themes of information, such as geomorphology, geology, soil type (extracted from existing topo sheet); slope [generated from shuttle radar topography mission (SRTM) digital elevation model (DEM)]; and land use/land cover (extracted from digital processing of AVNIR satellite data) were integrated with weighted overlay in GIS to generate groundwater potential zonation map of the area. The final map of the area was demarcated by four different zones of groundwater prospects, viz., good (5.32 % of the area), moderate (61.90 % of the area) poor (26.61 % of the area), and very poor (6.17 % of area). The hydrogeomorphological units, such as alluvial plain, low slope area, and land occupied by forest, are prospective zones for groundwater occurrence in the study area.
  • Ali P. Yunus, Ram Avtar, Steven Kraines, Masumi Yamamuro, Fredrik Lindberg, C. S. B. Grimmond
    REMOTE SENSING 8 (5) 2072-4292 2016/05 [Refereed][Not invited]
     
    Sea-level rise (SLR) from global warming may have severe consequences for coastal cities, particularly when combined with predicted increases in the strength of tidal surges. Predicting the regional impact of SLR flooding is strongly dependent on the modelling approach and accuracy of topographic data. Here, the areas under risk of sea water flooding for London boroughs were quantified based on the projected SLR scenarios reported in Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5) and UK climatic projections 2009 (UKCP09) using a tidally-adjusted bathtub modelling approach. Medium-to very high-resolution digital elevation models (DEMs) are used to evaluate inundation extents as well as uncertainties. Depending on the SLR scenario and DEMs used, it is estimated that 3%-8% of the area of Greater London could be inundated by 2100. The boroughs with the largest areas at risk of flooding are Newham, Southwark, and Greenwich. The differences in inundation areas estimated from a digital terrain model and a digital surface model are much greater than the root mean square error differences observed between the two data types, which may be attributed to processing levels. Flood models from SRTM data underestimate the inundation extent, so their results may not be reliable for constructing flood risk maps. This analysis provides a broad-scale estimate of the potential consequences of SLR and uncertainties in the DEM-based bathtub type flood inundation modelling for London boroughs.
  • Pankaj Kumar, Alok Kumar, Chander Kumar Singh, Chitresh Saraswat, Ram Avtar, A. L. Ramanathan, Srikantha Herath
    EXPOSURE AND HEALTH 8 (1) 19 - 30 2451-9766 2016/03 [Refereed][Not invited]
     
    Intense agricultural and mining/industrial activities make groundwater quality vulnerable to contaminants. This study conducted in one of the mining areas of Panna district evaluated the factors influencing the groundwater hydrogeochemistry using water quality parameters and multi-isotopic approach considering the fact that groundwater is the only major source of drinking water. Forty-five water samples comprising both shallow and deep aquifers were collected and analyzed for major ions, delta O-18, and delta D. The geochemical data were used to characterize and classify water samples based on a multitude of ion plots and diagrams. The groundwater in the region is found to be contaminated with fluoride and nitrate. The sources for fluoride are mostly geogenic in nature. The alkaline nature of groundwater triggers replacement of the exchangeable fluoride from minerals like biotite/muscovite and results in its enrichment. In addition, it is contributed through leaching of fluorides from granitic rocks, abundantly present in the study area. The weathering of these fluoride-bearing minerals releases fluoride into the groundwater. On the other hand, nitrate enrichment is mainly attributed to leaching from untreated sewerage system and agricultural runoff containing nutrients from excess use of fertilizers. The stable isotopic composition for most of the collected samples was found to be near the local meteoric water line (LMWL), i.e., origin of ground water is meteoric in principle; however, the point away from the LMWL might favor exchange with rock minerals and evaporation processes. This study sets an important background for decision makers to take the suitable countermeasures from the public health perspective for sustainable water resources management.
  • Sohail Ahmad, Ram Avtar, Mahendra Sethi, Akhilesh Surjan
    CITIES 50 111 - 118 0264-2751 2016/02 [Refereed][Not invited]
     
    Growing urbanization and recent Mass Rapid Transit System (MRTS) play an important role in land cover change in Indian cities. However, understanding about direction and magnitude of this change is limited, especially in reference to MATS introduction, which is required to assess sustainable urban futures. Thus, this study attempts to assess pattern of land cover change, paying special attention to the development of MRTS (both metro lines and stations) in the National Capital Territory of Delhi. Land covers are classified using Landsat images from year 2001 and 2011. In order to measure transformations in developed areas, this study employs maximum likelihood supervised classification and performs buffer analyses along the metro lines and stations. The results reveal that growth of built-up area is higher in peripheral districts, whereas relatively low along the MATS. This study indicates that ongoing development process needs corrective measures, such as increasing built-up areas across the metro stations and lines, and planned provisioning of physical and social infrastructure in peripheral areas to induce sustainable urban development. To implement these spatial interventions, robust implementation strategies are needed. (C) 2015 Elsevier Ltd. All rights reserved.
  • Ram Avtar, Pankaj Kumar, Akiko Oono, Chitresh Saraswat, Singay Dorji, Zarchi Hlaing
    Geocarto International 32 (8) 874 - 885 1010-6049 2016 
    The application of remote sensing (RS) techniques to monitor ecosystem services has increased in recent years. Nevertheless, the potential application of RS to monitor some of ecosystem services is still challenging. The paper reviews the applications of RS to monitor ecosystem services of forests, mangroves and urban areas. Satellite data provide substantial information about dynamics of environmental changes over time from local to global scale. These information are useful data sources for the people who are involved in the on-going evaluation and decision-making process to manage ecosystem. Many recent research papers on the topic were reviewed to find new applications and limitations of RS for monitoring ecosystem services. Advanced RS techniques have high potential to monitor ecosystem services with the advancement of sensors ranging from aerial photography to high and medium resolution optical RS and from hyperspectral RS to microwave RS.
  • Ali Kharrazi, Steven Kraines, Elena Rovenskaya, Ram Avtar, Shuichi Iwata, Masaru Yarime
    JOURNAL OF INDUSTRIAL ECOLOGY 19 (5) 805 - 813 1088-1980 2015/10 [Refereed][Not invited]
     
    Commodity trade networks exhibit certain patterns in the configuration of material flows that are similar to natural ecological networks. This article develops and explores an ecological information-based approach to examine the ecology of commodity trade networks. We demonstrate that commodity trade networks show a pattern of commonality when viewed through the introduced ecological information-based metrics. Specifically, we show how the network metrics of effective connectivity and effective number of roles can convey boundaries where commodity trade networks are robust. Further, the temporal trends of these metrics suggest the existence of multiple basins of attractions and provide clues on the dynamics of resilience of these networks over time.
  • Kumar Nirmal, Kumar Pankaj, Basil George, Kumar Rita N, Kharrazi Ali, Avtar Ram
    APPLIED WATER SCIENCE 5 (3) 261 - 270 2190-5487 2015/09 [Refereed][Not invited]
     
    This study is an effort to trace the spatiotemporal variation in water at Narmada estuarine region through solute concentration. A total of 72 water samples were collected and analyzed from three sampling points along with in situ measurement of tidal height at monthly basis for 2 years. Result shows that spatiotemporal variation of water quality occurs because of the following main mechanisms, i.e., carbonate weathering, dilution and seawater-freshwater mixing. Firstly, points situated toward inland showing the simple dilution effect on receiving high amount of monsoonal precipitation. Secondly, tidal fluctuation pattern has a strong influence on the water quality taken from the point located in near proximity to the coast. Finally, it can be concluded that water quality shows a different response, in accordance with the different tidal phase and the distance from the sea.
  • Saraswat Chitresh, Kumar Pankaj, Kem Dinara, Avtar Ram, Ramanathan A. L
    JOURNAL OF CLIMATE CHANGE 1 (1-2) 119 - 128 2395-7611 2015 [Refereed][Not invited]
  • Ram Avtar, Ali P. Yunus, Steven Kraines, Masumi Yamamuro
    PHYSICS AND CHEMISTRY OF THE EARTH 83-84 166 - 177 1474-7065 2015 [Refereed][Not invited]
     
    This study is focused on the evaluation of a Digital Elevation Model (DEM) for Tokyo, Japan from data collected by the recently launched TerraSAR add-on for Digital Elevation Measurements (TanDEM-X), satellite of the German Aerospace Center (DLR). The aim of the TanDEM-X mission is to use Interferometric SAR techniques to generate a consistent high resolution global DEM dataset. In order to generate an accurate global DEM using TanDEM-X data, it is important to evaluate the accuracy at different sites around the world. Here, we report our efforts to generate a high-resolution DEM of the Tokyo metropolitan region using TanDEM-X data. We also compare the TanDEM-X DEM with other existing DEMs for the Tokyo region. Statistical techniques were used to calculate the elevation differences between the TanDEM-X DEM and the reference data. Two high-resolution LiDAR DEMs are used as independent reference data. The vertical accuracy of the TanDEM-X DEM evaluated using the Root Mean Square Error (RMSE) is considerably higher than the existing global digital elevation models. However, the local area DEM generated by Geospatial Information Authority of Japan (GSI DEM) showed the highest accuracy among all non-LiDAR DEM's. The vertical accuracy in terms of RMSE estimated using the 2 m LiDAR as reference is 3.20 m for TanDEM-X, 2.44 m for the GSI, 7.00 m for SRTM DEM and 10.24 m for ASTER-GDEM. We also compared the accuracy of TanDEM-X with the other DEMs for different types of land cover classes. The results show that the absolute elevation error of TanDEM-X is higher for urban and vegetated areas, likewise to those observed for other global DEM's. This is probably because the radar signals used by TanDEM-X tend to measure the first reflective surface that is encountered, which is often the top of the buildings or canopy. Hence, the TanDEM-X based DEM is more akin to a Digital Surface Model (DSM). (C) 2015 Elsevier Ltd. All rights reserved.
  • Ram Avtar, Srikantha Herath, Osamu Saito, Weena Gera, Gulab Singh, Binaya Mishra, Kazuhiko Takeuchi
    Environment, Development and Sustainability 16 (5) 995 - 1011 1573-2975 2014/09/01 [Not refereed][Not invited]
     
    Sri Lanka being an agrarian country, the role of water is important for agricultural production. In Sri Lanka, various tank cascade systems, earthen dams and distribution canals have been accepted as few of the most complex ancient traditional water systems of the world. Rainfall, surface water, groundwater and runoff are linked with each other, they have close interactions to land cover classes such as forests and agriculture. The monitoring of vegetation conditions can show subsurface manifestations of groundwater. In this study, an effort to understand the role of traditional water reservoirs and groundwater recharge was made using remote sensing techniques. We have analyzed various vegetation indices such as Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI-2), Soil-Adjusted Vegetation Index (SAVI), tasselled cap transformation analysis (TCA brightness, greenness and wetness) and their relations with the existence of soil, vegetation and water. Result shows that EVI, SAVI, and TCA-based Greenness Index indicates good relationship with the vegetation conditions as compared to other indices. Therefore, these indices could play a crucial role in depicting the interaction between soil, vegetation, and water. However, multi-temporal observations can provide significant results about these interactions more accurately.
  • LN Gupta, Ram Avtar, Ameerjeet Singh, Pankaj Kumar, Emmanuel Mutisya, Geetha Mohan, GS Gupta
    International Journal of Life Sciences 8 (3) 2091-0525 2014/05
  • Pankaj Kumar, Ram Avtar, Alok Kumar, Chander Kumar Singh, Parijat Tripathi, G. Senthil Kumar, A. L. Ramanathan
    2014 
    A combined study of the geophysical survey and hydro-geochemistry in the Quaternary alluvial aquifers of Bhagalpur district from Bihar state in central Gangetic plain of India was carried out with the objective of identifying the geochemical processes and their relation with lithological profile. Results of resistivity survey validated with borehole lithology gave us a clear picture of the geological signature of the aquifers, which support the reducing nature of the aquifer where concentration of arsenic was high. Reducing nature of the aquifer environment was shown by water samples having relatively negative Eh value. From XRD study of the soil samples, it was found that goethite, dolomite, calcite, quartz and feldspar are the major minerals for most of the samples. Output of this work concludes that resistivity survey is an economically feasible tool which can be successfully used to target arsenic-safe aquifers on wide scale.
  • Ram Avtar, Rikie Suzuki, Haruo Sawada
    PLOS ONE 9 (1) e86121  1932-6203 2014/01 [Refereed][Not invited]
     
    Forests play a vital role in terrestrial carbon cycling; therefore, monitoring forest biomass at local to global scales has become a challenging issue in the context of climate change. In this study, we investigated the backscattering properties of Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data in cashew and rubber plantation areas of Cambodia. The PALSAR backscattering coefficient (sigma(0)) had different responses in the two plantation types because of differences in biophysical parameters. The PALSAR sigma(0) showed a higher correlation with field-based measurements and lower saturation in cashew plants compared with rubber plants. Multiple linear regression (MLR) models based on field-based biomass of cashew (C-MLR) and rubber (R-MLR) plants with PALSAR sigma(0) were created. These MLR models were used to estimate natural forest biomass in Cambodia. The cashew plant-based MLR model (C-MLR) produced better results than the rubber plant-based MLR model (R-MLR). The C-MLR-estimated natural forest biomass was validated using forest inventory data for natural forests in Cambodia. The validation results showed a strong correlation (R-2 = 0.64) between C-MLR-estimated natural forest biomass and field-based biomass, with RMSE = 23.2 Mg/ha in deciduous forests. In high-biomass regions, such as dense evergreen forests, this model had a weaker correlation because of the high biomass and the multiple-story tree structure of evergreen forests, which caused saturation of the PALSAR signal.
  • Ram Avtar, Haruo Sawada, Pankaj Kumar
    Environment, Development and Sustainability 15 (6) 1593 - 1603 1387-585X 2013/12 [Not refereed][Not invited]
     
    In this study, we have shown the importance of remote sensing applications and community forestry for forest management, discussed as a case study on Cambodian forest management. Curbing deforestation is necessary for the effective implementation of Reducing Emissions from Deforestation and forests Degradation (REDD+) mechanism and management of forest resources to support sustainable forest management plans. The updated information of the forest cover and forest biomass using advanced remote sensing techniques can be useful for selecting the suitable sites for planned thinning, reforestation, community forestry, and concession land, which eventually will help in controlling the deforestation in Cambodia. To overcome the limitations of remote sensing, an integrated approach of remote sensing and community forestry to monitor forests from local to national level has also been discussed. © 2013 Springer Science+Business Media Dordrecht.
  • Ram Avtar, Haruo Sawada
    ARABIAN JOURNAL OF GEOSCIENCES 6 (12) 4859 - 4871 1866-7511 2013/12 [Refereed][Not invited]
     
    Deforestation has been a major cause of climate change and other environmental problems. An accurate estimation of the volume of deforested area is needed for United Nations Reducing Emissions from Deforestation and Forest Degradation (UN-REDD+) policies implementation and global carbon accounting. Accurate information about three-dimensional (3-D) structure of forests is required to quantify forest carbon stock. This study demonstrates the use of different digital elevation models (DEMs) to monitor changes in height due to deforestation in Cambodia to support climate change mitigation policies of UN-REDD+. The Shuttle Radar Topographic Mission-DEM (SRTM-DEM), Advanced Spaceborne Thermal Emission and Reflection Radiometer Global DEM (ASTER-GDEM) and Panchromatic Remote sensing Instrument for Stereo Mapping-Digital Surface Model (PRISM-DSM) data were calibrated using Ice Cloud and land Elevation Satellite Geoscience Laser Altimeter System (ICESat-GLAS) data. The results obtained from this study clearly indicate the changes in the height of forests due to deforestation activity. The height of cutover forest generated from the PRISM-DSM and SRTM-DEM is more reliable than that from the PRISM-DSM and ASTER-GDEM data. Field data has also been used to validate the height of the cutover forests, which shows +/- 5 m uncertainties in the estimation.
  • Ram Avtar, Pankaj Kumar, C. K. Singh, Netrananda Sahu, R. L. Verma, J. K. Thakur, S. Mukherjee
    WATER QUALITY EXPOSURE AND HEALTH 5 (3) 105 - 115 1876-1658 2013/11 [Refereed][Not invited]
     
    Hydrochemical study of groundwater is useful for determining its suitability for drinking, industrial, and agricultural purposes. In this study, chemical analysis of the groundwater and soil samples has been carried out in Bundelkhand region, where The Government of India is planning to link Ken and Betwa Rivers through a man-made canal. Principal Component Analysis (PCA) of groundwater quality parameters produced five significant components, explaining the 71.04 % cumulative variance. The chemical composition of the groundwater and soil enables the hydro-chemical evaluation of the aquifer system based on the ionic constituents, water types, and the factors controlling groundwater quality. The results show that the major geochemical processes occurring in the region are weathering, ion-exchange, oxidation-reduction, and dissolution. The hydrochemistry of the groundwater of this region seems to be influenced by local anthropogenic activities as the concentrations of fluoride and nitrate were observed to be high at some places. It is expected that with this project development, habitat loss, change in downstream morphology, change in downstream water quality (because of the disturbance in the current surface water budget in both of the rivers and its surrounding areas) etc. will be some of the consequences.
  • Ram Avtar, Pankaj Kumar, Akhilesh Surjan, L. N. Gupta, Koel Roychowdhury
    ENVIRONMENTAL EARTH SCIENCES 70 (4) 1699 - 1708 1866-6280 2013/10 [Refereed][Not invited]
     
    The present study focuses on the hydrogeochemical composition of groundwater in Chhatarpur area with special focus on nitrate and fluoride contamination, considering the fact that groundwater is the only major source of drinking water here. Carbonate and silicate mineral weathering followed by ground water-surface water interactions, ion exchange and anthropogenic activities are mainly responsible for high concentrations of cations and anions in the groundwater in the region. The average concentration of nitrate and fluoride found in 27 samples is 1.08 and 61.4 mg/L, respectively. Nitrate enrichment mainly occurs in areas occupied with intense fertilizer practice in agricultural fields. Since the area is not dominated by industrialization, the possibility of anthropogenic input of fluoride is almost negligible, thus the enrichment of fluoride in groundwater is only possible due to rock-water interaction. The highly alkaline conditions, which favor the fluorite dissolution, are the main process responsible for high concentration of fluoride.
  • Ram Avtar, Rikie Suzuki, Wataru Takeuchi, Haruo Sawada
    PLOS ONE 8 (10) e74807  1932-6203 2013/10 [Refereed][Not invited]
     
    Tropical countries like Cambodia require information about forest biomass for successful implementation of climate change mitigation mechanism related to Reducing Emissions from Deforestation and forest Degradation (REDD+). This study investigated the potential of Phased Array-type L-band Synthetic Aperture Radar Fine Beam Dual (PALSAR FBD) 50 m mosaic data to estimate Above Ground Biomass (AGB) in Cambodia. AGB was estimated using a bottom-up approach based on field measured biomass and backscattering (sigma(o)) properties of PALSAR data. The relationship between the PALSAR sigma(o) HV and HH/HV with field measured biomass was strong with R-2 = 0.67 and 0.56, respectively. PALSAR estimated AGB show good results in deciduous forests because of less saturation as compared to dense evergreen forests. The validation results showed a high coefficient of determination R-2 = 0.61 with RMSE = 21 Mg/ha using values up to 200 Mg/ha biomass. There were some uncertainties because of the uncertainty in the field based measurement and saturation of PALSAR data. AGB map of Cambodian forests could be useful for the implementation of forest management practices for REDD+ assessment and policies implementation at the national level.
  • Ram Avtar, Wataru Takeuchi, Haruo Sawada
    INTERNATIONAL JOURNAL OF DIGITAL EARTH 6 (3) 255 - 275 1753-8947 2013/05 [Refereed][Not invited]
     
    Forest cover monitoring plays an important role in the implementation of climate change mitigation policies such as Kyoto protocol and Reducing Emissions from Deforestation and Forest Degradation (REDD). In this study, we have monitored land cover using the PALSAR (Phased Array type L-band Synthetic Aperture Radar) full polarimetric data based on incoherent target decomposition. Supervised classification technique has been applied on CloudePottier decomposition, FreemanDurden three component, and Yamaguchi four component decomposition for accurate mapping of different types of land cover classes. Based on confusion matrix derived from the predicted and defined pixels, the evergreen and sparsely deciduous forests have shown high producer's accuracy by FreemanDurden three component and Yamaguchi four component classifications. The overall accuracy of Maximum Likelihood Classification by Yamaguchi four component is 94.1% with 0.93 kappa coefficient as compared to the 90.3% with 0.88 kappa coefficient by FreemanDurden three component and 89.7% with 0.88 kappa coefficient by CloudePottier decomposition. High accuracy of classification in a forested area using full polarimetric PALSAR data may have been because of high penetration of L-band SAR. The content of this study could be useful for the forest cover mapping during cloudy days needed for proper implementation of REDD policies in Cambodia.
  • Integrating major ion chemistry with statistical analysis for geochemical assessment of groundwater quality in coastal aquifer of Saijo plain, Ehime Prefecture, Japan
    Pankaj Kumar, Ram Avtar
    Water Quality: Indicators, Human Impact and Environmental Health 99 - 108 2013/02 
    A comprehensive study of major ions, silica and isotopes was carried out to understand the geochemical processes controlling groundwater quality in coastal aquifer of Saijo plain, Western Japan. Various graphs were plotted using chemical data to enable hydrochemical evaluation of the aquifer system based on the ionic constituents, water types, hydrochemical facies, and factors controlling groundwater quality. Carbonate weathering and atmospheric precipitation are strong factors controlling the chemistry of major ions. From stable isotopic results, it was found that most of sample points plotted near the local meteoric water line (LMWL) i.e. origin of ground water is meteoric in principle however point away from the LMWL favors exchange with rock minerals mainly salinization process. This study is crucial considering that Saijo city is known as one of the water capital of Japan and groundwater is the exclusive source of drinking water in this region. © 2013 by Nova Science Publishers, Inc. All rights reserved.
  • Ram Avtar, Wataru Takeuchi, Haruo Sawada
    ENVIRONMENTAL MONITORING AND ASSESSMENT 185 (2) 2023 - 2037 0167-6369 2013/02 [Refereed][Not invited]
     
    An accurate estimation of a plant's age is required for the prediction of yield and management practices. This study demonstrates the relationship between backscattering properties (sigma A degrees) of Phased Array type L-band Synthetic Aperture Radar (PALSAR) dual polarimetric data with cashew plants' biophysical parameters (height, age, crown diameter, diameter at breast height, basal area, tree density, and biomass) in Cambodia. PALSAR sigma A degrees has shown a positive correlation with the biophysical parameters of cashew plants. The value of sigma A degrees increases with the age of cashew plants. At a young stage, the cashew plants show a higher rate of an increase in sigma A degrees compared to that at the mature stage. The sigma A degrees horizontal polarization transmitted and vertical received (HV) shows higher sensitivity to the plant's growth than sigma A degrees horizontal polarization transmitted and received (HH). High backscattering and low variations were observed at mature stage (8-12 years) of cashew plantation. Saturation in backscattering has shown from the age of about 13 years. The validation results indicate strong coefficient of determination (R (2) = 0.86 and 0.88) for PALSAR-predicted age and biomass of cashew plants with root mean square error = 1.8 years and 16.3 t/ha for age and biomass, respectively. The correlations of sigma A degrees (HH) with biophysical parameters observed in the dry season were better than those of the rainy season because soil moisture interferes with backscattering in the rainy season. Biomass accumulation rate of cashew plants has been predicted that would be useful for selection of plants species to enhance carbon sequestration. This study provides an insight to use PALSAR for the monitoring of growth stages of plants at the regional level.
  • Ram Avtar, Haruo Sawada, Wataru Takeuchi, Gulab Singh
    GEOCARTO INTERNATIONAL 27 (2) 119 - 137 1010-6049 2012 [Refereed][Not invited]
     
    In this study, we have demonstrated the capability of full polarimetric ALOS/Phased Array L-band Synthetic Aperture Radar data for the characterization of the forests and deforestation in Cambodia, to support climate change mitigation policies of Reducing Emission from Deforestation and Forest Degradation (REDD). We have observed mean backscattering coefficient (sigma degrees), entropy (H), alpha angle (alpha), anisotropy (A), pedestal height (PH), Radar Vegetation Index (RVI) and Freeman-Durden three-component decomposition parameters. The observations show that the forest types and deforested area are showing variable polarimetric and backscattering properties because of the structural difference. Evergreen forest is characterized by a high value of sigma degrees HV (-12.96 dB) as compared with the deforested area (sigma degrees HV = -22.2 dB). The value of polarimetric parameters such as entropy (0.93), RVI (0.91), PH (0.41) and Freeman-Durden volume scattering (0.43) is high for evergreen forest, whereas deforested area is characterized by the low values of entropy (0.36) and RVI (0.17). Based on these parameters, it is found that sigma degrees HV, entropy, RVI and PH provide best results among other parameters.
  • Gulab Singh, Y. Yamaguchi, S. -E. Park, Ram Avtar
    GEOCARTO INTERNATIONAL 27 (2) 139 - 151 1010-6049 2012 [Refereed][Not invited]
     
    In recent years, there has been increased utilization of fully polarimetric synthetic aperture radar (POLSAR) data to study glaciated terrain features for glaciological and climate change modelling. This article is concerned with more accurate results and appropriate analysis of POLSAR data over a highly rugged glaciated area in Himalayan region. For this purpose, the modified Yamaguchi four-component scattering power decomposition (4-CSPD) method with a rotation concept of 3 x 3 coherency matrix [T] about line of sight is evaluated. It has been found that the modified Yamaguchi 4-CSPD method significantly improved the decomposition results as compared with the original 4-CSPD by minimizing the cross-polarized Horizontal-Vertical (HV) components. This modified 4-CSPD leads to enhancement in the double bounce scattering and surface scattering components and also avoids the overestimation problem in the volume scattering component as compared with the original 4-CSPD from the sloped terrain. The significant reductions of the negative power occurrence in the surface scattering (3.9%) and the double bounce scattering (19.7%) components have also been noticed as compared with the original 4-CSPD method over the glaciated area in this part of the Indian Himalaya.
  • Ram Avtar, Chander Kumar Singh, Satayanarayan Shashtri, Saumitra Mukherjee
    ENVIRONMENTAL MONITORING AND ASSESSMENT 182 (1-4) 341 - 360 0167-6369 2011/11 [Refereed][Not invited]
     
    Ken-Betwa river link is one of the pilot projects of the Inter Linking of Rivers program of Government of India in Bundelkhand Region. It will connect the Ken and Betwa rivers through a system of dams, reservoirs, and canals to provide storage for excess rainfall during the monsoon season and avoid floods. The main objective of this study is to identify erosional and inundation prone zones of Ken-Betwa river linking site in India using remote sensing and geographic information system tools. In this study, Landsat Thematic Mapper data of year 2005, digital elevation model from the Shuttle Radar Topographic Mission, and other ancillary data were analyzed to create various thematic maps viz. geomorphology, land use/land cover, NDVI, geology, soil, drainage density, elevation, slope, and rainfall. The integrated thematic maps were used for hazard zonation. This is based on categorizing the different hydrological and geomorphological processes influencing the inundation and erosion intensity. Result shows that the southern part of the study area which lies in Panna district of Madhya Pradesh, India, is more vulnerable than the other areas.
  • Ram Avtar, C. K. Singh, Gulab Singh, R. L. Verma, S. Mukherjee, H. Sawada
    BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT 70 (4) 595 - 606 1435-9529 2011/11 [Refereed][Not invited]
     
    The 231 km long Ken-Betwa River Linking canal will transfer 1,020 hm(3) of surplus water from the Ken River to the deficit Betwa River basin. The landslide susceptibility zonation map of the river link has been assessed using remote sensing data in GIS. Various thematic maps such as geology, land use/land cover, lineament, drainage, slope, aspect, normalized difference vegetation index and soil type were generated from the Landsat Thematic Mapper 5 satellite data of 2005, the Survey of India topographic sheets, Shuttle Radar Topographic Mission Digital Elevation (SRTM-DEM) data and other existing maps. Numerical rating schemes were used for ranking the thematic layers. The results were supported with the rainfall data, groundwater level data and a petrological study of rock thin sections. In addition to providing valuable information for project decision- makers, the results will assist in slope management and land use planning in the area.
  • Deepak Agrawal, Pankaj Kumar, Ram Avtar, A. L. Ramanathan
    WATER QUALITY EXPOSURE AND HEALTH 3 (2) 119 - 126 1876-1658 2011/10 [Refereed][Not invited]
     
    This work gives us an overview of the groundwater quality and problems pertaining to the occurrence of arsenic (As) and other chemical contaminants in the groundwater of Begusarai district of Bihar, India. The total As concentration in the analyzed water samples varies between 21.5-94.3 mu g/L. Through the saturation index using PhreeqC, it was found that most of the samples are saturated for mineral goethite, calcite and dolomite. It was observed that mobilization of arsenic from the alluvial aquifers is mainly affected through the means of reductive dissolution of the iron oxyhydroxides within the sediments. Reductive dissolution of iron oxyhydroxide present as coatings on and around clay layer seems to be the main process responsible for the release of As into groundwater. Close to the Gangetic flood plain most of the tube wells (shallow aquifers) are affected. Groundwater is characterized by slightly alkaline pH with a moderate to strong reducing nature. The water type mainly falls in two categories i. e. Ca-HCO3 and Ca-Cl (with contribution of 75 and 25% of total water type, respectively). Enrichment of NO3- at few locations is an indicator of agriculture practice well supported by effluent leaching.
  • Chander Kumar Singh, Satyanarayan Shashtri, Saumitra Mukherjee, Rina Kumari, Ram Avatar, Amit Singh, Ravi Prakash Singh
    WATER RESOURCES MANAGEMENT 25 (7) 1881 - 1898 0920-4741 2011/05 [Not refereed][Not invited]
     
    The groundwater resource is a multidimensional concept; it is defined by its location, its occurrence over time, its size, properties, conditions of accessibility, the effort required to mobilize it and therefore, all of which are to be considered in the context of demand. Groundwater, a renewable and finite natural resource, vital for man's life, social and economic development and a valuable component of the ecosystem, is vulnerable to natural and human impacts. There is a great need for the assessment and monitoring of quality and quantity of groundwater resource required at local level to develop an exact scenario of watershed. In this study qualitative assessment of groundwater was done and a ground water quality index criterion was used to understand the suitability of groundwater for irrigation and drinking purpose in the study area. A GIS based multicriteria analysis was done by assigning weight to different water quality parameters. The water quality was grouped into six classes from very good to unfit for drinking. It was found that the in most part of the study area the water quality varied from moderate to good except in some areas where it is poor to unfit. An assessment of change in landuse and landcover was done from the year 1989 using Landsat data to year 2006 using LISS III satellite data. The change in LULC was correlated with water quality data and it was found that the areas around which rapid urbanisation as well as industrialisation is taking place showed poor to unfit groundwater in terms of quality.
  • Ram Avtar, Pankaj Kumar, C. K. Singh, S. Mukherjee
    WATER QUALITY EXPOSURE AND HEALTH 2 (3-4) 169 - 179 1876-1658 2011/02 [Refereed][Not invited]
     
    In this paper, we have studied the comparative hydrogeochemistry of the Ken and Betwa Rivers of Bundelkhand area, considering the importance of the Ken-Betwa River linking project (KBLP) in India. Factor analysis and principal component analysis (PCA) has been done to identify the highly correlated and interrelated water-quality parameters. All the physico-chemical parameters for both rivers are within the highest desirable or maximum permissible limit set byWHO (World Health Organization) except some anions viz. NO3-, Cl-, SO42- and F- at some sampling points. The Ken River showed a high spatial variability and significant ionic concentration due to the higher geological and pedological watershed richness as well as absence of pollution from anthropogenic point sources. The Betwa River showed a low spatial variability and higher mineralization due to the anthropogenic point sources that exist downstream. This preliminary study shows the spatiotemporal variability of the hydrogeochemical parameters of the Ken-Betwa River basin.
  • Genetically modified Cotton species detection by LISS-III satellite data
    Mukherjee, Saumitra, Shashtri, Satyanarayan, Singh, Ch, er Kumar, Kumari, Bindu, Kumari, Reena, Avatar, Ram, Singh, Amit, Mukherjee, Anita, Singh, Bhoop
    2011
  • AVTAR Ram, TAKEUCHI Wataru, SAWADA Haruo
    SEISAN KENKYU 東京大学生産技術研究所 63 (4) 443 - 446 0037-105X 2011 
            Information about the biophysical parameters of plants is useful for the prediction of growth, yield, rotation cycle, carbon sequestration and management practices. In this study, we have investigated different biophysical parameters of cashew and rubber plants using Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS/PALSAR) backscattering properties in Cambodia. The result shows the plants’ structural dependence on PALSAR data. The backscattering coefficient (σ0) has different response for both plantation types because of differences in their biophysical parameters. This dependency of σ0 shows different behaviour of PALSAR dual polarimetric data. The σ0 HV polarization shows fairly good correlation with the biomass, height, DBH and age of cashew and rubber plantations up to the saturation limit. [This abstract is not included in the PDF]
  • Ram Avtar, C. K. Singh, Satyanarayan Shashtri, Amit Singh, Saumitra Mukherjee
    GEOCARTO INTERNATIONAL 25 (5) 379 - 396 1010-6049 2010 [Refereed][Not invited]
     
    The use of remote sensing data with other ancillary data in a geographic information system (GIS) environment is useful to delineate groundwater potential zonation map of Ken-Betwa river linking area of Bundelkhand. Various themes of information such as geomorphology, land use/land cover, lineament extracted from digital processing of Landsat (ETM+) satellite data of the year 2005 and drainage map were extracted from survey of India topographic sheets, and elevation, slope data were generated from shuttle radar topography mission (SRTM) digital elevation model (DEM). These themes were overlaid to generate groundwater potential zonation (GWPZ) map of the area. The final map of the area shows different zones of groundwater prospects, viz., good (5.22% of the area), moderate (65.83% of the area) poor (15.31% of the area) and very poor (13.64% of area).
  • Chander Kumar Singh, Satyanarayan Shashtri, Ram Avtar, Saumitra Mukherjee, Sudhir Kumar Singh
    Ecological Questions 13 73 - 79 2083-5469 2010 [Not refereed][Not invited]
     
    Information about change is necessary for updating Land Use/Land Cover LULC maps and the management of natural resources. The paper aims to map the changes in the LULC using hybrid classification methods and to quantify the land use/land cover change that took place in the Rupnagar district of Punjab. The paper promotes the classification of LULC based on remote sensing information (obtained mainly through the utilization of Thematic Mapper TM) to generate data products that are both appropriate to, and immediately usable within different scientific applications. Satellite data provides the basis for geographically referenced land use/land cover characterization that is internally consistent, repeatable over time, and potentially more reliable. The main objective of this study is to quantify the change in the area of various LULC classes. Classification of four reflective bands of three Landsat images was carried out by using Isodata clustering algorithm with the aid of ground truth data. The second part focused on land use/land cover changes by using the change detection comparison (pixel by pixel). The change analysis was performed by post image classification method, comparing the data from three different dates. The result indicates there was a rapid change in land use/land cover due to the increase in population. The results indicate that severe land cover changes have occurred in cropland (225.97 km2), dense forest (128.57 km2), settlement (93.5 km2), salt affected land (9.74 km2) and water body (11.69 km2) areas from 1989 to 2006.
  • Sudhir Kumar Singh, Chander Kumar Singh, Kewat Sanjay Kumar, Ramvtar Gupta, Saumitra Mukherjee
    JOURNAL OF HYDROLOGY AND HYDROMECHANICS 57 (1) 45 - 54 0042-790X 2009 [Not refereed][Not invited]
     
    Monitoring of groundwater quality in Bareilly district, Uttar Pradesh, India, was performed at 10 different sites during the years 2005-2006. Obtained quality parameters were treated using principal component analysis (PCA) and cluster analysis (CA). The study shows usefulness of multivariate statistical techniques for evaluation and interpretation of groundwater quality data sets.

MISC

  • Nguyen Hong Duc, Pankaj Kumar, Pham Tam Long, Gowhar Meraj, Pham Phuong Lan, Mansour Almazroui, Ram Avtar  Earth Systems and Environment  8-  (2)  181  -205  2024/06  
    Water governance (WG) plays a crucial role in steering integrated water resources management (IWRM) toward the fulfillment of the Sustainable Development Goals (SDGs), particularly in developing regions. Despite this, substantial challenges hinder effective WG implementation across Asia. This study systematically reviews WG literature in Asia from 2000 to 2020, identifying prevailing challenges and proposing a modified WG framework to encourage policy reform. Utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, we searched the Scopus database and additional resources to accumulate comprehensive literature on WG in Asia. We incorporated peer-reviewed articles, gray literature, and institutional reports. These were evaluated based on their relevance to WG in Asia, use of analytical frameworks, and incorporation of performance indicators. The search identified 350 potentially relevant documents, with 145 qualifying for in-depth review after screening through rigorous selection criteria, comprising peer-reviewed articles, institutional reports, and influential gray literature. The literature revealed increasing attention to WG since the SDGs’ inception, with the most significant contributions related to Southeast Asia, South Asia, and East Asia. Critical WG issues identified include transboundary water management, irrigation challenges, water quality concerns, and water–food–energy nexus interdependencies. Predominantly, these issues stem from insufficient legal and institutional frameworks, poor stakeholder engagement, and ineffective cooperation, particularly in cross-border river basins. The analysis frequently employed legal and institutional frameworks, Ostrom’s theory, and OECD guidelines, all pointing to common challenges. We propose a modified WG framework with 13 elements, accompanied by key recommendations. The study underscores the need for an enhanced understanding of WG to support policymakers, managers, and scholars in developing effective WG strategies that align with the SDGs. This research contributes to the literature by providing a synthesized perspective on WG in Asia and a foundation for future governance improvements.
  • Stanley Anak Suab, Hitesh Supe, Ram Avtar, Ramzah Dambul, Xinyu Chen  IOP Conference Series: Earth and Environmental Science  1064-  (1)  012003  -012003  2022/07/01  
    Abstract Recurring floods severely impacted the livelihood and socio-economic. It causes disruption of clean water, electricity, communications, properties damages and sometimes loss of life. Information on flooded areas is crucial for effective emergency responses support. In this study we used Sentinel 1 (S-1) C-band and Sentinel 2 (S-2) Multispectral satellite imageries where wider area covered in 12 days repeat satellite pass. The flood event on the 26 May 2021 was identified and we retrieved the S-1 GRD SAR imagery and S-2 level-2A BOA in GEE environment. We analysed the S-1 VV, VH, VV/VH imagery by pixels clustering using object based SNIC classification and Machine Learning (ML) algorithm for extraction of waterbody. Meanwhile for the S-2 we used MNDWI and extracted the waterbody area using thresholding value. We obtained the final flooded area of S-1 and S-2 by subtraction with permanent waterbody. The S-2 flood estimation results were better than S-1. However, S-2 limited to cloud free and less cloudy coverage while S-1 lacking of ability to identify flood in detailed was influenced by slope shadow area. This study provides the basis of detection and mapping floods using S-1 and S-2 imageries through Machine Learning techniques in GEE for local scope of Sabah, Borneo region and Malaysia.
  • Combining UAV and satellite image for monitoring drifting ice
    Matsumura K, Chiba S, Avtar R, Matoba S, Ichinose T, Morikawa K  Okhotsk Sea and Polar Oceans Research  5-  2021/09
  • Ram Avtar, Teiji Watanabe  Unmanned Aerial Vehicle: Applications in Agriculture and Environment  1  -199  2019/01/01  
    This book showcases how new and emerging technologies like Unmanned Aerial Vehicles (UAVs) are trying to provide solutions to unresolved socio-economic and environmental problems. Unmanned vehicles can be classified into five different types according to their operation. These five types are unmanned ground vehicles, unmanned aerial vehicles, unmanned surface vehicles (operating on the surface of the water), unmanned underwater vehicles, and unmanned spacecraft. Unmanned vehicles can be guided remotely or function as autonomous vehicles. The technology has a wide range of uses including agriculture, industry, transport, communication, surveillance and environment applications. UAVs are widely used in precision agriculture; from monitoring the crops to crop damage assessment. This book explains the different methods in which they are used, providing step-by-step image processing and sample data. It also discusses how smart UAVs will provide unique opportunities for manufacturers to utilise new technological trends to overcome the current challenges of UAV applications. The book will be of great interest to researchers engaged in forest carbon measurement, road patrolling, plantation monitoring, crop yield estimation, crop damage assessment, terrain modelling, fertilizer control, and pest control.
  • Ram Avtar, Stanley Anak Suab, Ali P. Yunus, Pankaj Kumar, Prashant K. Srivastava, Manish Ramaiah, Churchill Anak Juan  Unmanned Aerial Vehicle: Applications in Agriculture and Environment  85  -100  2019/01/01  
    The scope of unmanned aerial vehicles (UAVs), also known as “drone technology, " is increasing, with various applications in the field of remote sensing and environment. UAVs not only provide high-resolution, real-time data, but also have different applications for end users. They have become an essential tool for land surveyors because traditional land survey methods are expensive and time-consuming, requiring trained professionals and many hours to measure a single plot of land. With the advancement of UAVs, we can significantly reduce the cost. In this study, we have collected UAV data in Malaysia to acquire information about the plantation management practices, as well as oil palm health assessment. Our results showed that multispectral data collected from a UAV-borne MicaSense RedEdge camera is useful for identifying physiological stress in mature oil palm plants, which clearly illustrates stunted tree crown with low value of normalized difference vegetation index (NDVI).
  • Ram Avtar, Teiji Watanabe  Unmanned Aerial Vehicle: Applications in Agriculture and Environment  1  -6  2019/01/01  
    This chapter gives an introduction to the brief history, development, and state-of-the-art technology used in unmanned aerial vehicles (UAVs) with their application in the fields of agriculture and environment. The chapter also outlines the structure of book consisting of several chapters, each of which is authored by researchers working in their respective fields throughout their research career. The contributing authors are an amalgam of academicians, researchers, industry professionals, and users of such technology. The research areas considered in the case studies of this book cover diverse land from different countries and regions. This chapter summarizes the structure and approach toward the use of UAVs in an attempt to tackle the various challenges and issues faced in the use of UAVs.
  • Stanley Anak Suab, Ram Avtar  Unmanned Aerial Vehicle: Applications in Agriculture and Environment  101  -118  2019/01/01  
    Unmanned aerial vehicle system (UAVS) or drone gains significant role for acquiring geospatial data especially in forestry and plantation operations. This was made possible by current advancement of consumer drone and availability of open-source UAVS technology for custom-made UAVS. The role of UAVS technology is seen as bridging the gap between field data collection and airborne and spaceborne remote sensing. UAVS offers great details of geospatial data at very high resolution with flexibility of deployment and cloud-free aerial photos. In Malaysia, the usage of UAVS is regulated by the Civil Aviation Authority of Malaysia (CAAM). The benefits of UAVS applications in forestry and plantation operations greatly improve efficiency through fast and timely geospatial data acquisition for various operational applications. In order to utilise UAVS technology, the forest and plantation owners’ choices are either hiring third-party specialist or purchasing UAVS hardware and software with necessary training for own staff. UAVS workflow generally consists of flight mission planning, data acquisition, data processing and output integration into geographic information systems (GIS). In this chapter, various UAVS applications in forestry and plantation operations based on experiences in Sabah and Sarawak are discussed. UAVS applications are infrastructure management, roads, nursery, boundary and encroachment monitoring, nursery management and high conservation value areas (HCV).
  • Ram Avtar  Unmanned Aerial Vehicle: Applications in Agriculture and Environment  v  -vi  2019/01/01
  • Ram Avtar, Saumitra Mukherjee, S.B.S. Abayakoon, Chann Sophal, Rajesh Thapa  APN Science Bulletin  8-  (1)  2018
  • Ram Avtar  Tropical Forest, Geospatial Data and REDD+  1  -139  2017/01/01  [Not refereed][Not invited]
     
    © 2017 by Nova Science Publishers, Inc. All rights reserved. With an increasing role of tropical forests supporting a range of ecosystem services, biodiversity conservation, water regulation, soil conservation, timber, non-timber forest products, carbon sequestration, and climate change mitigation, the importance of forest resources management has become very crucial. The tropical forests of Indochina countries are rich in biodiversity and carbon density, and thus are significant from social, ecological, political and economic aspects. These forests provide essential livelihoods to the local and indigenous people. Rapid economic growth, agriculture expansion, illegal logging, population growth, and urbanization have been reported as major contributors to almost all cases of deforestation. Due to rapid development, forest resources are at a great risk. The FRA 2010 report shows that deforestation caused a loss of about 13 million hectares of tropical forests per year from the year 2000 to 2010. Therefore, there is an urgent need for better management of these resources. This book partially contributes towards climate change mitigation by implementing the Reducing Emissions from Deforestation and forest Degradation (REDD+) mechanism. To mitigate climate change, most present studies are now concentrated on afforestation, reforestation and reducing deforestation and degradation. This book is focused on the application of multi-sensor remote sensing techniques to manage Cambodian forests for the effective implementation of the REDD+ mechanism. In this context, it is important to obtain reliable and consistent information of (a) forest cover, (b) deforestation, and (c) forest biomass to estimate CO2 emissions for the improvement of national carbon accounting. Additionally, this information will also be used for the development of the measurement, reporting and verification (MRV) system and for the management of forest resources to support sustainable forest management. Current knowledge is very limited with regard to the MRV system for REDD+ mechanism implementation. This book demonstrates the use of multi-sensor remote sensing techniques to manage the forest resources more sustainably. Further, it includes a concept on how precisely we can measure various forest parameters to minimize the uncertainty and to validate the results based on field data. The study is very much interdisciplinary in nature. It integrates core remote sensing techniques with the socio-economic angle of the REDD+ mechanism. It emphasizes on remote sensing as a technique for ensuring the MRV of REDD+ initiatives, taking into consideration its cost effectiveness in implementation.
  • Mutisya Emmanuel, Lilian Muasa, Chiahsin Chen, Florence Mutisya, Ram Avtar  Natural Resources Management: Concepts, Methodologies, Tools, and Applications  3-2-  1121  -1132  2016/09/08  [Not refereed][Not invited]
     
    Africa continues to experience serious signs of multiple crises in the context of sustainability. These crises nclude vulnerability to climate change, rapid urbanization, food insecurity, and many others. One crisis, that defines Africa today, is the unprecedented rapid urbanization which continues to pose a big challenge to the diminishing available resources, environmental quality and human well-being. Cities in Africa continue to experience a fast horizontal growth of settlements due to influx of people from rural areas who often settle in the economically lowest segments in urban areas. This horizontal rapid growth has eaten up land set for agriculture around cities and promoted the rapid growth of informal settlements exacerbating the impacts of climate change leading to a negative impact on agricultural production. Policies linking rapid urbanization and climate change with agricultural productivity are need. This paper explores and documents the impact of rapid urbanization on climate change policies and subsequent impact on agriculture in Africa.
  • Linking and harmonizing scenarios and models across scales and domains.
    Cheung, W. W. L, Rondinini, C, Avtar, R, Hickler, T, Metzger, J. P, Scharlemann, J. P. W, Yue, T. X  In IPBES;methodological assessment of scenarios;models of biodiversity;ecosystem services. Berlin;Secretariat of the;Intergov;l;Platform for Biodiversity;Ecosystem ServicesIn IPBES;methodological assessment of scenarios;models of biodiversity;ecosystem services. Berlin;Secretariat of the;Intergov;l;Platform for Biodiversity;Ecosystem Services  2016/09
  • Ali P. Yunus, Jie Dou, Ram Avtar, A. C. Narayana  Coastal Research Library  14-  65  -77  2016  
    The December 24, 2004 Sumatra earthquake and Tsunami had caused large damage to the coastal environment in the Indian Ocean countries. Continuous monitoring of shorelines are needed to understand the causes and consequences of recent changes and to assess the long term impact of tsunami waves. Assessment of the shoreline and coastal morphological changes due to tsunami in Katchal Island have been lacking due to obstacles in the field data acquisition owing to their remote location. As access to the ground information is limited, the only possibility is the monitoring of shorelines from multi-temporal satellite images. In this study, we demonstrate the methods used in extracting shorelines and analyzing their changes using the data from Indian Remote Sensing (IRS) satellites, the EO1-ALI and Landsat images in a GIS environment. Eight satellite images acquired between 2004 and 2014 where used for the shoreline change and coastal morphology analysis in the Katchal Island. The results showed that the island experienced extensive erosion and significant loss in land area of about 20 km2. Erosion has been more prevalent than accretion at an average linear regression rate of ~ −13 m/year between 2004 and 2010. Net shoreline movement of more than 4 km landward has been observed at the western coast of the island. Regions of high net shoreline movements were associated with bay-mouth areas, and regions linked with coastal inlets. This study demonstrates the strong potential of archived satellite images for detecting shoreline movements in far-off islands. The results will likewise help in understanding the response and recovery of shorelines in Indian Ocean regions after the 2004 tsunami.
  • A Multivariate approach for water quality assessment of river Mandakini in Chitrakoot, India
    L. N. Gupta, Ram Avtar, P. Kumar, G. S. Gupta, R. L. Verma, N. Sahu, S. Sil, A. Jayaraman, K. Roychowdhury, K. Sharma, S. Singh  Journal of Water Resources and Hydraulic Engineering  3-  (1)  22  -29  2014/09  [Refereed]
  • Ram Avtar, Osamu Saito, Gulab Singh, Hideki Kobayashi, Yunus Ali, Srikantha Herath, Kazuhiko Takeuchi  2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)  761  -763  2014  [Refereed][Not invited]
     
    Agriculture in both industrialized and developing countries is a unique sector, characterized by complex issues and problems, ranging from macro (economic) policy levels all the way to the micro (smallholder) farming household and field plot levels. Agriculture, being predominantly a (small-scale) family and/or communal enterprise differs in fundamental ways from administrative services and industrial sectors in terms of relative unpredictability, uncertainty and variability in geo-physical (soil and weather) conditions on which the primary production processes rely. Also, there is a huge diversity in production strategies and objectives among farming households as well as household individuals. Agriculture in Africa is mainly seasonal and faces high levels of risks, which are in-turn compounded by poor infrastructure and isolated rural communities [1]. Fluctuating market and trade conditions, as well as political instability further add to farmer uncertainty. Agriculture therefore, faces rather unique problems with respect to research and development including the planning, implementation and evaluation processes that are involved as well as the assessments of impacts at various levels [2].
  • Ram Avtar, R. Ishii, H. Kobayashi, H. Fadaei, R. Suzuki, S. Herath  2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)  2137  -2140  2013  [Refereed][Not invited]
     
    Carbon rich tropical forests of Southeast Asia have increasingly become a target for the conversion to plantation area. Plantations are economically important for the local society because they provide incentives in a short period of time. Southeast Asia has a high rate of conversion of tropical forests to various types of plantation species such as oilpalm, rubber, acacia, cashew, teak, eucalyptus etc. Therefore, monitoring of carbon loss due to the conversion of forests to various plantation species has become crucial in the global carbon cycle. Information about the age or growth stages (juvenile, young, mature and old) of plantation species is a useful parameter to calculate carbon sequestration as well as for predicting yield and a range of management practices such as determining location for thinning, harvesting and replantation. This study focuses on the comparison and efficiency of multi-frequency, multi-polarized Synthetic Aperture Radar (SAR) data to monitor various growth stages of oilpalm plants in Sarawak, Malaysia based on backscattering and polarimetric decomposition techniques. Phased Array type L-band Synthetic Aperture Radar (PALSAR) data with dual and quad polarization, Radarsat-2 data with quad polarization and TerraSAR-X (TSX) data with HH polarization have been used in this investigation. Results show that, PALSAR data with HV polarization shows highest sensitivity with the oilpalm plant's age as compared to other SAR data. TSX based texture information will also be utilized to find the important texture parameters to identify various growth stages of oilpalm plants.
  • Ram Avtar, R. Ishii, H. Kobayashi, H. Fadaei, S. Herath, R. Suzuki  CONFERENCE PROCEEDINGS OF 2013 ASIA-PACIFIC CONFERENCE ON SYNTHETIC APERTURE RADAR (APSAR)  115  -118  2013  [Refereed][Not invited]
     
    With the increase in the global demands for food and bio-fuels, the plantation area is increasing and they are the major derivers of deforestation and biodiversity loss in Southeast Asia. A number of research papers have demonstrated the applicability of Synthetic Aperture Radar (SAR) data to monitor terrestrial ecosystem in tropical countries without limitations of clouds. This study investigated the use of multi-sensor SAR and optical data to monitor growth stages of oilpalm plantation in Sarawak. Regression models were developed between oilplam age estimated based on Landsat archive data and SAR backscattering. Phased Array type L-band Synthetic Aperture Radar (PALSAR) data with HV polarization showed best correlation with r(2) = 0.77 as compared to X-band and C-band SAR data. We have further applied various polarimetric decomposition techniques to identify best polarimetric parameters to monitor growth stages of oilpalm plants. Yamaguchi 4-component based polarimetric decomposition showed good results compared to other polarimetric decomposition parameters.
  • Ram Avtar, Jay Krishna Thakur, Amit Kumar Mishra, Pankaj Kumar  Geospatial Techniques for Managing Environmental Resources  9789400718586-  139  -151  2012/11/01  [Not refereed][Not invited]
     
    Forests are one of the most crucial life supporting system that provide range of economic, social and environmental benefits, including essential ecosystem services such as climate change mitigation and adaptation. Forest plays an important role in maintaining ecological balance and homeostatic in the environment (Wulder and Franklin, 2003). Forest cover mapping is necessary for sustainable management and utilization of forest resources. Forest cover monitoring based on geospatial data can significantly contribute in future forest management plans for reducing deforestation and implementation of climate change mitigation policies. Establishing a reliable baseline of forest cover and monitoring forest cover change in the tropical countries become essential (FAO, 2001 REDD, 2010). Recent report of FRA (2010) shows the global change in forest area is about -5.2 million hectares per year during 2001-2010.
  • Ram Avtar, Haruo Sawadaand, Rikie Suzuki  2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS)  5333  -5336  2012  [Refereed][Not invited]
     
    Deforestation has been a major cause of the climate change. An accurate estimation of deforested area is needed for United Nations Reducing Emissions from Deforestation and Forest Degradation (UN-REDD+) policies implementation. The height of the deforested area was estimated using different digital elevation models (DEMs) in Cambodia. The Shuttle Radar Topographic Mission-Digital Elevation Model (SRTM-DEM), Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER-GDEM) and Panchromatic Remote sensing Instrument for Stereo Mapping-Digital Surface Model (PRISM-DSM) data were calibrated using Ice Cloud and land Elevation Satellite Geoscience Laser Altimeter System (ICESat-GLAS) data. The results obtained from this study clearly showed the height of the deforested area. Field data has been used to validate the height of the cut-over forests, which shows +/- 5 m uncertainties in the estimation.
  • Ram Avtar, Wataru Takeuchi, Haruo Sawada  2011 3rd International Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2011  252  -255  2011/12/22  [Not refereed][Not invited]
     
    Forests play an important role in the climate change mitigation and regulation. Monitoring of forest biomass from local to global scale has become a challenging issue in the context of climate change. In this study, we have investigated the backscattering properties of ALOS/PALSAR data in cashew and rubber plantation area of Cambodia. The result shows that PALSAR backscattering coefficient (σ 0) has different response for both the plantation types because of difference in their biophysical parameters. The PALSAR σ 0 indicates a high correlation and a less saturation in cashew plants than rubber plants. A multi-linear regression (MLR) model has been generated using the cashew plants ground based biomass and PALSAR σ 0. This MLR model has been applied to estimate natural forests biomass in Cambodia. The natural forest biomass was validated using forest inventory data of Cambodia. The validation results indicate a strong correlation (R 2 = 0.64) between PALSAR estimated biomass and field based biomass with RMSE = 23t/ha in deciduous forests. In high biomass region such as dense evergreen forest, this model becomes saturated because of saturation of PALSAR signal. The application of this model is to estimate biomass of deciduous forest in Cambodia for UN-REDD (United Nations Reducing Emission from Deforestation and Forest Degradation) policies implementation. © 2011 KIEES.
  • Ram Avtar, Haruo Sawada  32nd Asian Conference on Remote Sensing 2011, ACRS 2011  3-  1962  -1967  2011/12/01  [Not refereed][Not invited]
     
    Tropical countries like Cambodia require information about forest biomass for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and forest degradation plus (REDD+). This study investigates the potential of Phased Array-type L-band Synthetic Aperture Radar fine beam dual (PALSAR FBD) 50m mosaic data to estimate above ground biomass in Cambodia. The radiometric and terrain corrections were applied to reduce the topographic effects. Above ground biomass (AGB) was estimated using bottom-up approach based on field calculated biomass and backscattering (σ°) properties of PALSAR data. The relationship between the PALSAR σ° HV and HH/HV with field based biomass was strong with R 2 = 0.67 and 0.56, respectively. PALSAR estimated biomass shows good results in deciduous forests because of less saturation as compared to dense evergreen forests. The validation result shows high coefficient of determination R 2 = 0.61 with RMSE = 21 t/ha using values up to 200 t/ha biomass. There are some uncertainty because of uncertainty in the field based measurement and saturation of PALSAR data. Above-ground biomass map of Cambodian forests will provide information about the successful implementation of forest management practices for the REDD+ assessment and policies implementation at national level.
  • Ram Avtar, Haruo Sawada  31st Asian Conference on Remote Sensing 2010, ACRS 2010  1-  37  -43  2010/12/01  [Not refereed][Not invited]
     
    In this paper, we have measured backscattering signature from cashew plantation area in a part of Cambodia using L-band PALSAR (Phased Array type L-band Synthetic Aperture Radar) data. Empirical relationship between cashew plants growth and L-band backscattering was investigated. The backscattering coefficient (σ0) of PALSAR data shows a positive correlation with the cashew plants age. The results show that, the value of σ0 increases with the increase in the age of cashew plant. In the young stage the cashew plants show more increase in the value of σ0 as compared to the mature and old stage.
  • Ram Avtar, H. Sawada, S. Mukherjee, M. Kumar, C. K. Singh, P. Kumar  30th Asian Conference on Remote Sensing 2009, ACRS 2009  1-  326  -331  2009/12/01  [Not refereed][Not invited]
     
    The main objective of this study is to identify erosional and inundation prone zones of Ken-Betwa River linking site in India by using Remote Sensing and GIS tools. In this study, Landsat (ETM +) data of year 2005, digital elevation model from the SRTM and other ancillary data were analyzed to create various thematic maps. The integrated thematic maps were used for hazard zonation. Result shows, in inundation map most of the area falls into moderate hazard zone while southern part of the area falls into high hazard zone and the linking canal path also falls into high hazard zone. In erosion hazard map most of the area falls into moderate and low hazard zone while southern part of the study area falls into high hazard zone. Therefore from both maps it is clear that southern part of the study area which lies in Panna district of Madhya Pradesh, India is more vulnerable than the other areas.

Books etc

  • Unmanned Aerial Vehicle: Applications in Agriculture and Environment
    Avtar Ram (Editor)
    Springer 2019/10
  • Tropical forest, Geospatial Data and REDD+
    Avtar Ram (Single work)
    2017/03
  • Pankaj Kumar, Ram Avtar 
    Water Quality: Indicators, Human Impact and Environmental Health 2013/02 
    A comprehensive study of major ions, silica and isotopes was carried out to understand the geochemical processes controlling groundwater quality in coastal aquifer of Saijo plain, Western Japan. Various graphs were plotted using chemical data to enable hydrochemical evaluation of the aquifer system based on the ionic constituents, water types, hydrochemical facies, and factors controlling groundwater quality. Carbonate weathering and atmospheric precipitation are strong factors controlling the chemistry of major ions. From stable isotopic results, it was found that most of sample points plotted near the local meteoric water line (LMWL) i.e. origin of ground water is meteoric in principle; however point away from the LMWL favors exchange with rock minerals mainly salinization process. This study is crucial considering that Saijo city is known as one of the water capital of Japan and groundwater is the exclusive source of drinking water in this region. © 2013 by Nova Science Publishers, Inc. All rights reserved.
  • Water Resource Management through the Lens of Planetary Health Approach
    Pankaj Kumar, Ram Avtar (Editor)

Research Projects

  • Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research
    Date (from‐to) : 2021/04 -2025/03 
    Author : 渡邉 悌二, 古川 不可知, 韓 志昊, 渡辺 和之, 相馬 拓也, アバタル ラム
  • 日本学術振興会：科学研究費助成事業
    Date (from‐to) : 2021/04 -2024/03 
    Author : アバタル ラム
     
    This research aims to monitor the impact of large-scale biogas intervention on forest regeneration in Uttrakhand area of India. This intervention introduces biogas digesters and replaces fuelwood in 60 villages as part of a low-carbon farming initiative. The study's overarching goal is to examine the consequences of large-scale biogas interventions on forest regeneration and carbon storage in the forest surrounding villages that have adopted biogas technology as their primary source of fuel with comparable villages in the region that had not. We have processed multi-sensor remote sensing data and satellite data, clearly showing a changing forest cover pattern in the study area. Planet satellite-based vegetation data shows an increase of about 2 percent of forest cover in the areas near the villages with biogas intervention. However, it needs ground validation. We are planning to start collecting ground truth data to see the change in forest biomass based on the forest inventory data. High-resolution Planet data shows some vegetation recovery/regeneration in the study area. We are also going to conduct a questionnaire survey to identify the factors of forest recovery and how the people's socio-economic status affects the recovery of the forest in the study area. The questionnaire survey will be useful to get qualitative information about forest status and changes in people’s lifestyle after biogas intervention.
  • Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research
    Date (from‐to) : 2017/04 -2021/03 
    Author : Ishikawa Mamoru
     
    Permafrost plays an important roles for sustaining local ecosystem service since it produces water rich soils, allowing forest growth and river discharges even under the arid climatic conditions. We created high resolutive permafrost maps over Mongolia, and reconstructed transition of spring water since 1960s. The permafrost distribution was modelled with transient heat conduction and statistical-stochastic ways. The past and present states of spring activities were investigated by government maps published in 1960s, satellite images, and field surveys. Validation with deep ground temperature at multiple points showed good agreement between modelled distribution and the observations. However, they disagreed over the southern limit permafrost with ground temperature close to 0 degree. These regions overlap well with the regions experiencing significant degradation of spring water. Further researches i.e., model improvement, increasing the number of field evidences are required.

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