Biswajeet Pradhan – författare

Water, Land, and Forest Susceptibility and Sustainability, Volume 1: Geospatial Approaches & Modeling brings an interdisciplinary perspective to solving complex problems in sustainability, utilizing the latest research and technologies, and includes case studies that emphasize the applications of remote sensing, GIS, and image processing for addressing the current state and future needs to achieve sustainability. As forests, land, and water are among the most precious resources on earth, emphasizing the need to conserve them for future generations and, of course, a safe and sustainable planet. The assessment of the susceptibility of all these three precious resources must therefore be addressed to inform their sustainable management.

This 1st volume encourages adaptive activities among experts employed in interdisciplinary fields, from data mining and machine learning to environmental science by linking geospatial computational intelligence technology to forest, land and water issues.

Big Data Analytics in Agriculture focuses on the quantitative and qualitative assessment of agricultural systems using state-of-the-art technologies to deliver practical improvements in agricultural production.Addressing the challenge of translating data into real-world applications, the book provides a comprehensive mapping of the entire data lifecycle-from data generation, storage, and curation to processing and implementation. It guides readers through the steps required to produce high-quality, reliable information that supports effective decision-making. Following a logical progression, the volume demonstrates how diverse data streams converge into decision-support systems and how they can be transformed into actionable outcomes, aligned with intelligent, efficient, technologically advanced, economically viable, and politically and culturally sustainable practices.This book further explores the integration of information and communication technologies (ICT) and the Internet of Things (IoT) for managing rural assets and enhancing economic and environmental performance in spatially and temporally variable agricultural environments. Topics covered include big data analytics, data management and processing, and a range of algorithms and applications relevant to agriculture. Subtopics encompass artificial intelligence- and machine-learning-enabled smart and precision irrigation, disease and pest management, microclimatic forecasting, preventive fertigation and chemigation, data-driven smart farming through the Internet of Everything (IoE), and supply-chain analytics for improved farm-level operations.

Water, Land, and Forest Susceptibility and Sustainability, Volume 2: Insight Towards Management, Conservation and Ecosystem Services brings an interdisciplinary perspective to solving complex problems in sustainability, utilizing the latest research and technologies, and includes case studies that emphasize the applications of remote sensing, GIS, and image processing for addressing the current state and future needs to achieve sustainability. As forests, land, and water are among the most precious resources on earth, emphasizing the need to conserve them for future generations and, of course, a safe and sustainable planet. The assessment of the susceptibility of all these three precious resources must therefore be addressed to inform their sustainable management.

This second volume focuses on environmental management, conservation, and ecosystem services and provides information on forest, land, and water resources, presenting in integrated manner various aspects of their characterization, susceptibility, and sustainability.

This edited volume is based on the best papers accepted for presentation during the 1st Springer Conference of the Arabian Journal of Geosciences (CAJG-1), Tunisia 2018. The book compiles a wide range of topics addressing various issues by experienced researchers mainly from research institutes in the Mediterranean, MENA region, North America and Asia.Remote sensing observations can close gaps in information scarcity by complementing ground-based sparse data. Spatial, spectral, temporal and radiometric characteristics of satellites sensors are most suitable for features identification. The local to global nature and broad spatial scale of remote sensing with the wide range of spectral coverage are essential characteristics, which make satellites an ideal platform for mapping, observation, monitoring, assessing and providing necessary mitigation measures and control for different related Earth''s systems processes.Main topics in this book include: Geo-informatics Applications, Land Use / Land Cover Mapping and Change Detection, Emerging Remote Sensing Applications, Rock Formations / Soil Lithology Mapping, Vegetation Mapping Impact and Assessment, Natural Hazards Mapping and Assessment, Ground Water Mapping and Assessment, Coastal Management of Marine Environment and Atmospheric Sensing.

This book aims to promote the core understanding of a proper modelling of road traffic accidents by deep learning methods using traffic information and road geometry delineated from laser scanning data. The first two chapters of the book introduce the reader to laser scanning technology with creative explanation and graphical illustrations, review and recent methods of extracting geometric road parameters. The next three chapters present different machine learning and statistical techniques applied to extract road geometry information from laser scanning data. Chapters 6 and 7 present methods for modelling roadside features and automatic road geometry identification in vector data. After that, this book goes on reviewing methods used for road traffic accident modelling including accident frequency and injury severity of the traffic accident (Chapter 8). Then, the next chapter explores the details of neural networks and their performance in predicting the traffic accidents along with a comparison with common data mining models. Chapter 10 presents a novel hybrid model combining extreme gradient boosting and deep neural networks for predicting injury severity of road traffic accidents. This chapter is followed by deep learning applications in modelling accident data using feed-forward, convolutional, recurrent neural network models (Chapter 11). The final chapter (Chapter 12) presents a procedure for modelling traffic accident with little data based on the concept of transfer learning. This book aims to help graduate students, professionals, decision makers, and road planners in developing better traffic accident prediction models using advanced neural networks.

Floods and flash floods with hydro-meteorological and tropical cyclones are the some of the most devastating natural disasters causing massive damages to natural and man-made features. Flood hazards are a major threat to human life, properties (agricultural area, yield production, building and homes) and infrastructures (bridges, roads, railways, urban infrastructures, etc). Flood hazards susceptibility mapping (risk assessment) and modelling is an essential step for early warning systems, emergency services, prevention and mitigation of future environmental and social hazards and implementation of risk management strategies. Due to the lack of proper information, technology-based policies and strategies, mapping and modelling can often not be implemented to the best possible level. Geo-spatial techniques have enjoyed rising interest in recent decades among the earth environmental and social sciences research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward sustainable earth and human society. 

By linking geo-spatial computational intelligence techniques with societal and environmental-oriented problems, this book demonstrates geospatial technology approaches to data mining techniques, data analysis, modelling, risk assessment and visualization and management strategies in different aspects of flood hazards. We believe that a diverse group of academics, scientists, geographers, hydrologist, remote sensing and GIS expertise, environmentalists, meteorologists and computing experts with a common interest in geospatial sciences within the earth environmental sciences and humanistic and social sciences will find this book to be of great value.

This volume gathers the latest advances, innovations, and applications in the field of geographic information systems and unmanned aerial vehicle (UAV) technologies, as presented by leading researchers and engineers at the 2nd International Conference on Unmanned Aerial System in Geomatics (UASG), held in Roorkee, India on April 2-4, 2021. It covers highly diverse topics, including photogrammetry and remote sensing, surveying, UAV manufacturing, geospatial data sensing, UAV processing, visualization, and management, UAV applications and regulations, geo-informatics and geomatics. The contributions, which were selected by means of a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaboration among different specialists.