Prashant K. Srivastava – författare

Hyperspectral Remote Sensing: Theory and Applications offers the latest information on the techniques, advances and wide-ranging applications of hyperspectral remote sensing, such as forestry, agriculture, water resources, soil and geology, among others. The book also presents hyperspectral data integration with other sources, such as LiDAR, Multi-spectral data, and other remote sensing techniques. Researchers who use this resource will be able to understand and implement the technology and data in their respective fields. As such, it is a valuable reference for researchers and data analysts in remote sensing and Earth Observation fields and those in ecology, agriculture, hydrology and geology.

Includes the theory of hyperspectral remote sensing, along with techniques and applications across a variety of disciplines Presents the processing, methods and techniques utilized for hyperspectral remote sensing and in-situ data collection Provides an overview of the state-of-the-art, including algorithms, techniques and case studies

Sensitivity Analysis in Earth Observation Modeling highlights the state-of-the-art in ongoing research investigations and new applications of sensitivity analysis in earth observation modeling. In this framework, original works concerned with the development or exploitation of diverse methods applied to different types of earth observation data or earth observation-based modeling approaches are included. An overview of sensitivity analysis methods and principles is provided first, followed by examples of applications and case studies of different sensitivity/uncertainty analysis implementation methods, covering the full spectrum of sensitivity analysis techniques, including operational products. Finally, the book outlines challenges and future prospects for implementation in earth observation modeling.

Information provided in this book is of practical value to readers looking to understand the principles of sensitivity analysis in earth observation modeling, the level of scientific maturity in the field, and where the main limitations or challenges are in terms of improving our ability to implement such approaches in a wide range of applications. Readers will also be informed on the implementation of sensitivity/uncertainty analysis on operational products available at present, on global and continental scales. All of this information is vital in the selection process of the most appropriate sensitivity analysis method to implement.

Outlines challenges and future prospects of sensitivity analysis implementation in earth observation modeling Provides readers with a roadmap for directing future efforts Includes case studies with applications from different regions around the globe, helping readers to explore strengths and weaknesses of the different methods in earth observation modeling Presents a step-by-step guide, providing the principles of each method followed by the application of variants, making the reference easy to use and follow

Satellite Soil Moisture Retrieval: Techniques and Applications offers readers a better understanding of the scientific underpinnings, development, and application of soil moisture retrieval techniques and their applications for environmental modeling and management, bringing together a collection of recent developments and rigorous applications of soil moisture retrieval techniques from optical and infrared datasets, such as the universal triangle method, vegetation indices based approaches, empirical models, and microwave techniques, particularly by utilizing earth observation datasets such as IRS III, MODIS, Landsat7, Landsat8, SMOS, AMSR-e, AMSR2 and the upcoming SMAP.

Through its coverage of a wide variety of soil moisture retrieval applications, including drought, flood, irrigation scheduling, weather forecasting, climate change, precipitation forecasting, and several others, this is the first book to promote synergistic and multidisciplinary activities among scientists and users working in the hydrometeorological sciences.

Demystifies soil moisture retrieval and prediction Links soil moisture retrieval techniques with new satellite missions for earth and environmental science oriented problems Written to be accessible to a wider range of professionals with a common interest in geo-spatial techniques, remote sensing, sustainable water resource development, and earth and environmental issues

Agricultural Water Management: Theories and Practices advances the scientific understanding, development and application of agricultural water management through an integrated approach. This book presents a collection of recent developments and applications of agricultural water management from advanced sources, such as satellite, mesoscale and climate models that are integrated with conceptual modeling systems. Users will find sections on drought, irrigation scheduling, weather forecasting, climate change, precipitation forecasting, and more. By linking these systems, this book provides the first resource to promote the synergistic and multidisciplinary activities of scientists in hydro-meteorological and agricultural sciences.

As agricultural water management has gained considerable momentum in recent decades among the earth and environmental science communities as they seek solutions and an understanding of the concepts integral to agricultural water management, this book is an ideal resource for study and reference.

Presents translational insights into drought, irrigation scheduling, weather forecasting, climate change and precipitation forecasting Advances the scientific understanding, development and application of agricultural water management Integrates geo-spatial techniques, agriculture, remote sensing, sustainable water resource development, applications and other diverse areas within earth and environmental, meteorological and hydrological sciences

GPS and GNSS Technology in Geosciences offers an interdisciplinary approach to applying advances in GPS/GNSS technology for geoscience research and practice. As GPS/GNSS signals can be used to provide useful information about the Earth's surface characteristics and land surface composition, GPS equipment and services for commercial purposes continues to grow, thus resulting in new expectations and demands. This book provides case studies for a deeper understanding of the operation and principles of widely applied approaches and the benefits of the technology in everyday research and activities. Presents processing, methods and techniques of GPS/GNSS implementation that are utilized in in-situ data collection in design and systems analysis Offers an all-inclusive, critical overview of the state-of-the-art in different algorithms and techniques in GPS/GNSS Addresses both theoretical and applied research contributions on the use of this technology in a variety of geoscience disciplines

Radar Remote Sensing: Applications and Challenges advances the scientific understanding, development, and application of radar remote sensing using monostatic, bistatic and multi-static radar geometry. This multidisciplinary reference pulls together a collection of the recent developments and applications of radar remote sensing using different radar geometry and platforms at local, regional and global levels.

Radar Remote Sensing is for researchers and practitioners with earth and environmental and meteorological sciences, who are interested in radar remote sensing in ground based scatterometer and SAR systems; air borne scatterometer and SAR systems; space borne scatterometer and SAR systems.

Covers monostatic, bistatic and multi-static radar geometry Features case studies, including experimental investigations, for practical application Includes geophysical, oceanographical, and meteorological Synthetic Aperture Radar data

Remote Sensing in Precision Agriculture: Transforming Scientific Advancement into Innovation compiles the latest applications of remote sensing in agriculture using spaceborne, airborne and drones' geospatial data. The book presents case studies, new algorithms and the latest methods surrounding crop sown area estimation, determining crop health status, assessment of vegetation dynamics, crop diseases identification, crop yield estimation, soil properties, drone image analysis for crop damage assessment, and other issues in precision agriculture. This book is ideal for those seeking to explore and implement remote sensing in an effective and efficient manner with its compendium of scientifically and technologically sound information. Presents a well-integrated collection of chapters, with quality, consistency and continuity Provides the latest RS techniques in Precision Agriculture that are addressed by leading experts Includes detailed, yet geographically global case studies that can be easily understood, reproduced or implemented Covers geospatial data, with codes available through shared links

Earth Observation for Monitoring and Modeling Land Use presents a practical guide and theoretical overview of the latest techniques and Earth observation technologies applied to land use and land cover change through qualitative assessment of Earth observation technologies. The book's chapters include detailed case studies, Earth observation datasets, and detailed applications of the technologies covered that are presented in a way that each chapter is a self-contained guide on a specific application of Earth observation technologies to land use problems, ensuring all technical and background information is provided on each subject without the need for cross-referencing or searching for other sources.The book spatializes the understanding of monitoring land cover and use, and quantifies the challenges faced, allowing analysis of the dynamics of the territory in terms of occupation processes, land use, and its transformations. It focuses on practical applications of using remote sensing and modeling that support new research in relation to monitoring of land use and spectral modelling, elucidating the importance of advanced methodologies in the coverage and use mappings of the Earth.Focuses on a variety of interdisciplinary applications using Earth observation data, technologies, and machine learning techniques to address various challenges in land use changeIncludes detailed application-specific discussions that allow readers to understand the different applications of tools aimed at observing the Earth's surfaceCovers theoretical and applied research contributions, along with background information on the use of current technologies applied to land use and land resourcesPresents summaries of technical information and data handling that will enable readers to understand the key benefits of Earth observation technologies in respect to land use

Earth Observation in Urban Monitoring: Techniques and Challenges presents the latest techniques of remote sensing in urban monitoring, along with methods for quantitative and qualitative assessment using state-of-the-art Earth observation technologies. The book details the advances of remote sensing technologies in urban environmental monitoring for a range of practical and research applications, Earth observation datasets, remote sensing of environmental considerations, geostatistical techniques and resilience perspectives. Chapters cover sensor applications, urban growth modelling, SAR applications, surveying techniques, satellite time series analysis and a variety of other remote sensing technologies for urban monitoring.

Each chapter includes detailed case studies at a variety of scales and from a variety of geographies, offering up-to-date, global, urban monitoring methodologies for researchers, scientists and academics in remote sensing, geospatial research, environmental science and sustainability.

Focuses on a variety of interdisciplinary applications using Earth observation data, GIS and soft computing techniques to address various challenges in urban monitoring Provides numerous case studies at a variety of scales, from local to global, to aid readers in implementing urban monitoring techniques at any level Includes theoretical and applied research contributions along with background information on the use of concurrent technologies in the disciplines of urban studies

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. The 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.

Introduces readers to the evolution from conventional analytical approaches to large-scale analytical paradigms through a stepwise, sectioned framework that supports progressive skill developmentExamines practical considerations surrounding storage architectures, multi-source datasets, scalability constraints, and cost trade-offs in agricultural computing environmentsDetails algorithm-centric workflows, including feature construction, model calibration, and comparative performance evaluation across diverse agricultural contextsShowcases a wide range of sector-specific implementations, covering crop monitoring, irrigation planning, weed control, nutrient stress identification, climate assessment, pest detection, and agri-food supply-chain operations in both advanced and resource-limited settings

This book advances the scientific understanding, development, and application of geospatial technologies related to water resource management. It presents recent developments and applications specifically by utilizing new earth observation datasets such as TRMM/GPM, AMSR E/2, SMOS, SMAP and GCOM in combination with GIS, artificial intelligence, and hybrid techniques. By linking geospatial techniques with new satellite missions for earth and environmental science, the book promotes the synergistic and multidisciplinary activities of scientists and users working in the field of hydrological sciences.

This book collates traditional and modern applications of remote sensing in aquatic ecosystem monitoring. It covers conventional assessment methods like sampling, surveying, macroinvertebrates, and chlorophyll estimation for aquatic ecosystem health assessment. Advanced remote sensing technology provides timely spectral information for quantitative and qualitative assessment of water quality, shoreline changes, coral bleaching, and vegetation monitoring. The book covers different types of aquatic ecosystems like wetlands, rivers, lakes, saline, and the brackish lake. It also:Reviews the latest applications of remote sensing in the monitoring and assessment of aquatic ecosystemsIncludes traditional methods like cartography, sampling, surveying, phytoplankton assessment, river interlinking, and chlorophyll estimationDiscusses the application of multi-source data and machine learning in monitoring aquatic ecosystemsDiscusses aquatic ecosystem management, services, threats, and sustainabilityExplores challenges, opportunities, and prospects of future Earth observation applications for aquatic ecosystem monitoringThe book discusses space-borne, airborne, and drone geospatial data. The parts broadly cover aquatic ecosystem monitoring, vegetation management, advanced modeling practices, and challenges. It is meant for scientists, professionals, and policymakers working in environmental sciences, remote sensing, and geology.

A comprehensive guide to managing and mitigating natural disasters   Recent years have seen a surge in the number, frequency, and severity of natural disasters, with further increases expected as the climate continues to change. However, advanced computational and geospatial technologies have enabled the development of sophisticated early warning systems and techniques to predict, manage, and mitigate disasters.Techniques for Disaster Risk Management and Mitigation explores different approaches to forecasting disasters and provides guidance on mitigation and adaptation strategies.Volume highlights include:  Review of current and emerging technologies for disaster predictionDifferent approaches to risk management and mitigationStrategies for implementing disaster plans and infrastructure improvementsGuidance on integrating artificial intelligence with GIS and earth observation dataExamination of the regional and global impacts of disasters under climate variability

The objective of this publication is to provide insight into advancing remote sensing techniques dealing with floods, droughts, landslides, earthquakes, permafrost-related hazards, glacial lake outburst floods, forest fires, droughts, tropical cyclones, climate resilience and COVID-19.

The objective of this publication is to provide insight into advancing remote sensing techniques dealing with floods, droughts, landslides, earthquakes, permafrost-related hazards, glacial lake outburst floods, forest fires, droughts, tropical cyclones, climate resilience and COVID-19. This publication will incorporate the latest technologies and techniques to illustrate disaster monitoring for acquiring information and dissemination of technological results and outcomes for the betterment of society. This publication would be of immense importance for earth scientists, policymakers and professionals working in the field of disaster risk reduction.

This book provides insight into advancing GIS and remote sensing technology in the field of mangrove ecosystem monitoring, offering traditional as well as advanced techniques for mangrove types, biophysical and biochemical parameters, retrieval, species identification, mapping classification, machine learning, physics-based approaches, challenges, and the way forward. This will incorporate the latest technology to derive biophysical and biochemical parameters using SAR data, hyperspectral data, and integration of data sets for the enhanced accuracy of the results and outcome. It also presents the advancement of geospatial technology using multispectral, hyperspectral, radar microwave, and LiDAR data in mangrove monitoring. The book will benefit academics and the research community with the latest research ideas, problem-solving skills, and future perspectives in forestry monitoring to aid mangrove-related developments globally. It is intended for marine ecologists, climate change scientists, universities, governments, industries, developers of sensors and other sophisticated tools for mangrove monitoring, and policymakers.

Remote Sensing Applications in Environmental Research is the basis for advanced Earth Observation (EO) datasets used in environmental monitoring and research. Now that there are a number of satellites in orbit, EO has become imperative in today’s sciences, weather and natural disaster prediction. This highly interdisciplinary reference work brings together diverse studies on remote sensing and GIS, from a theoretical background to its applications, represented through various case studies and the findings of new models. The book offers a comprehensive range of contributions by well-known scientists from around the world and opens a new window for students in presenting interdisciplinary and methodological resources on the latest research. It explores various key aspects and offers state-of-the-art research in a simplified form, describing remote sensing and GIS studies for those who are new to the field, as well as for established researchers.

Remote Sensing Applications in Environmental Research is the basis for advanced Earth Observation (EO) datasets used in environmental monitoring and research. Now that there are a number of satellites in orbit, EO has become imperative in today’s sciences, weather and natural disaster prediction. This highly interdisciplinary reference work brings together diverse studies on remote sensing and GIS, from a theoretical background to its applications, represented through various case studies and the findings of new models. The book offers a comprehensive range of contributions by well-known scientists from around the world and opens a new window for students in presenting interdisciplinary and methodological resources on the latest research. It explores various key aspects and offers state-of-the-art research in a simplified form, describing remote sensing and GIS studies for those who are new to the field, as well as for established researchers.

Computational intelligence techniques have enjoyed growing interest in recent decades among the earth and environmental science research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward a sustainable earth. This book compiles a collection of recent developments and rigorous applications of computational intelligence in these disciplines. Techniques covered include artificial neural networks, support vector machines, fuzzy logic, decision-making algorithms, supervised and unsupervised classification algorithms, probabilistic computing, hybrid methods and morphic computing. Further topics given treatment in this volume include remote sensing, meteorology, atmospheric and oceanic modeling, climate change, environmental engineering and management, catastrophic natural hazards, air and environmental pollution and water quality. By linking computational intelligence techniques with earth and environmental science oriented problems, this book promotes synergistic activities among scientists and technicians working in areas such as data mining and machine learning. We believe that a diverse group of academics, scientists, environmentalists, meteorologists and computing experts with a common interest in computational intelligence techniques within the earth and environmental sciences will find this book to be of great value.

Computational intelligence techniques have enjoyed growing interest in recent decades among the earth and environmental science research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward a sustainable earth. This book compiles a collection of recent developments and rigorous applications of computational intelligence in these disciplines. Techniques covered include artificial neural networks, support vector machines, fuzzy logic, decision-making algorithms, supervised and unsupervised classification algorithms, probabilistic computing, hybrid methods and morphic computing. Further topics given treatment in this volume include remote sensing, meteorology, atmospheric and oceanic modeling, climate change, environmental engineering and management, catastrophic natural hazards, air and environmental pollution and water quality. By linking computational intelligence techniques with earth and environmental science oriented problems, this book promotes synergistic activities among scientists and technicians working in areas such as data mining and machine learning. We believe that a diverse group of academics, scientists, environmentalists, meteorologists and computing experts with a common interest in computational intelligence techniques within the earth and environmental sciences will find this book to be of great value.