Prem Chandra Pandey - Böcker

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

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

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.

Remote Sensing for Vegetation Monitoring: Technologies, Applications and Models provides insight on the pivotal role that remote sensing plays in vegetation monitoring. As traditional field assessments face challenges due to inaccessible study sites and lengthy data collection, this book offers a comprehensive view of remote sensing applications for monitoring various vegetation ecosystems, including forests, grasslands, mangroves, and agriculture. The book presents a coherent and consistent structure, across five sections that build upon prior knowledge and detail the quantitative and qualitative assessments made possible through remote sensing technologies. Remote Sensing for Vegetation Monitoring: Technologies, Applications and Models caters to a diverse audience, including researchers and practitioners seeking to navigate the evolving landscape of vegetation monitoring through case studies, new algorithms and state-of-the-art methods.Provides the latest remote sensing techniques applied in all aspects of vegetation monitoring including forests, agriculture, grassland, phytoplankton, and mangrovesChapters are well-integrated and interdisciplinary, with consistent quality and continuityIncludes recent, practical case studies across major global geographies that are formatted to be easily understood and reproduced

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.

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 covers the quantification of forests, grasslands, and woodlands ecosystem services from the supply side (e.g., regulatory and provisioning services) to the demand side, including human cultural needs. The Millennium Ecosystem Assessment (MA, 2005) defines ecosystem services as simply the benefits that are derived from ecosystems for human well-being (Board 2005). The report has documented that ecosystems have contributed more than 50% of the world's GDP. However, as a result of climate change and anthropogenic impacts, about 60% of the world's ecosystem services have been degraded. This significant reduction of services has serious consequences on food production, climate regulation, and net primary production, among other services which directly affect human well-being. In order to appreciate the benefits of various ecosystems to humanity and monitor their degradation, a systematic quantification of ecosystem services and their change in both time and space is critical. In particular, there is a need to characterize the ecological infrastructures, processes, and ecosystem functions that underpin the ecosystem services in ways that can be evaluated and tracked (Potschin and Haines-Young 2016). In addition, various intervention measures to restore degraded ecosystems require constant and accurate measurement of the ecosystem characteristics in order to assess the benefits of ecological restoration.Vegetation in particular provides a number of provisioning (forage production, food), regulatory (climate, temperature), supporting (primary production, nutrient cycling), and cultural (educational, recreation) ecosystem services as well as biodiversity maintenance (Masenyama et al. 2022). Remote sensing data contributes significantly to mapping, modeling, and quantitative valuation of the ecosystem services in a spatially explicit manner. It provides an opportunity to use standard protocols at various spatial scales as well as wall-to-wall mapping of phenomena through time, which is critical for monitoring on a continuous basis.