Earth Observation - Böcker

Remote Sensing of Ocean and Coastal Environments advances the scientific understanding and application of technologies to address a variety of areas relating to sustainable development, including environmental systems analysis, environmental management, clean processes, green chemistry and green engineering. Through each contributed chapter, the book covers ocean remote sensing, ocean color monitoring, modeling biomass and the carbon of oceanic ecosystems, sea surface temperature (SST) and sea surface salinity, ocean monitoring for oil spills and pollutions, coastal erosion and accretion measurement.

This book is aimed at those with a common interest in oceanography techniques, sustainable development and other diverse backgrounds within earth and ocean science fields. This book is ideal for academicians, scientists, environmentalists, meteorologists, environmental consultants and computing experts working in the areas of earth and ocean sciences.

Provides a comprehensive assessment of various ocean processes and their relative phenomena Includes graphical abstract and photosets in each chapter Presents literature reviews, case studies and applications

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

Earth Observation for Flood Applications: Progress and Perspectives describes the latest scientific advances in Earth Observation. With recent floods around the world becoming ever more devastating, there is a need for better science enabling more effective solutions at a fast pace. This book aims at stretching from the current flood mapping to diverse real data so as to estimate the flood risk and damage. Earth Observation for Flood Applications: Progress and Perspectives includes three parts containing each a separate but complementary topic area under floods. Each chapter unfolds various applications, case studies, and illustrative graphics. In terms of flood mapping and monitoring, the usage of multi-sensor satellite data, web-services information, microwave remote sensing methods are discussed in depth. So, this book is a valuable resource for scientists, researchers, and students in the area of earth observation. Focuses in on one specific application field of Earth Observation Brings the latest scientific advances and perspectives from experts around the world Includes extensive figures, tables, and case studies to illustrate real-life applications

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

Earth Observation Applications to Landslide Mapping, Monitoring and Modeling: Cutting-edge Approacheswith Artificial Intelligence, Aerial and Satellite Imagery focuses on the application of drone and satellite imagery for landslide mapping, monitoring, and modeling. The topics covered include the use of ultrahigh spatial resolution imagery acquired by UAVs (Unmanned Aerial Vehicles) for mapping and predicting landslide activity, the use of satellite imagery for monitoring landslide activity, the assimilation of EO (EarthObservation) data into landslide susceptibility and hazard prediction models, and the building of landslide inventories. The primary objective of this book is the advancement of the scientific understanding and application of technologies to address a variety of areas related to landslide mapping and monitoring for robust and sustainable development. Earth Observation Applications to Landslide Mapping, Monitoring and Modeling be useful for PhD students, postdoctoral researchers, professors, and scientists in geoscience.Recent developments in landslide monitoring and mapping algorithmsProvides clear and detailed case studies and methods that can be easily replicated and implemented in landslide monitoring systemsProvides detailed methods for applying research to landslide monitoring and mapping

Unmanned Aerial Systems for Monitoring Soil, Vegetation, and Riverine Environments provides an overview of how unmanned aerial systems have revolutionized our capability to monitor river systems, soil characteristics, and related processes at unparalleled spatio-temporal resolutions. This capability has enabled enhancements in our capacity to describe water cycle and hydrological processes. The book includes guidelines, technical advice, and practical experience to support practitioners and scientists in increasing the efficiency of monitoring with the help of UAS. The book contains field survey datasets to use as practical exercises, allowing proposed techniques and methods to be applied to real world case studies. Includes a summary of technical UAS issues allowing readers to focus on how the exact technology fits their scientific question Provides specific applications enabling readers to understand the benefits and threats within the field Includes a comprehensive literature review in each chapter, allowing readers to know the key players and research in the field

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

Geoinformatics for Geosciences: Advanced Geospatial Analysis using RS, GIS and Soft Computing is a comprehensive guide to the methodologies and techniques that can be used in Earth observation data assessments, geospatial analysis, and soft computing in the geosciences. The book covers a variety of spatiotemporal problems and topics in the areas of the environment, geohazards, urban analysis, health, pollution, climate change, resources and geomorphology, among others. Sections cover environmental and climate issues, analysis of geomorphological data, hazard and disaster impacts, natural and human resources, the influence of environmental conditions, geohazards, climate change, geomorphological changes, etc., and socioeconomic challenges.

Detailing up-to-date techniques in geoinformatics, this book offers in-depth, up-to-date methodologies for researchers and academics to understand how contemporary data can be combined with innovative techniques and tools in order to address challenges in the geosciences.

Focuses on a variety of interdisciplinary applications using Earth observation data, GIS, and soft computing techniques to address various challenges in the geosciences Presents both innovative techniques and specific features of the practices described, thus allowing readers to choose the most appropriate method to apply to their specific problems Comprehensively details the state-of-the-art methodologies and decision-making tools included to ensure they are easily reproduceable

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

Atmospheric Remote Sensing: Principles and Applications discusses the fundamental principles of atmospheric remote sensing and their applications in different research domains. Furthermore, the book covers the basic concepts of satellite remote sensing of the atmosphere, followed by Ionospheric remote sensing tools like Global Positioning System (GPS) and Very Low Frequency (VLF) wave. Sections emphasize the applications of atmospheric remote study in Ionospheric perturbation, fire detection, aerosol characteristics over land, ocean and Himalayan regions. In addition, the application of atmospheric remote sensing in disaster management like dust storms, cyclones, smoke plume, aerosol-cloud interaction, and their impact on climate change are discussed.

This book is a valuable reference for students, researchers and professionals working in atmospheric science, remote sensing, and related disciplines.

Covers the fundamentals of remote sensing as applied to atmospheric science Includes methods and applications of remote sensing technologies for atmospheric science and related disciplines in earth science Includes full color photographs and figures that visually represent concepts discussed in the book

Sustainable Development Perspectives in Earth Observation offers expert insight into the latest progress made in terrestrial, oceanic, and atmospheric processes, and their interlinkage in the face of changing climate using Earth observation. By addressing the use of advanced datasets, measurement techniques, modeling approaches, analytical protocols, and interpretation methods, the editors have guided the book towards key advances in understanding the evolving dynamics of ecosystems, including coasts, exposure to extreme weather events, and advances in understanding of ocean-atmosphere interactions. Those working towards sustainability through Earth observation will find that this text is a valuable resource for understanding the changing dynamics of the environment in a warming world.

Analyzes various challenges faced in agricultural research and education, crop production forecasting, agroforestry, vegetation phenology, forest cover resilience, high altitude wetlands, aerosols, greenhouse gases and coastal managementExplores ocean-atmosphere interactions, modes of climate variations, such as El Nino and Indian Ocean Dipole, extreme events, tropical cyclone, summer monsoon, and distribution of organic matter and their interlinks among various ocean-atmosphere phenomenaExamines various biogeophysical processes using Earth observation for better climate mitigation and adaptation

Remote Sensing of Soil and Land Surface Processes: Monitoring, Mapping, and Modeling couples artificial intelligence and remote sensing for mapping and modeling natural resources, thus expanding the applicability of AI and machine learning for soils and landscape studies and providing a hybridized approach that also increases the accuracy of image analysis. The book covers topics including digital soil mapping, satellite land surface imagery, assessment of land degradation, and deep learning networks and their applicability to land surface processes and natural hazards, including case studies and real life examples where appropriate.

This book offers postgraduates, researchers and academics the latest techniques in remote sensing and geoinformation technologies to monitor soil and surface processes.

Introduces object-based concepts and applications, enhancing monitoring capabilities and increasing the accuracy of mappingCouples artificial intelligence and remote sensing for mapping and modeling natural resources, expanding the applicability of AI and machine learning for soils and sediment studiesIncludes the use of new sensors and their applications to soils and sediment characterizationIncludes case studies from a variety of geographical areas

Advanced Geospatial and Ground Based Techniques in Forest Monitoring provides insights into advanced geospatial technology in the field of forestry. The book provides both traditional and special techniques for monitoring the forest, including biophysical and biochemical parameters, retrieval, species identification, mapping, and classification. In addition, it covers the latest technologies using SAR data, hyperspectral data, and the integration of datasets for the enhanced accuracy of the results and its outcome. This book will benefit the academic and research communities with the latest research ideas and problem-solving skills in forestry and land management.Includes the application of EO data for forest monitoring in both natural resources mapping and forest sustainable managementPresents advancements in geospatial technology using multispectral, hyperspectral, radar microwave, and LIDAR data in forest monitoring and its parameter retrievalCovers upcoming satellite missions for forest monitoring

Deep Learning for Multi-Sensor Earth Observation addresses the need for transformative Deep Learning techniques to navigate the complexity of multi-sensor data fusion. With insights drawn from the frontiers of remote sensing technology and AI advancements, it covers the potential of fusing data of varying spatial, spectral, and temporal dimensions from both active and passive sensors. This book offers a concise, yet comprehensive, resource, addressing the challenges of data integration and uncertainty quantification from foundational concepts to advanced applications. Case studies illustrate the practicality of deep learning techniques, while cutting-edge approaches such as self-supervised learning, graph neural networks, and foundation models chart a course for future development.Structured for clarity, the book builds upon its own concepts, leading readers through introductory explanations, sensor-specific insights, and ultimately to advanced concepts and specialized applications. By bridging the gap between theory and practice, this volume equips researchers, geoscientists, and enthusiasts with the knowledge to reshape Earth observation through the dynamic lens of deep learning.Addresses the problem of unwieldy datasets from multi-sensor observations, applying Deep Learning to multi-sensor data integration from disparate sources with different resolution and qualityProvides a thorough foundational reference to Deep Learning applications for handling Earth Observation multi-sensor data across a variety of geosciencesIncludes case studies and real-world data/examples allowing readers to better grasp how to put Deep Learning techniques and methods into practice

Remote Sensing, Big Data, and GeoAI: Exploring Applications with Geospatial Insights is an in-depth analysis of the transformative power of AI and Big Data in remote sensing. This book provides readers with the knowledge and tools to utilize these technologies to enhance decision-making and analysis. Starting from fundamental concepts, it progresses to advanced applications, offering accessible explanations and real-world examples to bridge the gap between theory and practice. The book uses a structured format to balance theoretical knowledge with immersive case studies, giving readers a deeper understanding of practical implications.It also covers ethical and legal considerations, making it an invaluable resource for researchers, professionals, and students keen on using AI and Big Data techniques in remote sensing to solve complex geospatial challenges.Provides a full review of the development of Big Data and AI for remote sensing technologies, elucidating on how we have begun to incorporate data and methods, and highlighting potential areas of growthApproaches the content from a practical but immersive angle, allowing readers to understand common data and methodological approaches with real world examplesIncludes chapters on emerging topics of consideration, including the ethics/legality of using AI in remote sensing and how we teach such complex topics to students

Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications explores a wide range of transformative data fusion techniques of Artificial Intelligence (AI) technologies applied to Google Earth Engine (GEE) techniques. It includes a wide range of scientific domains that can utilize remote sensing and geographic information systems (GIS) through detailed case studies. This book delves into the challenges of AI-driven tools and technologies for Earth observation data analysis, offering possible solutions and directly addressing current and upcoming needs within Earth observation. Google Earth Engine and Artificial Intelligence for Earth Observation: Algorithms and Sustainable Applications is a useful reference for geospatial scientists, remote sensing experts, and environmental scientists utilizing remote sensing to apply the latest AI techniques to data obtained from GEE for their research and teaching.Includes utilization of AI with GEE tools for a spectrum of scientific domains in remote sensing and geographic information systems (GIS) including natural hazard assessment, aquatic and hydrological applications, and forest coverHighlights the challenges and possible solutions for AI-driven tools and technologies for Earth observation data analysisIncludes detailed case studies showing specific considerations and exceptions for applications of AI in GEE for Earth observation

Harnessing Earth Observation for Coastal Engineering addresses the intersection of cutting-edge geoinformatics technologies and coastal engineering to tackle challenges in coastal processes and natural hazards. By offering robust methodologies and algorithms, the book equips students, researchers, and engineers with practical tools for immediate application. The global, real-world case studies provide insights into diverse decision-making tools and global perspectives on geoinformatics in coastal engineering and examples of the methodology in action. It goes on to promote protection and resilience by integrating geoinformatics seamlessly into coastal engineering practices, advancing knowledge and practice in the field.Users will find a great resource that not only addresses the pressing need for leveraging modern remote sensing and GIS technologies but also provides a blend of research insights and practical applications exploring advanced algorithms and techniques, allowing readers to effectively utilize new sensor data, extract vital information, and implement sustainable solutions in coastal zones worldwide.Explores cutting-edge trends and technologies in Geoinformatics for addressing challenges in coastal engineeringIncludes robust methodologies and algorithms that are ready for immediate application, leveraging Earth observation technologies into practical toolsProvides real-world case studies spanning the globe, showcasing diverse decision-making tools in action and global perspectives on geoinformatics in coastal engineering

Integrative Sensing Strategies for Disaster Management explores the synergy between airborne remote sensing and social data in addressing disaster management. The book provides a framework for leveraging diverse data sources to enhance response and resilience. Detailed chapters cover the fundamentals of remote sensing, data integration techniques, and ethical implications, showcasing practical case studies in urban flooding, air quality monitoring, and pandemic evaluation. The book is an essential resource for postgraduates, PhD students, researchers, and professors in Earth observation and disaster management.Users will find this book to be a great resource for advancing their understanding of integrated sensing technologies, including current challenges and emerging trends, and tactics on how to implement innovative solutions.Provides an integrated approach to remote sensing technologies, combining airborne remote sensing with social data analyticsOffers readers a unique perspective on leveraging multiple geospatial data sources for enhanced disaster management and resilienceIncludes practical case studies that demonstrate the applications of integrated sensing technologies across a variety of areasAddresses the broader implications and responsibilities associated with using advanced sensing technologies in disaster management

Advances in Computational Geomechanics: Advanced Computational Techniques and Methodologies in Geotechnical Engineering provides a comprehensive overview of cutting-edge computational methodologies in geotechnical engineering. The first part examines stochastic, probabilistic, and reliability analyses in geotechnical engineering, covering stochastic methods, probabilistic approaches to soil characterization, reliability analysis in geotechnical design, and risk assessment and management in geotechnical projects. The second part delves into artificial intelligence (AI) and machine learning applications in geotechnical engineering, including machine learning algorithms for geotechnical data analysis, AI-based predictive models for soil behavior and properties, AI in geotechnical risk and decision-making, and data-driven approaches for soil classification and site characterization. The third part focuses on numerical modeling and analysis techniques, such as the Finite Element Method (FEM), Finite Difference Method (FDM), Discrete Element Method (DEM), and explores hybrid numerical methods and future directions in computational geomechanics. This book serves as a valuable resource for geotechnical engineers, researchers, and practitioners seeking to leverage advanced computational tools for geomechanical analyses and design.Examines a wide range of topics, covering contemporary computational geomechanics and the latest advancements in geotechnical engineeringReviews both theoretical foundations and practical insightsProvides real-world case studies and examples to illustrate the practical applications of discussed methodologiesIntegrates knowledge from various disciplines, making it relevant to a broad audience within geotechnical engineering and beyond

Health Geography: Innovative Geospatial Epidemiology presents a comprehensive exploration of the fundamental principles and methodologies underpinning remote sensing for spatial epidemiology. Organised in two parts, the first delves into the methodology of utilizing cutting-edge remote sensing technologies to detect, analyze, and predict the spatial distribution of infectious diseases through the process of extracting critical information and creating accurate geospatial models for disease mapping and monitoring. The second part provides numerous case studies that illustrate the real-world applications and transformative potential of the interdisciplinary approaches, allowing the book to bridge the gap between theoretical knowledge and practical implementation. Health Geography is an indispensable resource for researchers, practitioners, and graduate students in spatial epidemiology, geospatial sciences, and geostatistics seeking to utilize the potential of remote sensing technologies in tackling spatial epidemiological challenges.Provides Earth Observation techniques to analyze spatial data and space-time variations in disease incidencesDelivers methodology for digital image processing, analysis and processing of primary data for monitoring, analyzing and spatiotemporal prediction of possible outbreaksIncludes a section of case studies on the use of remote sensing technologies for specific techniques, models and workflows to deal with disease

Multimodal Remote Sensing Data Fusion for Classification: Algorithms and Applications offers a comprehensive overview of Earth observation data fusion, focusing on multimodal remote sensing. It presents state-of-the-art algorithms and practical applications that enhance understanding of Earth's dynamic processes. Through detailed analysis, case studies, and practical examples, this book equips readers with the necessary tools to effectively utilize multimodal data fusion for land cover and land use classification, as well as environmental monitoring, making it an invaluable resource for those in remote sensing and Earth sciences.Furthermore, the book is tailored for Masters and Doctorate students, scientists, and professionals in remote sensing, geography, and Earth sciences. It delves into the integration and analysis of multimodal remote sensing data, offering insights into sustainable solutions for environmental challenges. This comprehensive coverage ensures readers are well-versed in the cutting-edge techniques and methodologies required for advanced Earth observation and classification tasks.Provides a holistic overview of Multimodal Remote Sensing, from data acquisition, preprocessing, fusion techniques, analysis methodologies, and diverse applicationsIncludes real-world case studies and examples, showcasing the application of multimodal remote sensing in various fieldsEmphasizes future perspectives and emerging technologies, providing readers with forward-thinking applications and their potential impact on the field

Carbon Fluxes and Biophysical Variables from Earth Observation: Methods for Ecosystem Assessment transforms the way remote sensing data can be used to approach monitoring of carbon fluxes (CF) and biophysical variables (BV) in ecosystem and global vegetation monitoring. In a field where these two subjects have traditionally been treated as distinct entities, this book offers an integrated exploration of CF and BV retrieval through remote sensing. It not only delves into a wide array of approaches and methodologies but also assists readers in selecting the most suitable models based on available inputs and spatiotemporal scales. Carbon Fluxes and Biophysical Variables from Earth Observation is a useful resource for Earth Observation specialists, particularly in Remote Sensing, machine learning, ecology, and plant physiology, to enhance and adapt their approaches and methodologies.Provides multidisciplinary approaches to the use of remote sensing for monitoring carbon fluxes and biophysical variablesEnables deeper understanding and monitoring of ecosystems and dynamics from Earth observation technologiesIncludes in-situ, local scale, and global methods to provide readers with techniques and applications for a wide spectrum of needs

Remote Sensing at Night: Technologies, Applications, and Perspectives delves into the pivotal role of remote sensing in deciphering Earth's nocturnal landscapes. This comprehensive resource utilizes a range of case studies to make complex topics accessible to a diverse audience with varied scientific backgrounds. The book emphasizes recent advances in remote sensing technology, encompassing nightlight, thermal infrared, and Synthetic Aperture Radar (SAR) capabilities facilitated by state-of-the-art Earth observation satellites. The book also explores the technological advancements in nighttime monitoring for practical and research purposes, Earth observation datasets, and the challenges faced. It equips readers with multidisciplinary knowledge and practical solutions for nighttime monitoring, providing up-to-date global case studies and methodologies for researchers, graduate students, scientists, and academics in remote sensing, geospatial research, and environmental science.Written with interdisciplinarity in mind, and in easy to understand language, allowing a wide variety of career levels and subject specialties to understand and implement techniquesApproaches the content with a dual orientation, both in innovative techniques and in specific features of local and global technologies, together with the required adaptations for the best-fitting technologyIncludes detailed case studies that are templated for ease of viewing, along with guided methods for easy replication

Utilizing Earth Observation Data in Reaching Sustainable Development Goals explores the transformative potential of Earth observation data through case studies showcasing its pivotal role in achieving Sustainable Development Goals (SDGs) in developing regions. The book begins with a historical and theoretical overview of EO data missions, then shifts to actionable SDGs, highlighting successes, challenges, and lessons learned. This comprehensive work delves into the dynamic interplay between technology and sustainability. The book utilizes a consistent template for each chapter, exploring instances where satellite imagery, remote sensing, and geospatial analytics converge to provide actionable insights.It emphasizes both achievements and obstacles, offering practical solutions and strategies for effective implementation.Provides detailed case studies of Earth observation data in developing regions, templated for ease of referenceIncludes clear references to which SDGs are addressed by each Earth observation techniqueSets out clear data extraction procedures that facilitate readers to explore similar EO data sources and be able to reproduce the techniques

Earth Observation using Scatterometers: State-of-the-Art Techniques, Applications, and Challenges explores the critical role scatterometers play in addressing natural disasters, climate action, and food security. It provides comprehensive guidance on leveraging scatterometers for real-time applications, including advanced techniques like super-resolution mapping and multi-source data fusion. This book is an essential resource for understanding the challenges and opportunities of scatterometer satellite datasets. In addition to covering the latest advancements in algorithms and emerging applications, it empowers professionals to efficiently analyze vast amounts of Earth observation data.The book addresses scatterometers' expanding applicability in oceanography, agriculture, the cryosphere, and related Earth-science fields, making it invaluable for scientists, geospatial data analysts, and students of Remote Sensing and Geoscience.Provides detailed instruction on the applications of scatterometers to a wide range of Earth sciences, including benefits and case studies showing real world useCovers the use of scatterometers in analyzing and responding to natural disasters, including analysis of sea-ice melt, cyclone predictions, etc.Includes techniques for monitoring the cryosphere and global climate, with dedicated methodology and data analysis

The Geoinformatics Frontier: AI, Big Data, and Crowdsourced Technologies tackles the critical challenge of integrating Geoinformatics, AI, Big Data, and VGI; offering a comprehensive introduction to these pivotal concepts, the book elucidates their foundations and relevance to Geoinformatics. It approaches builds on the theory discussed with practical guidance, examples, and detailed case studies; equipping readers with the knowledge needed to effectively implement them. The book presents case studies spanning various sectors, showcasing how the technologies can be successfully employed to address intricate spatial issues and facilitate well-informed decision-making for the complexities of managing large-scale spatial datasets. It also provides indispensable insights into data collection, storage, quality control, and fusion techniques, offering practical solutions to the challenges of data storage, processing, and analysis. The Geoinformatics Frontier serves as an indispensable guide, bridging the gap in understanding and practice for geospatial scientists, empowering readers to harness the transformative potential of Geoinformatics and advanced computer technologies.Provides comprehensive of the integration of AI, Big Data, and Volunteered Geographic Information (VGI) in Geoinformatics, providing a solid foundation of knowledge and practical insightsIncorportates practical examples and detailed case studies throughout the chapters, allowing readers to see successful implementations, understand the challenges faced, and identify opportunities for their own projectsIncludes considerations for ethics and responsible implementation of AI, Big Data, and VGI, fostering a deeper understanding of the implications of these technologies and tools needed to ensure responsible practices

Data-Driven Earth Observation for Disaster Management: From Theory to Practical Applications delves into the critical role of Earth observation data and technologies in predicting, managing, and mitigating a spectrum of disasters. With a multidisciplinary approach encompassing geography and geospatial science, the book addresses the challenges of comprehending and managing disasters in our rapidly changing world. Offering solutions through insights into early detection, prediction, management, and prevention, it provides strategies for understanding Earth surface changes and the application of Earth Observation technologies. Readers will gain understanding on how to use Earth observation data and techniques in studying different domains of disaster management.Chapters follow a consistent format, featuring introductory summaries, key takeaways, and a focus on the role of Earth observation, enhancing both comprehensibility and searchability. The book also includes case studies and practical applications of Earth observation technologies, providing context and demonstrating the tangible impact of the techniques covered.Provides a systematic and holistic understanding of how to use Earth observation data and techniques in disaster managementIncludes empirical research examples and case studies to better emphasize theoretical concepts via real-world examplesUtilizes sharable data and workflows in analytical contexts so that techniques and examples presented can be practically replicated

Models and Methods for Synthetic Aperture Radar Remote Sensing: From Physics to Applications expansively outlines the use of SAR remote sensing in Earth Observation, offering state-of-the-art methodologies, broad applications and use cases, and a multidisciplinary approach. It explores basic and advanced methods, accompanied by practical applications and case studies, fostering a deep understanding and facilitating real-world problem solving in Earth Observation. Models and Methods for Synthetic Aperture Radar Remote Sensing provides invaluable insights into SAR technologies, enhancing research quality and relevance through reproducible methodology for Earth Observation and remote sensing researchers and academics, or Earth and Environmental scientists employing remote sensing techniques.State-of-the-art methodologies ensure readers understand the most current and effective approaches for SAR remote sensing and Earth ObservationA multidisciplinary approach promotes holistic understanding, collaboration, and innovative solutions in Earth ObservationPractical applications and case studies demonstrate real-world relevance, aiding in application and problem-solvingDetailed, tailored methodology provides detailed explanations facilitating replication, adaptation, reproducibility, and field advancement