Monitoring drought’s slow evolution and identifying the end of a drought is still a big challenge for scientists, natural resource managers, and decision makers. This comprehensive two-volume set with contributions from over 200 experts, and featuring case studies representing numerous countries throughout the world, discusses different aspects of drought from types, indices, and forecasting to monitoring, modeling, and mitigation measures. It also addresses how climate change is impacting drought and decision-making concluding with lessons learned about science, policy, and managing uncertainty. Features: Provides a global perspective on drought prediction and management and a synthesis of the recent state of knowledge. Covers a wide range of topics from essential concepts and advanced techniques for forecasting and modeling drought to societal impacts, consequences, and planning Presents numerous case studies with different management approaches from different regions and countries. Addresses how climate change impacts drought, the increasing challenges associated with managing drought, decision making, and policy implications. Includes contributions from hundreds of experts around the world. Professionals, researchers, academics, and postgraduate students with knowledge in Environmental Sciences, Ecology, Agriculture, Forestry, Hydrology, Water Resources Engineering, and Earth Sciences, as well as those interested in how climate change impacts drought management, will gain new insights from the experts featured in this two-volume handbook.

This book describes recent advances in radiative transfer, atmospheric remote sensing, polarization optics of random media, and light scattering. It is a valuable resource for anyone involved in light scattering research. Providing numerous step-by-step tutorials, it allows readers to quickly learn about various aspects of theoretical and experimental light scattering media optics. The book features among others a chapter on aerosol remote sensing that helps readers to define and solve various aerosol remote sensing problems.

This book discusses various statistical models and their implications for developing landslide susceptibility and risk zonation maps. It also presents a range of statistical techniques, i.e. bivariate and multivariate statistical models and machine learning models, as well as multi-criteria evaluation, pseudo-quantitative and probabilistic approaches. As such, it provides methods and techniques for RS & GIS-based models in spatial distribution for all those engaged in the preparation and development of projects, research, training courses and postgraduate studies. Further, the book offers a valuable resource for students using RS & GIS techniques in their studies.

From simple road maps to advanced global-position satellite (GPS) technology, geographic information is essential in today's world. As a result of computers, the Internet, and satellite technology, geographic information is expanding in both quantity and type. Businesses, scientists, travelers, and countless others rely heavily on accurate, up-to-date geographic information. This book is a unique, timesaving, and easy-to-use reference, steering users through the massive amount of geographic information available from a wide range of sources and providing tips on how to use them effectively and efficiently in real-world research. Topics include map basics, finding place names, general geography works, general and thematic atlases, special format maps, aerial photography, remotely sensed images, and more. This book provides an accessible overview of the important, emerging field of Geographic Information Systems (GIS), computer systems capable of assembling, storing, manipulating, and displaying geographically referenced information. Also included is information on geographical standards, organizations, instructional resources, commercial publications, and careers in geography. Whether researching a specific location or a general topic, collecting antiquarian maps, or having an interest in learning how to use geographic tools from topographical maps to nautical charts, this book is a must-have reference.

Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume I, Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation introduces the fundamentals of hyperspectral or imaging spectroscopy data, including hyperspectral data processes, sensor systems, spectral libraries, and data mining and analysis, covering both the strengths and limitations of these topics. Volume II, Hyperspectral Indices and Image Classifications for Agriculture and Vegetation evaluates the performance of hyperspectral narrowband or imaging spectroscopy data with specific emphasis on the uses and applications of hyperspectral narrowband vegetation indices in characterizing, modeling, mapping, and monitoring agricultural crops and vegetation. Volume III, Biophysical and Biochemical Characterization and Plant Species Studies demonstrates the methods that are developed and used to study terrestrial vegetation using hyperspectral data. This volume includes extensive discussions on hyperspectral data processing and how to implement data processing mechanisms for specific biophysical and biochemical applications such as crop yield modeling, crop biophysical and biochemical property characterization, and crop moisture assessments. Volume IV, Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation discusses the use of hyperspectral or imaging spectroscopy data in numerous specific and advanced applications, such as forest management, precision farming, managing invasive species, and local to global land cover change detection.

This is a comprehensive handbook focused on geospatial applications used to study, assess, and monitor the Himalayan mountains. As a region of high relevance and very vulnerable regarding geohazards, it is crucial to detect landscape changes and understand the drivers behind the changes. With advanced remote sensing and GIS tools, in-depth analyses, and interdisciplinary approaches, the Handbook of Himalayan Ecosystems and Sustainability, Two Volume Set studies forest and agriculture ecosystems, urban sprawl and air pollution, geo and other hazards, and provides a breadth of data to support decision making and to aids in the preservation of the landscapes in a sustainable way. Features: Uses geospatial technology for studying fragile Himalayan ecosystems and their sustainability Includes 21 case studies from Indian Himalayan, Nepal, and Afghanistan regions Provides satellite data and geospatial modelling tools for assessing and monitoring all Himalayan landscapes Addresses cryospheric studies and related ongoing geohazards and potential climate change impacts Discusses ecology of the Himalayan rivers, biodiversity, and floristic shifting of endemic species, and landscape restoration

The scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Big Data Analytics for Satellite Image Processing and Remote Sensing is a critical scholarly resource that examines the challenges and difficulties of implementing big data in image processing for remote sensing and related areas. Featuring coverage on a broad range of topics, such as distributed computing, parallel processing, and spatial data, this book is geared towards scientists, professionals, researchers, and academicians seeking current research on the use of big data analytics in satellite image processing and remote sensing.

This book presents the spatial and temporal dynamics of land use and land cover in the central Tibetan Plateau during the last two decades, based on various types of satellite data, long-term field investigation and GIS techniques. Further, it demonstrates how remote sensing can be used to map and characterize land use, land cover and their dynamic processes in mountainous regions, and to monitor and model relevant biophysical parameters. The Tibetan Plateau, the highest and largest plateau on the Earth and well known as "the roof of the world," is a huge mountainous area on the Eurasian continent and covers millions of square kilometers, with an average elevation of over 4000 m. After providing an overview of the background and an introduction to land use and land cover change, the book analyzes the current land use status, dynamic changes and spatial distribution patterns of different land-use types in the study area, using various types of remotely sensed data, digital elevation models and GIS spatial analysis methods to do so. In turn, it discusses the main driving forces, based on the main physical environment variables and socioeconomic data, and provides a future scenario analysis of land use change using a Markov chain model. Given its scope, it provides a valuable reference guide for researchers, scientists and graduate students working on environmental change in mountainous regions around the globe, and for practitioners working at government and non-government agencies.

In the digital world of the knowledge society, developing the infrastructures required to provide citizens with access to cultural content and tourism services demands a multi-fold analysis of social, business, and technological factors. Digital Culture and E-Tourism: Technologies, Applications and Management Approaches presents integrated approaches to culture and tourism, emphasizing content, context and multiple dynamic views of interactions. Covering applications of such technologies as broadband networks, Web 2.0, open source software and semantic knowledge portals, this text is a valuable resource for students, researchers and contributors to the cultivation of a regional and global vision for the management of cultural content and tourism.

This multivolume handbook is the most comprehensive and updated reference of advanced geospatial techniques for water resource and watershed management. It addresses complex solutions that appear in individual articles but require an exhaustive search for assimilation. By assembling these tremendous advances in an expertly curated resource and making it available in depth to professionals and the water research community worldwide, this successful vehicle will help readers in elevating the quality and variety of water research and solutions. A broad range of authors, specialties, sources, institutions, countries, and continents showcase exemplary approaches and capabilities for the 21st century.

This contributed volume collects cutting-edge research in Geographic Information Science & Technologies, Location Modeling, and Spatial Analysis of Urban and Regional Systems. The contributions emphasize methodological innovations or substantive breakthroughs on many facets of the socio-economic and environmental reality of urban and regional contexts.

This book is intended for researchers, practitioners and students who are interested in the current trends and want to make their GI applications and research dynamic. Time is the key element of contemporary GIS: mobile and wearable electronics, sensor networks, UAVs and other mobile snoopers, the IoT and many other resources produce a massive amount of data every minute, which is naturally located in space as well as in time. Time series data is transformed into almost (from the human perspective) continuous data streams, which require changes to the concept of spatial data recording, storage and manipulation. This book collects the latest innovative research presented at the GIS Ostrava 2017 conference held in 2017 in Ostrava, Czech Republic, under the auspices of EuroSDR and EuroGEO. The accepted papers cover various aspects of dynamics in GIscience, including spatiotemporal data analysis and modelling; spatial mobility data and trajectories; real-time geodata and real-time applications; dynamics in land use, land cover and urban development; visualisation of dynamics; open spatiotemporal data; crowdsourcing for spatiotemporal data and big spatiotemporal data.

Open access to information of geographic places and spatial relationships provides an essential part of the analytical processing of spatial data. Access to connected geospatial programs allows for improvement in teaching and understanding science, technology, engineering, and mathematics. Emerging Trends in Open Source Geographic Information Systems provides emerging research on the applications of free and open software in geographic information systems in various fields of study. While highlighting topics such as data warehousing, hydrological modeling, and software packages, this publication explores the assessment and techniques of open software functionality and interfaces. This book is an important resource for professionals, researchers, academicians, and students seeking current research on the different types and uses of data and data analysis in geographic information systems.

This book contains a selection of papers presented during a special workshop on Complexity Science organized as part of the 9th International Conference on GIScience 2016. Expert researchers in the areas of Agent-Based Modeling, Complexity Theory, Network Theory, Big Data, and emerging methods of Analysis and Visualization for new types of data explore novel complexity science approaches to dynamic geographic phenomena and their applications, addressing challenges and enriching research methodologies in geography in a Big Data Era.

This book discusses in detail the science and morphology of powerful hurricane detection systems. It broadly addresses new approaches to monitoring hazards using freely available images from the European Space Agency's (ESA's) Sentinel-1 SAR satellite and benchmarks a new interdisciplinary field at the interface between oceanography, meteorology and remote sensing. Following the launch of the first European Space Agency (ESA) operational synthetic aperture radar satellite, Sentinel-1, in 2014, synthetic aperture radar (SAR) data has been freely available on the Internet hub in real-time. This advance allows weather forecasters to view hurricanes in fine detail for the first time. As a result, the number of synthetic aperture radar research scientists working in this field is set to grow exponentially in the next decade; the book is a valuable resource for this large and budding audience.

This book is specifically designed to serve the community of postgraduates and researchers in the fields of epidemiology, health GIS, medical geography, and health management. It starts with the basic concepts and role of remote sensing, GIS in Kala-azar diseases. The book gives an exhaustive coverage of Satellite data, GPS, GIS, spatial and attribute data modeling, and geospatial analysis of Kala-azar diseases. It also presents the modern trends of remote sensing and GIS in health risk assessment with an illustrated discussion on its numerous applications.

This volume is a comprehensive guide to the use of geographic information systems (GIS) for the spatial analysis of supply and demand for energy in the global and local scale. It gathers the latest research and techniques in GIS for spatial and temporal analysis of energy systems, mapping of energy from fossil fuels, optimization of renewable energy sources, optimized deployment of existing power sources, and assessment of environmental impact of all of the above. Author Lubos Matejicek covers GIS for assessment a wide variety of energy sources, including fossil fuels, hydropower, wind power, solar energy, biomass energy, and nuclear power as well as the use of batteries and accumulators. The author also utilizes case studies to illustrate advanced techniques such as multicriteria analysis, environmental modeling for prediction of energy consumption, and the use of mobile computing and multimedia tools.

This new textbook and lab manual on remote sensing and digital image processing of natural resources includes numerous practical, problem-solving exercises, and case studies that use the free and open-source platform R. It explains the basic concepts of remote sensing and its multidisciplinary applications using R language and R packages, and engages students in learning theory through hands-on real-life projects. Features 1. Aims to expand theoretical approaches of remote sensing and digital image processing through multidisciplinary applications using R and R packages. 2. Engages students in learning theory through hands-on real-life projects. 3. All chapters are structured with solved exercises and homework and encourages readers to understand the potential and the limitations of the environments. 4. Covers data analysis in free and open-source (FOSS) R platform, which makes remote sensing accessible to anyone with a computer. 5. Explores current trends and developments in remote sensing in homework assignments with data to further explore the use of free multispectral remote sensing data, including very high spatial resolution information. Students in upper-level undergraduate or graduate programs with Remote Sensing Course and Geoprocessing Course, civil and environmental engineering, geosciences, and environmental sciences, electrical engineering, biology, hydrology, agriculture Engineering. Professionals in different areas who use remote sensing and image processing. Students in upper-level undergraduate or graduate programs taking courses in Remote Sensing and Geoprocessing, civil and environmental engineering, geosciences, and environmental sciences, electrical engineering, biology, hydrology, agricultural engineering, as well as professionals in different areas who use remote sensing and image processing, will gain a deeper understanding and first-hand experience with remote sensing and digital processing, with a learn-by-doing methodology using applicable examples in natural resources. .

This book focuses on the generalization of map features, providing descriptions and classifying groups of map objects into six categories: point clusters, groups of contours, road networks, river networks, continuous areal features and discrete areal features. Discussing the methods and algorithms in map generalization in equal measure, it also describes the approaches for describing map features. The book is a valuable reference for graduates and researchers who are interested in cartography and geographic information science/systems, especially those in automated map generalization and spatial databases construction.

Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book. This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference.

This thesis reports on sparsity-based multipath exploitation methods for through-the-wall radar imaging. Multipath creates ambiguities in the measurements provoking unwanted ghost targets in the image. This book describes sparse reconstruction methods that are not only suppressing the ghost targets, but using multipath to one's advantage. With adopting the compressive sensing principle, fewer measurements are required for image reconstruction as compared to conventional techniques. The book describes the development of a comprehensive signal model and some associated reconstruction methods that can deal with many relevant scenarios, such as clutter from building structures, secondary reflections from interior walls, as well as stationary and moving targets, in urban radar imaging. The described methods are evaluated here using simulated as well as measured data from semi-controlled laboratory experiments.

Geographic data is a valuable source of information in modern society. By utilizing alternative sources of this data, the availability and potential applications of geographic information systems can be increased. Volunteered Geographic Information and the Future of Geospatial Data is a pivotal reference source for the latest scholarly research on information gathering from volunteers, as opposed to official agencies and private companies, to compile geospatial data. Highlighting a range of pertinent topics such as regional landscape mapping, road safety, and land usage, this book is ideally designed for researchers, academics, students, professionals, and practitioners interested in the growing area of volunteered geographic information.