Remote Sensing Of Global Croplands For Food Security

Increases in populations have created an increasing demand for food crops while increases in demand for biofuels have created an increase in demand for fuel crops. What has not increased is the amount of croplands and their productivity. These and many other factors such as decreasing water resources in a changing climate have created a crisis like situation in global food security. Decision makers in these situations need accurate information based on science. Remote Sensing of Global Croplands for Food Security provides a comprehensive knowledge base in use of satellite sensor-based maps and statistics that can be used to develop strategies for croplands (irrigated and rainfed) and their water use for food security. Over 50 Multi-disciplinary Global Experts Give Insight and Provide Practical Approaches Emphasizing practical mapping technologies based on advanced remote sensing data and methods, this book provides approaches for estimating irrigated and rainfed cropland areas and their water use on a national, continental, or global basis. Written by 50+ leading experts working at the forefront of this critical area, it offers case studies from a variety of continents highlighting the subtle requirements of each. In a very practical way it demonstrates the experience, utility, and models for determining water resources used and resulting yields of irrigated and rainfed croplands. The authors discuss: (a) innovative methods used for mapping croplands, (b) approaches adopted to collect cropland data in different countries by traditional and non-traditional means, (c) accuracies, uncertainties, and errors involved in producing cropland products, (d) surface energy balance models used to assess crop water use, and (e) extensive results and outcomes pertaining to global croplands and their water use. Develop Strategies for an Enhanced Green Revolution and an Accelerated Blue Revolution Linking croplands to water use and food security, the book provides a global perspective on this sensitive issue. It gives insight into the extent of cropland usage, their spatial distribution, their cropping intensities, and their water use patterns. The editors collect the experience, methods, models, and results that show the way forward and help in decision-making on water resources and food security. All of this is required for developing strategies for an enhanced green revolution and for an accelerated blue revolution.

Volume III of the Remote Sensing Handbook, Second Edition, is focused on agriculture, food security, vegetation, phenology, rangelands, soils, and global biomass modeling, mapping, and monitoring using multi-sensor remote sensing. This book is an essential resource for researchers at all levels interested in using remote sensing.

Land remote sensing: the use of space-based satellite technologies to obtain information on environmental variables such as land-use and land-covering combination with other types of data can provide information on changes in the Earth's surface and atmosphere that are critical for forecasting and responding to human welfare issues, such as disease outbreaks, food shortages, and floods. This book summarizes a workshop on the potential contributions of remotely sensed data to land-use and land-cover change and ways to use physical, biological, temporal, and social characteristics of particular locations to support decisions about human welfare. The discussions focused on human health and food security, two aspects of human welfare in which remotely-sensed environmental conditions play a key role. Examples illustrating the possibilities for applying remote sensing for societal benefit are included throughout the report. As a result of the workshop, three themes were identified that, if fostered, could help realize the potential for the application of land remote sensing to decisions about human welfare: (1) integration of spatial data on environmental conditions derived from remote sensing with socioeconomic data; (2) communication between remote sensing scientists and decision makers to determine effective use of land remote sensing data for human welfare issues; and (3) acquisition and access to long-term environmental data and development of capacity to interpret these data.

A volume in the three-volume Remote Sensing Handbook series, Remote Sensing of Water Resources, Disasters, and Urban Studies documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Remotely Sensed Data Characterization, Classification, and Accuracies, and Land Reso

A volume in the three-volume Remote Sensing Handbook series, Land Resources Monitoring, Modeling, and Mapping with Remote Sensing documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Remotely Sensed Data Characterization, Classification, and Accuracies, and Remo

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.

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 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. It emphasizes the importance of hyperspectral remote sensing tools for studying vegetation processes and functions as well as the appropriate use of hyperspectral data for vegetation management practices. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume IV through the editors’ perspective. Key Features of Volume IV: Guides readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Includes specific applications on agriculture, crop management practices, study of crop stress and diseases, crop characteristics based on inputs (e.g., nitrogen, irrigation), study of vegetation impacted by heavy metals, gross and net primary productivity studies, light use efficiency studies, crop water use and actual evapotranspiration studies, phenology monitoring, land use and land cover studies, global change studies, plant species detection, wetland and forest characterization and mapping, crop productivity and crop water productivity mapping, and modeling. Encompasses hyperspectral or imaging spectroscopy data in narrow wavebands used across visible, red-edge, near-infrared, far-infrared, shortwave infrared, and thermal portions of the spectrum. Explains the implementation of hyperspectral remote sensing data processing mechanisms in a standard, fast, and efficient manner for their applications. Discusses cloud computing to overcome hyperspectral remote sensing massive big data challenges. Provides hyperspectral analysis of rocky surfaces on the earth and other planetary systems.

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. This book also presents and discusses hyperspectral narrowband data acquired in numerous unique spectral bands in the entire length of the spectrum from various ground-based, airborne, and spaceborne platforms. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume I through the editors’ perspective. Key Features of Volume I: Provides the fundamentals of hyperspectral remote sensing used in agricultural crops and vegetation studies. Discusses the latest advances in hyperspectral remote sensing of ecosystems and croplands. Develops online hyperspectral libraries, proximal sensing and phenotyping for understanding, modeling, mapping, and monitoring crop and vegetation traits. Implements reflectance spectroscopy of soils and vegetation. Enumerates hyperspectral data mining and data processing methods, approaches, and machine learning algorithms. Explores methods and approaches for data mining and overcoming data redundancy; Highlights the advanced methods for hyperspectral data processing steps by developing or implementing appropriate algorithms and coding the same for processing on a cloud computing platform like the Google Earth Engine. Integrates hyperspectral with other data, such as the LiDAR data, in the study of vegetation. Includes best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, crop productivity and water productivity mapping, and modeling.