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Volume V of theSix Volume Remote Sensing Handbook, Second Edition, is focused on the use of remote sensing technologies for studying water resources, including groundwater, floods, snow and ice, and wetlands. It discusses water productivity studies from Earth observation data characterization and modeling, mapping their successes and challenges. Chapters include remote sensing of surface water hydrology; quantitative geomorphology; river basin studies; floods; wetlands, including mangroves and river deltas; groundwater studies; crop water use or actual evapotranspiration modeling and mapping; and snow and ice mapping. This thoroughly revised and updated volume draws on the expertise of a diverse array of leading international authorities in remote sensing and provides an essential resource for researchers at all levels interested in using remote sensing. It integrates discussions of remote sensing principles, data, methods, development, applications, and scientific and social context. FEATURES Provides the most up-to-date comprehensive coverage of remote sensing science for water resources, including wetlands, floods, snow, and ice. Provides comprehensive assessments of crop water use and crop water productivity modeling and mapping, including evapotranspiration studies. Discusses and analyzes data from old and new generations of satellites and sensors spread across 60 years. Includes numerous case studies on advances and applications at local, regional, and global scales. Introduces advanced methods in remote sensing, such as machine learning, cloud computing, and artificial intelligence (AI). Highlights scientific achievements over the last decade and provides guidance for future developments. This volume is an excellent resource for the entire remote sensing and GIS community. Academics, researchers, undergraduate and graduate students, as well as practitioners, decision makers, and policymakers, will benefit from the expertise of the professionals featured in this book and their extensive knowledge of new and emerging trends.
The HilbertOCoHuang Transform (HHT) represents a desperate attempt to break the suffocating hold on the field of data analysis by the twin assumptions of linearity and stationarity. Unlike spectrograms, wavelet analysis, or the WignerOCoVille Distribution, HHT is truly a time-frequency analysis, but it does not require an a priori functional basis and, therefore, the convolution computation of frequency. The method provides a magnifying glass to examine the data, and also offers a different view of data from nonlinear processes, with the results no longer shackled by spurious harmonics OCo the artifacts of imposing a linearity property on a nonlinear system or of limiting by the uncertainty principle, and a consequence of Fourier transform pairs in data analysis. This is the first HHT book containing papers covering a wide variety of interests. The chapters are divided into mathematical aspects and applications, with the applications further grouped into geophysics, structural safety and visualization.
Most government agencies and private companies are investing significant resources in the production and use of geographical data. The capabilities of Geographical Information Systems (GIS) for data analysis are also improving, to the extent that the potential performance of GIS software and the data available for analysis outstrip the abilities of
SOHO, the Solar and Heliospheric Observatory, is a project of international cooperation between ESA and NASA to study the Sun, from its deep core to the outer corona, and the solar wind. To achieve its scientific goals it carries a complement of twelve sophisticated, state-of-the-art instruments. Three helioseismology instruments are expected to provide unique data for the study of the structure and dynamics of the solar interior, from the very deep core to the outermost layers of the convection zone. A set of five complementary remote sensing instruments, consisting of EUV and UV imagers, spectrographs and coronagraphs, will give us our first comprehensive view of the outer solar atmosphere and corona, leading to a better understanding of the enigmatic coronal heating and solar wind acceleration processes. Finally, three experiments will complement the remote sensing observations by making in-situ measurements of the composition and energy of the solar wind and charged energetic particles. This volume contains detailed descriptions of all the twelve instruments on board SOHO. Also included are an overview paper and a description of the SOHO ground system, science operations and data products. The aim of these papers is to make the broader scientific community, and in particular potential guest investigators, aware of the scientific objectives and capabilities of the SOHO payload and to provide a reference document for the various instruments.
An authoritative and accessible introduction to the concepts and tools needed to make ecology a more predictive science Ecologists are being asked to respond to unprecedented environmental challenges. How can they provide the best available scientific information about what will happen in the future? Ecological Forecasting is the first book to bring together the concepts and tools needed to make ecology a more predictive science. Ecological Forecasting presents a new way of doing ecology. A closer connection between data and models can help us to project our current understanding of ecological processes into new places and times. This accessible and comprehensive book covers a wealth of topics, including Bayesian calibration and the complexities of real-world data; uncertainty quantification, partitioning, propagation, and analysis; feedbacks from models to measurements; state-space models and data fusion; iterative forecasting and the forecast cycle; and decision support. Features case studies that highlight the advances and opportunities in forecasting across a range of ecological subdisciplines, such as epidemiology, fisheries, endangered species, biodiversity, and the carbon cycle Presents a probabilistic approach to prediction and iteratively updating forecasts based on new data Describes statistical and informatics tools for bringing models and data together, with emphasis on: Quantifying and partitioning uncertainties Dealing with the complexities of real-world data Feedbacks to identifying data needs, improving models, and decision support Numerous hands-on activities in R available online
International financial markets play an increasingly important role. There can be no doubt that over the past twenty years the size of financial markets have grown at a faster pace than the size of the markets for goods and services. However, it is still unclear whether this is a desirable development. This book discusses the debate on the possible separation of the financial sector and real economy. The text makes use of established scientific research.
Recent economic growth in China and other Asian countries has led to increased commodity demand which has caused price rises and accompanying price fluctuations not only for crude oil but also for the many other raw materials. Such trends mean that world commodity markets are once again under intense scrutiny. This book provides new insights into the modeling and forecasting of primary commodity prices by featuring comprehensive applications of the most recent methods of statistical time series analysis. The latter utilize econometric methods concerned with structural breaks, unobserved components, chaotic discovery, long memory, heteroskedasticity, wavelet estimation and fractional integration. Relevant tests employed include neural networks, correlation dimensions, Lyapunov exponents, fractional integration and rescaled range. The price forecasting involves structural time series trend plus cycle and cyclical trend models. Practical applications focus on the price behaviour of more than twenty international commodity markets.
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.