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Remotely sensed data characterization, classification, and accuracies / edited by Prasad S. Thenkabail

Thenkabail, Prasad Srinivasa, 1958- [editor].
Tipo de material: Libro
 Libro impreso(a) Series Editor: Boca Raton, Florida, United States: CRC Press Taylor and Francis Group, c2016Descripción: xxxiv, 678 páginas : fotografías, ilustraciones, mapas ; 29 centímetros.ISBN: 1482217864; 9781482217865.Tema(s): Sensores remotos | Procesamiento de datos | Sistemas de información geográficaClasificación: 621.3678 / R4 Nota de bibliografía: Incluye bibliografía e índice Número de sistema: 58455Contenidos:Mostrar Revisión:
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Acervo General 621.3678 R4 Vol. 1 Prestado 11/08/2021 ECO030008662
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Satellites and Sensors From Different Eras and Their Characteristics.. Remote Sensing Systems—Platforms and Sensors: Aerial, Satellite, UAV, Optical, Radar, and LiDAR.. Fundamentals of Remote Sensing: Evolution, State of The Art, and Future Possibilities.. Fundamentals of Remote Sensing for Terrestrial Applications: Evolution, Current State of the Art, and Future Possibilities.. Data Normalization, Harmonization, and Intersensor Calibration.. Overview of Satellite Image Radiometry in the Solar-Reflective Optical Domain.. Postlaunch Radiometric Calibration of Satellite-Based Optical Sensors with Emphasis on Terrestrial Reference Standard Sites.. Remote Sensing Data Normalization..Satellite Data Degradations and Their Impacts on High-Level Products.. Vegetation Index Standardization and Cross-Calibration of Data From Multiple Sensors.. Inter- and Intrasensor Spectral Compatibility and Calibration of the Enhanced Vegetation Indices.. Toward Standardization of Vegetation Indices.. Image Processing Methods and Approaches.. Digital Image Proceßing: A Review of the Fundamental Methods and Techniques.. Urban Image Classification: Per-Pixel Claßifiers, Subpixel Analysis, Object-Based Image Analysis, and Geospatial Methods.. Image Classification Methods in Land Cover and Land Use.. Hyperspectral Image Processing: Methods and Approaches.. Thermal Infrared Remote Sensing: Principles and Theoretical Background.. Object-Based Image Analysis: Evolution, History, State of the Art, and Future Vision.. Geospatial Data Integration in OBIA: Implications of Accuracy and Validity.. Image Segmentation Algorithms for Land Categorization.. LiDAR Data Processing and Applications.. Change Detection.. Change Detection Techniques Using Multisensor Data.. Integrating Geographic Information Systems (GIS) And Remote Sensing In Spatial Modeling Framework For Decision Support.. Geoproceßing, Workflows, and Provenance..Toward Democratization of Geographic Information: GIS, Remote Sensing, and GNß Applications in Everyday Life.. Frontiers of GIScience: Evolution, State of the Art, and Future Pathways.. Object-Based Regionalization for Policy-Oriented Partitioning of Space.. Global Navigation Satellite Systems (GNSS;) Remote Sensing.. Global Navigation Satellite Systems Theory and Practice: Evolution, State of the Art, and Future Pathways.. Global Navigation Satellite System Reflectometry for Ocean and Land Applications.. Global Navigation Satellite Systems for Wide Array of Terrestrial Applications.. Crowdsourcing and Remote Sensing Data.. Crowdsourcing and Remote Sensing: Combining Two Views of Planet Earth.. Cloud Computing and Remote Sensing.. Proceßing Remote-Sensing Data in Cloud Computing Environments.. Google Earth For Remote Sensing.. Google Earth for Remote Sensing.. Accuracies, Errors, and Uncertainties of Remote Sensing-Derived Products.. Assessing Positional and Thematic Accuracies of Maps Generated from Remotely Sensed Data.. Space Law and Remote Sensing.. Remote Sensing Law: An Overview of Its Development and Its Trajectory in the Global Context.. Summary.. Remote Sensing Data Characterization, Classification, and Accuracies: Advances of the Last 50 Years and a Vision for the Future

A volume in the Remote Sensing Handbook series, Remotely Sensed Data Characterization, Classification, and Accuracies documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Land Resources Monitoring, Modeling, and Mapping with Remote Sensing, and Remote Sensing of Water Resources, Disasters, and Urban Studies. This volume demonstrates the experience, utility, methods, and models used in studying a wide array of remotely sensed data characterization, classification, and accuracies for terrestrial applications. Leading experts on global geographic coverage, study areas, and array of satellite and sensors contribute to this unique handbook. This theoretical as well as highly practical book represents a thorough history of advancement in the field over last 50 years, bringing us to where we are now, and highlighting future possibilities. Highlights include: • Fundamental and advanced topics in remote-sensing satellites and sensors. • Remote sensing data calibration, normalization, harmonization, and synthesis. • Optical, Radar, LiDAR, thermal, hyperspectral, and other satellite sensors, normalization of remotely sensed data, and data degradations. • Digital image processing, urban image classification, and image classification methods in land use\land cover, cropland, change detection studies. • Enhanced vegetation indices and standardization of vegetation índices. • Object-based image analysis (OBIA) and geospatial data integration. • LiDAR data processing and applications. • Geoprocessing, GIS, and GIScience. • GNSS applications. • Crowdsourcing and cloud computing. • Google Earth for Earth Sciences. • Map accuracies. • Remote-sensing law or space law, and a host of other topics. Considered magnum opus on the subject, the three-volume Remote Sensing Handbook is edited by Dr. Prasad S. Thenkabail of the United States Geological Survey and a renowned international expert in remote sensing and GIScience, with contributions from the very best leading global experts, the handbook gives you a knowledge base on the evolution of remote sensing science, current state-of-the-art technology, and a future vision for the field.

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