Remote Sensing of Natural Resources

1. Auflage 2020
ISBN: 978-0-367-86745-4
Verlag: Taylor & Francis Ltd

Buch, Englisch, 580 Seiten, Format (B × H): 177 mm x 254 mm, Gewicht: 1166 g

Reihe: Remote Sensing Applications Series

Highlighting new technologies, Remote Sensing of Natural Resources explores advanced remote sensing systems and algorithms for image processing, enhancement, feature extraction, data fusion, image classification, image-based modeling, image-based sampling design, map accuracy assessment and quality control. It also discusses their applications for evaluation of natural resources, including sampling design, land use and land cover classification, natural landscape and ecosystem assessment, forestry, agriculture, biomass and carbon-cycle modeling, wetland classification and dynamics monitoring, and soils and minerals mapping.

The book combines review articles with case studies that demonstrate recent advances and developments of methods, techniques, and applications of remote sensing, with each chapter on a specific area of natural resources. Through a comprehensive examination of the wide range of applications of remote sensing technologies to natural resources, the book provides insight into advanced remote sensing systems, technologies, and algorithms for researchers, scientists, engineers, and decision makers.

Autoren/Hrsg.

Wang, Guangxing

Weng, Qihao

Fachgebiete

• Geowissenschaften Geologie GIS, Geoinformatik
• Geowissenschaften Umweltwissenschaften Umweltschutz, Umwelterhaltung
• Geowissenschaften Umweltwissenschaften Umwelttechnik
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
• Naturwissenschaften Biowissenschaften Biowissenschaften Biowissenschaften, Biologie: Sachbuch, Naturführer

Inhaltsverzeichnis

Remote Sensing Systems, Data, and Applications. RS Applications for Sampling Design of Natural Resources. Advanced Algorithms for Accuracy and Quality Assessment of RS Products. RS Applications for Land Use and Land Cover Classification. RS Applications for Natural Landscape and Ecosystems. RS Applications for Forestry. RS Applications for Agriculture. RS Applications for Biomass and Carbon Cycle Modeling. RS Applications for Wetland Classifications and Dynamics Monitoring. RS Applications for Soils and Minerals Mapping.

Über Autor(innen)

Guangxing Wang, PhD, is an associate professor of remote sensing and geographic information systems (GIS) in the Department of Geography and Environment Resources at Southern Illinois University at Carbondale (SIUC), Illinois.

Qihao Weng, PhD is the director of the Center for Urban and Environmental Change and a Professor of geography at Indiana State University.