Remote Sensing of Natural Resources

1. Auflage 2013
ISBN: 978-1-4665-5692-8
Verlag: CRC Press

Buch, Englisch, 580 Seiten, Format (B × H): 180 mm x 257 mm, Gewicht: 1179 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.

Zielgruppe

Researchers and academics working in the field of earth science and natural resources; graduate students taking courses in remote sensing at environmental and natural resources; industry researchers and professionals in agencies and in government who use advanced remote sensing.

Autoren/Hrsg.

Wang, Guangxing

Weng, Qihao

Fachgebiete

• Geowissenschaften Geologie Geodäsie, Kartographie, Fernerkundung
• Geowissenschaften Geologie GIS, Geoinformatik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
• Geowissenschaften Geographie | Raumplanung Geodäsie, Kartographie, GIS, Fernerkundung

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.