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(Ebook) Remote sensing of natural resources by Guangxing Wang, Qihao Weng (Editors) ISBN 9781466556935, 1466556935

  • SKU: EBN-4345646
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Instant download (eBook) Remote sensing of natural resources after payment.
Authors: Guangxing Wang, Qihao Weng (Editors)
Pages:580 pages.
Year:2013
Editon:1-st
Publisher:CRC Press
Language:english
File Size:79.35 MB
Format:pdf
ISBNS:9781466556935, 1466556935
Categories: Ebooks

Product desciption

(Ebook) Remote sensing of natural resources by Guangxing Wang, Qihao Weng (Editors) ISBN 9781466556935, 1466556935

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.

Review:

"… a comprehensive view on and real world examples of remote sensing technologies in natural resources assessment and monitoring. … state-of-the-art knowledge in this multidisciplinary field. Readers can expect to finish the book armed with the required knowledge to understand the immense literature available and apply their knowledge to the understanding of sampling design, the analysis of multi-source imagery, and the application of the techniques to specific problems relevant to natural resources."―Yuhong He, University of Toronto Mississauga, Ontario, Canada

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