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.The amount of data produced by such systems is huge (at the rate of 0.25a1 M pts/s), and manual processing of the data is ... field of view, zenith scan angle, and beam divergence), and structure and density of the tree crown (Holmgren et al.
|Title||:||Remote Sensing of Natural Resources|
|Author||:||Guangxing Wang, Qihao Weng|
|Publisher||:||CRC Press - 2013-07-12|