Advances in Land Remote Sensing
System, Modeling, Inversion and Application
Herausgegeben: Liang, Shunlin
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With a CD-Rom included, graduate students and practitioners of remote sensing will find this an essential text. It collects the review papers of the 9th International Symposium on Physical Measurements and Signatures in Remote Sensing (ISPMSRS). It systematically summarizes the past achievements and identifies the frontier issues as the research agenda for the near future. It covers all aspects of land remote sensing, from sensor systems, physical modeling, inversion algorithms, to various applications.
This book collects the review papers from both technical sessions and three discussion panels of the 9th International Symposium on Physical Measurements and Signatures in Remote Sensing (ISPMSRS). It systematically summarizes the past achievements and identifies the frontier issues as the research agenda for the near future. It covers all aspects of land remote sensing, from sensor systems, physical modeling, inversion algorithms, to various applications. The papers on remote sensing system evaluate the capabilities of different sensor systems for estimating key land surface variables and how they can best be improved and integrated effectively in the future. Papers on modeling and inversion review the state-of-the-art methodologies on physical modeling and the inversion algorithms for estimating a series of land surface variables. The papers on remote sensing application assess the current status of various applications and discuss how better to bridge the development of remote-sensing science and technology and practical applications. Representing the community effort and contributed by a team of international leading experts, this indispensable reference book for graduate students and practitioners of remote sensing also aids those engaged in academic research, government and industry.
Audience: Graduate students, practitioners of remote sensing through academic research, government and industry.
Audience: Graduate students, practitioners of remote sensing through academic research, government and industry.
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