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Urban remote sensing :

By: Yang, Xiaojun.
Material type: materialTypeLabelBookPublisher: [S.l.] : Wiley, 2011Edition: 1st ed.Description: 408 p.ISBN: 047074958X (hardcover); 9780470749586 (hardcover).Online resources: Click here to access online Summary: Urban Remote Sensing is designed for upper level undergraduates, graduates, researchers and practitioners, and has a clear focus on the development of remote sensing technology for monitoring, synthesis and modeling in the urban environment. It covers four major areas: the use of high-resolution satellite imagery or alternative sources of image date (such as high-resolution SAR and LIDAR) for urban feature extraction; the development of improved image processing algorithms and techniques for deriving accurate and consistent information on urban attributes from remote sensor data; the development of analytical techniques and methods for deriving indicators of socioeconomic and environmental conditions that prevail within urban landscape; and the development of remote sensing and spatial analytical techniques for urban growth simulation and predictive modeling.
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Books Books Reference Section
Reference 621.3678YAN (Shelf - 51B) (Browse shelf) Available 46220
Books Books Reference Section
Reference 621.3678YAN (Shelf - 51B) (Browse shelf) Available 46221
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621.3678KUM (Shelf - 54D) Electronics Engineering / 621.3678PAM (Shelf - 51B) Remote sensing : 621.3678PAM (Shelf - 51B) Remote sensing : 621.3678YAN (Shelf - 51B) Urban remote sensing : 621.3678YAN (Shelf - 51B) Urban remote sensing : 621.367SHI (Shelf - 51B) Image Processing and Pattern Recognition : fundamentals and techniques 621.3692AGR (Shelf - 51B) Nonlinear fiber optics, fourth edition /

Urban Remote Sensing is designed for upper level undergraduates, graduates, researchers and practitioners, and has a clear focus on the development of remote sensing technology for monitoring, synthesis and modeling in the urban environment. It covers four major areas: the use of high-resolution satellite imagery or alternative sources of image date (such as high-resolution SAR and LIDAR) for urban feature extraction; the development of improved image processing algorithms and techniques for deriving accurate and consistent information on urban attributes from remote sensor data; the development of analytical techniques and methods for deriving indicators of socioeconomic and environmental conditions that prevail within urban landscape; and the development of remote sensing and spatial analytical techniques for urban growth simulation and predictive modeling.

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