Retrieval of canopy biophysical variables from remote sensing data using contextual information |
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| Authors: | XIAO Zhi-qiang WANG Jin-di LIANG Shun-lin QU Yong-hua WAN Hua-wei |
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| Affiliation: | [1]State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100875, China [2]School of Geography, Beijing Normal University, Beijing 100875, China [3]Department of Geography, University of Maryland, College Park, MD 20742, USA |
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| Abstract: | In order to improve the accuracy of biophysical parameters retrieved from remotely sensing data,a new algorithm was presented by using spatial contextual to estimate canopy variables from high-resolution remote sensing images.The developed algorithm was used for inversion of leaf area index (LAI) from Enhanced Thematic Mapper Plus (ETM+) data by combining with optimization method to minimize cost functions.The results show that the distribution of LAI is spatially consistent with the false composition imagery from ETM+ and the accuracy of LAI is significantly improved over the results retrieved by the conventional pixelwise retrieval methods,demonstrating that this method can be reliably used to integrate spatial contextual information for inverting LAI from high-resolution remote sensing images. |
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| Keywords: | inverse problem canopy biophysical variables contextual information leaf area index |
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