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Proceedings Paper

Generation of an all-weather land surface temperature product from MODIS and AMSR-E data
Author(s): Si-Bo Duan; Zhao-Liang Li; Pei Leng; Xiao-Jing Han; Yuanyuan Chen
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Paper Abstract

Land surface temperature (LST) is widely used in a variety of applications, such as meteorology, climatology, and ecology. Up to now, there are no all-weather LST products at high spatial resolution. In this study, we propose a method to generate an all-weather LST product by merging MODIS and AMSR-E data. Two main processes are performed in this method, including retrieving AMSR-E LST and downscaling AMSR-E LST to MODIS pixel resolution. After the implement of these two processes, MODIS LSTs under clear-sky conditions and AMSR-E LSTs under cloudy conditions are merged to generate an all-weather LST product. Results indicate that the merged LSTs filled up the missing data in the original MODIS LSTs due to the effects of cloud when compared with the original MODIS LSTs.

Paper Details

Date Published: 9 December 2015
PDF: 7 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 980816 (9 December 2015); doi: 10.1117/12.2207848
Show Author Affiliations
Si-Bo Duan, Chinese Academy of Agricultural Sciences (China)
Zhao-Liang Li, Chinese Academy of Agricultural Sciences (China)
ICube, Univ. of Strasbourg, CNRS (France)
Pei Leng, Chinese Academy of Agricultural Sciences (China)
Xiao-Jing Han, Chinese Academy of Agricultural Sciences (China)
Yuanyuan Chen, Chinese Academy of Agricultural Sciences (China)


Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)

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