A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data (original) (raw)

Abstract

AMSR-E and MODIS are two EOS (Earth Observing System) instruments on board the Aqua satellite. A regression analysis between the brightness of all AMSR-E bands and the MODIS land surface temperature product indicated that the 89 GHz vertical polarization is the best single band to retrieve land surface temperature. According to simulation analysis with AIEM, the difference of different frequencies can eliminate the influence of water in soil and atmosphere, and also the surface roughness partly. The analysis results indicate that the radiation mechanism of surface covered snow is different from others. In order to retrieve land surface temperature more accurately, the land surface should be at least classified into three types: water covered surface, snow covered surface, and non-water and non-snow covered land surface. In order to improve the practicality and accuracy of the algorithm, we built different equations for different ranges of temperature. The average land surface temperature error is about 2–3°C relative to the MODIS LST product.

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Authors and Affiliations

  1. Key Laboratory of Resources Remote Sensing and Digital Agriculture, MOA, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
    Mao KeBiao, Qin ZhiHao & Xu Bin
  2. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing, 100101, China
    Mao KeBiao & Shi JianCheng
  3. Graduate University of Chinese Academy of Sciences, Beijing, 100049, China
    Mao KeBiao
  4. Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
    Li ZhaoLiang & Li ManChun
  5. International Institute for Earth System Science, Nanjing University, Nanjing, 210093, China
    Qin ZhiHao

Authors

  1. Mao KeBiao
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  2. Shi JianCheng
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  3. Li ZhaoLiang
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  4. Qin ZhiHao
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  5. Li ManChun
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  6. Xu Bin
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Corresponding author

Correspondence toMao KeBiao.

Additional information

Supported by the National Natural Science Foundation of China (Grant Nos. 90302008 and 40571101), the Open Fund of Key Laboratory of Resources Remote Sensing and Digital Agriculture, MOA, and Project 863 (Grant No. 2006AA12Z103)

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Mao, K., Shi, J., Li, Z. et al. A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data.SCI CHINA SER D 50, 1115–1120 (2007). https://doi.org/10.1007/s11430-007-2053-x

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