Volume 12 Issue 2
Jun.  2019
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Article Contents
Ke Zhang, Li-jun Chao, Qing-qing Wang, Ying-chun Huang, Rong-hua Liu, Yang Hong, Yong Tu, Wei Qu, Jin-yin Ye. 2019: Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China. Water Science and Engineering, 12(2): 85-97. doi: 10.1016/j.wse.2019.06.001
Citation: Ke Zhang, Li-jun Chao, Qing-qing Wang, Ying-chun Huang, Rong-hua Liu, Yang Hong, Yong Tu, Wei Qu, Jin-yin Ye. 2019: Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China. Water Science and Engineering, 12(2): 85-97. doi: 10.1016/j.wse.2019.06.001

Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China

doi: 10.1016/j.wse.2019.06.001
Funds:  This study was supported by the National Key Research and Development Program of China (Grant No. 2016YFC0402701), the National Natural Science Foundation of China (Grants No. 51879067 and 51579131), the Natural Science Foundation of Jiangsu Province (Grant No. BK20180022), the Six Talent Peaks Project in Jiangsu Province (Grant No. NY-004), the Fundamental Research Funds for the Central Universities of China (Grants No. 2018B42914 and 2018B04714), the China National Flash Flood Disaster Prevention and Control Project (Grant No. 126301001000150068), and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant No. KYCX18_0572).
More Information
  • Corresponding author: Ke Zhang
  • Received Date: 2019-01-08
  • Rev Recd Date: 2019-05-13
  •     The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and higher accuracy. Our approach was to first apply the single-channel brightness radiometric algorithm to estimate soil moisture from the respective brightness temperature observations of the SMAP, SMOS, AMSR2, FY3B, and FY3C satellites on the same day and then produce a daily composite dataset by averaging the individual satellite-retrieved soil moisture. We further evaluated our product, the official soil moisture products of the five satellites, and the ensemble mean (i.e., arithmetic mean) of the five official satellite soil moisture products against ground observations from two networks in Central Tibet and Anhui Province, China. The results show that our product outperforms the individual released products of the five satellites and their ensemble means in the two validation areas. The root mean square error (RMSE) values of our product were 0.06 and 0.09 m3/m3 in Central Tibet and Anhui Province, respectively. Relative to the ensemble mean of the five satellite products, our product improves the accuracy by 9.1% and 57.7% in Central Tibet and Anhui Province, respectively. This demonstrates that jointly using brightness temperature observations from multiple satellites to retrieve soil moisture not only improves the spatial coverage of daily observations but also produces better daily composite products.


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