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Chinese Agricultural Science Bulletin ›› 2020, Vol. 36 ›› Issue (20): 51-58.doi: 10.11924/j.issn.1000-6850.casb20191000776

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Soil Moisture Retrieval of Farmland in Southern Shanxi: Based on Sentinel Multi-source Data

Liu Zhengchun1, Feng Meichen2, Xu Lishuai1, Jing Yaodong1, Bi Rutian1()   

  1. 1College of Resources and Environment, Shanxi Agricultural University, Jinzhong Shanxi 030801
    2Institute of Dry Farming Engineering, Shanxi Agricultural University, Jinzhong Shanxi 030801
  • Received:2019-10-30 Revised:2019-12-02 Online:2020-07-15 Published:2020-07-20
  • Contact: Bi Rutian E-mail:brt@sxau.edu.cn

Abstract:

Using remote sensing data to retrieve soil moisture of farmland is essential for monitoring agricultural drought and crop status, and predicting crop yield. Taking the winter wheat planting area in Wenxi of Shanxi as the study area, we wiped off vegetation influence by “water-cloud model”, established the relationship between soil backscattering coefficient and soil moisture to retrieve the soil moisture of the winter wheat planting area of Wenxi on March 19 th 2018. The results showed that: fusion image of microwave (Sentinel-1 image) combined with visible spectrum remote sensing image (Sentinel-2 image) could remove vegetation influence to improve the retrieval accuracy of soil moisture, VV polarization determination coefficient R 2 was increased by 0.0914, and the RMSE was decreased by 0.0895%; the soil at middle valley plain and southeastern and northwestern tablelands of Wenxi was mildly drought, while it was moderately drought at the southwestern hills and eastern mountain lands. The spatial distribution of soil moisture retrieved is highly consistent with hypsographic condition, irrigation condition and farmland productivity grade, with low-lying terrains and favorable irrigation condition corresponding to regions of high soil moisture.

Key words: soil moisture, winter wheat spring drought, water-cloud model, Sentinel data, productivity grade

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