基于Sentinel多源遥感数据的河北省景县农田土壤水分协同反演

doi:10.19741/j.issn.1673-4831.2019.0944

Abstract

Abstract: Vegetation has significant effect on the retrieval of surface soil moisture by microwave remote sensing. A related study was carried out in Jingxian County of Hebei Province. The quantitative inversion research on the surface soil moisture in vegetation covered agricultural areas was based on the combination method of the modified water cloud model and the Oh model using Sentinel-1 SAR and Sentinel-2 optical remote sensing data. The results show that the combination method had good inversion accuracy in the VV polarization mode, with R² of 0.653 0, RMSE of 0.040 1 cm³·cm^-3, MAE of 0.032 7 cm³·cm^-3. Compared with the VH polarization mode, the VV polarization mode had better ability for the detection of the change of surface soil water content. The proposed method can obtain the data of the surface soil moisture with high spatial resolution and high accuracy in the vegetation covered areas.

Key words: modified water cloud model, Oh model, soil moisture, vegetation water content, Sentinel-1/2

CLC Number:

P237
S127

LI Bo-xiang, CHEN Xiao-yong. Synergic Use of Sentinel-1 and Sentinel-2 Images for Soil Moisture Retrieval in Vegetation Covered Agricultural Areas of Jingxian County of Heibei Province[J]. Journal of Ecology and Rural Environment, 2020, 36(6): 752-761.

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Synergic Use of Sentinel-1 and Sentinel-2 Images for Soil Moisture Retrieval in Vegetation Covered Agricultural Areas of Jingxian County of Heibei Province

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