Improved Surface Soil Moisture Estimation Model in Semi-Arid Regions Using the Vegetation Red-Edge Band Sensitive to Plant Growth

Abstract

Accurate description of surface soil moisture (SSM) in vegetation-covered areas is of great significance to water resource management and drought monitoring. To remove the effect of vegetation on SSM estimation, the vegetation index obtained from Sentinel-2 (S2) was applied for vegetation water content (VWC) estimation. The VWC model was substituted into the water cloud model (WCM), and thus, the SSM estimation model was developed based on the WCM. The methodology was tested at Daxing, Beijing, and Gu’an, Hebei, in which training and validation data of SSM were acquired by in situ measurements. The results can be described as follows: (1) For the vegetation-covered areas, the Modified Chlorophyll Absorption Ratio Index (MCARI) obtained from the B3, B4, and B5 bands of S2 was the most suitable for removing the influence of vegetation on SSM estimation; (2) Compared to Sentinel-1 (S1) vertical–horizontal (VH) polarization, vertical–vertical (VV) polarization was more suitable for SSM estimation and achieved higher accuracy; (3) The developed model could be used to estimate SSM under crop cover with high accuracy, which indicated the correlation coefficients (R2) between in situ measured and estimated SSM were 0.867, the root mean square error (RMSE) was 0.028 cm3/cm3, and the MAE was 0.023 cm3/cm3. Thus, this methodology has the potential for SSM estimation in vegetated areas.