Soil moisture retrieval based on Sentinel-1 satellite: a case study of Liyang city

doi:10.13474/j.cnki.11-2246.2026.0701

Abstract

Abstract: [Purposes] Soil moisture retrieval was recognized as a technical challenge limiting accurate and rapid acquisition of soil moisture data in fields such as hydrology and meteorology. [Methods] Based on the Dubois model,Sentinel-1 radar data and concurrent Sentinel-2 optical images were utilized,along with field soil moisture data obtained through the traditional drying method and time-domain reflectometry(TDR)in-situ measurements.A soil moisture retrieval model was developed for sparsely vegetated and bare soil areas,and a soil moisture map of the study area was generated by incorporating cumulative distribution function(CDF)correction results. [Findings] High consistency was observed between soil moisture data obtained by TDR in-situ measurements and the traditional drying method (R²=0.917,RMSE=0.038 7 m³·m^-3).Good agreement was also demonstrated between TDR in-situ measurement data and model-inverted soil moisture data (R²=0.706,RMSE=0.040 6 m³·m^-3).After applying the CDF method for consistency correction,the RMSE was decreased from 0.040 6 m³·m^-3 to 0.028 9 m³·m^-3,and the KS statistic was decreased from 0.173 1 to 0.086 5. [Conclusions] Data measured by TDR devices can support high spatiotemporal resolution surface moisture monitoring,and the CDF method contributes to improve data quality,providing valuable insights and references for surface soil moisture retrieval.

Key words: soil moisture retrieval, Dubois model, Sentinel-1, remote sensing, cumulative distribution function

CLC Number:

P237

Liu Haoyue, Li Pengao, Li Zichuang, Shao Wen, Xie Yong. Soil moisture retrieval based on Sentinel-1 satellite: a case study of Liyang city[J]. Bulletin of Surveying and Mapping, 2026, 0(7): 1-8.

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