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Time-series approach to estimate the soil moisture of a subsidence area by using dual polarimetric radar data

  • role： First author第一作者
  • Affiliation：

    School of Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China

  • Email：1534660893@qq.com
  • Introduction：马威(1990—　)，男，硕士研究生，研究方向为雷达遥感理论与应用。E-mail：1534660893@qq.com
Wei MA1,  
  • Affiliation：

    School of Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China

Dengkui CHEN1,  
  • Affiliation：

    School of Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China

    Key Laboratory of Mine Spatial Information Technologies of SBSM, Henan Polytechnic University, Jiaozuo 454000, China

Na YANG12,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Surveying & Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China

    Key Laboratory of Mine Spatial Information Technologies of SBSM, Henan Polytechnic University, Jiaozuo 454000, China

  • Email：mac@hpu.edu.cn
  • Introduction：马超(1967—　)，男，教授，研究方向为遥感理论教学和遥感技术矿区地质灾害的监测。E-mail：mac@hpu.edu.cn
Chao MA12*

résumé

Soil moisture is a key factor that induces the deterioration of ecological environments in mining subsidence areas. In this study, a method of soil moisture inversion using Sentinel-1A dual polarized SAR and OLI surface reflectance data is proposed. First, the water content of vegetation is determined based on the normalized difference water index. Second, the effect of vegetation on the Sentinel-1A backscattering coefficient is eliminated by using the water cloud model, which has been transformed into the backscattering coefficient of bare soil. Third, based on the empirical model established by AIEM and Oh models, the surface parameters of the study area are determined and verified by the OLI optical inversion results. Finally, the soil moisture contents in the subsidence and non-subsidence areas are compared. (1) Compared with the results of soil moisture based on the soil moisture monitoring index, the VH-polarized inversion results exhibit better agreement between two polarization patterns. Moreover, the inversion results of two polarization patterns simultaneously show that the inversion result of the desertification grassland area is better than those of loess hilly and gully regions, which indicates that the effect of terrain on the backscatter cannot be ignored. (2) In the 72 sets of data during 2016, the VH-polarized inversion results show that the soil moisture content in the comparative area is larger than that in the subsidence area; it accounts for 41 cases, and the proportion is 57%. Meanwhile, the VV-polarized inversion results show that the soil moisture content in the comparative area is larger than that in the subsidence area; it accounts for 36 cases, and the proportion is 50%. In addition, subsidence in different mining areas is affected differently. Results indicate that the increase in surface roughness caused by mining subsidence exerts a negative effect on surface soil moisture. However, differences exist between different mining areas.

mots-clés

polarimetric radar;soil moisture;interferometry synthetic aperture radar(InSAR);mining subsidence;time series

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