基于Sentinel-1卫星进行土壤水分反演——以溧阳市为例

doi:10.13474/j.cnki.11-2246.2026.0701

摘要/Abstract

摘要： [目的] 土壤水分反演是制约水文、气象等领域实现土壤水分准确、快速获取的技术难点。[方法] 本文基于Dubois模型,利用Sentinel-1雷达数据、同期Sentinel-2光学影像数据、传统烘干法与时域反射仪(TDR)原位测量土壤水分数据,构建了稀疏植被区与裸土区的土壤水分反演模型,通过累积分布函数(CDF)校正得到研究区土壤湿度图。[结果] TDR原位测量与传统烘干法获得的土壤水分数据有较高一致性(R²=0.917,RMSE=0.038 7 m³·m^-3);TDR测量数据与模型反演结果也较为吻合(R²=0.706,RMSE=0.040 6 m³·m^-3);经CDF方法校正后,RMSE由0.040 6 m³·m^-3降低为0.028 9 m³·m^-3,KS统计量由0.173 1降低为0.086 5。[结论] 研究表明,TDR设备测量的数据能够支撑高时空分辨率的地表水分监测,CDF方法有助于提升数据质量,可为地表土壤水分反演提供思路和借鉴。

关键词: 土壤水分反演, Dubois模型, Sentinel-1, 遥感, 累积分布函数

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

中图分类号:

P237

刘皓月, 李鹏傲, 李自闯, 邵雯, 谢勇. 基于Sentinel-1卫星进行土壤水分反演——以溧阳市为例[J]. 测绘通报, 2026, 0(7): 1-8.

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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