Meter-level resolution surface soil moisture estimation over agricultural fields from time-series quad-pol SAR with constraints of coarse resolution CCI data products

作者：Hongtao Shi, Qing Wu, Zhong Lu, Jinqi Zhao, Wensong Liu, Tianjie Zhao, Liujun Zhu, Fengkai Lang, Lingli Zhao · 发表于：Agricultural Water Management · 年份：2025 · DOI：10.1016/j.agwat.2025.109856 · 被引用次数：3 · 研究领域：Soil Moisture and Remote Sensing、Synthetic Aperture Radar (SAR) Applications and Techniques、Geophysical Methods and Applications

Monitoring the spatial and temporal variations in surface soil moisture (SSM) within agricultural areas is essential for effective water resource management. Active and passive microwave remote sensing techniques have been widely utilized for SSM retrieval and mapping at both global and regional scales. Despite these advancements, accurately monitoring SSM at high spatial resolutions (up to tens of meters) remains a substantial challenge. This study proposes a novel time-series SSM retrieval algorithm for field-scale mapping of surface volumetric soil moisture using L-band quad-polarimetric (HH, HV or VH, and VV) synthetic aperture radar (PolSAR) data. The method employs a two-component polarimetric target decomposition model to isolate the soil surface scattering component by removing the contribution of vegetation scattering. The real part of the complex soil dielectric constant is subsequently estimated using the alpha approximation model, from the extracted time-series soil surface scattering coefficients. To address the under-determined nature of the soil dielectric constant estimation, which limits retrieval accuracy, constraints on soil permittivity derived from coarse-resolution microwave SSM products are introduced. Time-series volumetric SSM values are subsequently estimated using an empirical dielectric mixing model, which establishes a relationship between the dielectric constant and volumetric soil moisture. The proposed approach demonstrates significant advantag...