Abstract
We present a discretized, multi-layer soil moisture model that links soil moisture variability to single-look SAR measurements. Our model reveals distinct closure phase signatures arising from variation of soil moisture, radar frequencies, and soil textures. Specifically, our model predicts that positive asymmetric soil moisture anomalies produce positive closure phase step-changes, and negative asymmetric anomalies yield negative closure phase step-changes, consistent with observed data. Additionally, our analysis reveals that low-frequency radar (e.g., L-band) exhibits heightened sensitivity to the vertical distribution of soil moisture. We identify an approximate transfer function between soil moisture anomalies and closure phase responses and introduce a scalable algorithm for retrieving the InSAR Soil Moisture Index, a relative soil moisture product. We demonstrate the retrieval algorithm in two diverse environments: the Mojave Desert and the Central Valley in California. Good agreements between the derived InSAR Soil Moisture Index, in situ soil moisture measurements, and SMAP/Sentinel-1 soil moisture measurements highlight the potential for large-scale soil moisture monitoring using InSAR closure phase.
Yujie Zheng
Assistant Professor
I develop satellite radar and geodetic methods to understand how water, the solid Earth, climate variability, and human activity shape the surface and subsurface.