ASCAT2SMAP: Image-to-Image Translation to Obtain L-Band-Like Soil Moisture From C-Band Satellite Data

Abstract

Soil moisture (SM) is a critical parameter in understanding the Earth&apos;s hydrological cycle and managing water resources. Remote sensing instruments, such as Advanced SCATterometer (ASCAT), can provide valuable long-term SM. However, compatibility issues may arise when integrating ASCAT SM retrieval with another retrieval, such as soil moisture active passive (SMAP), a high-quality microwave radiometer-based SM retrieval. In this study, we propose a novel image-to-image translation approach based on the U-Net architecture to convert ASCAT SM data into the format of SMAP (ASCAT2SMAP). The resulting SM from the ASCAT2SMAP was evaluated using temporally separated SMAP data and independent in-situ SM measurement from the International Soil Moisture Network (ISMN). In the separately divided test periods, ASCAT2SMAP showed good agreement with SMAP with R of 928, ubRMSD of 0.043 $\text{m}<^>{3}/\text{m}<^>{3}$, and bias of 0.002 $\text{m}<^>{3}/\text{m}<^>{3}$. When evaluating ASCAT2SMAP with ISMN data, it showed a better agreement than ASCAT and more similar metrics with SMAP. Moreover, we found that the ASCAT2SMAP is more robust to a problem of subsurface scattering than the original ASCAT SM. When simulating V-polarized brightness temperature from ASCAT2SMAP SM, it showed good agreement with ubRMSD of 5.602 K and bias of -0.135 K. Our results are expected to provide a valuable perspective preceding to creation of harmonized SM datasets from different sensors, contributing to improved data integration and analysis in the field of geoscience and remote sensing.