Soil Moisture Retrieval During Crop Growth Cycle Using Satellite SAR Time Series

Satellite SAR-based soil moisture retrieval over agricultural fields, under crop overlain conditions, is a challenging exercise. This is so because the overlying crop volume interacts with both the incoming and the backscattered radar signal. Therefore, the soil moisture linked solely to the top layer (0–5 cm) of the soil cannot be reliably retrieved under such conditions without avoiding the obscuring effect of growing crop volume. In this investigation, we demonstrated a proof-of-concept for a time-series approach to retrieve soil moisture during crop growth cycle. Contrary to the use of the single-scene approach, the novelty of the proposed approach lies in exploiting the satellite SAR time series acquired during a cropping cycle. The proposed time-series approach is effective for capturing the nuances in the crop phenological stages while calibrating the Dubois–water cloud model (WCM) soil moisture retrieval model. By employing this approach, we achieved the 0.04
$\text{m}^{3}\;\text{m}^{-3}$
soil moisture retrieval root-mean-square error benchmark at a high spatial resolution and addressed the issue of solving for the Dubois–WCM model constants under data-constrained conditions. Furthermore, we observed that the combination of temporally non-overlapping vegetation descriptors (optical and SAR) resulted in degradation in the performance of the retrievals and under such circumstances single polarimetric descriptor performed better.