Application of a Change Detection Soil Moisture Retrieval Algorithm to Combined, Semi-Concurrent Radiometer and Radar Observations

This paper extends the application of an existing change-detection-based, time-series soil moisture retrieval algorithm to non-concurrent active and passive measurements from WindSat/AMSR2 and the Soil Moisture Active Passive radar, which was active from late April until mid-July on 2015. A time-series of L-band radar backscatter observations was used to populate an under-determined matrix equation whose optimal solution was derived via a bounded linear least squares estimator, and whose bounds were derived from a time-series of radiometerderived soil moisture estimates (taken by either WindSat or AMSR2). Surface soil moisture estimates are compared with insitu measurement probes, which were treated as ground truth. Error statistics and time-series results for the validation sites are presented here and conclusions derived therefrom. The overall RMSE and un-biased RMSE for the retrieval algorithm, taken across all reference pixels considered in the study, were 0.070 m3/m3 and 0.067 m3/m3 respectively, when using WindSat to constrain the algorithm. When using AMSR2 to constrain the algorithm, the RMSE and un-biased RMSE were 0.093 m3/m3 and 0.090 m3/m3 respectively.