Evaluation of synthetic aperture radar for soil moisture measurement in mountainous rangeland areas

Synthetic Aperture Radar (SAR) has been evaluated for soil moisture (m{dollar}rmsb{lcub}v{rcub}){dollar} measurements in semi-arid mountainous rangeland areas. The evaluation was done with the help of field measured m{dollar}rmsb{lcub}v{rcub}{dollar} values and also with simulated values from a hydrologic model in a geographic information system. An empirical imaging model, which was determined using incident angle ({dollar}theta{dollar}) alone as a key topographic variable, is not able to take into account for the variability due to topographic effects in the SAR backscatter coefficient ({dollar}sigmasp0).{dollar} Use of slope in addition to {dollar}theta{dollar} did little to improve the description of topographic effects on SAR {dollar}sigmasp0.{dollar} To quantify the effects of surface roughness, Root Mean Square (RMS) surface height (h) was determined using co-polarized SAR data in a recently developed algorithm. To correct the SAR {dollar}sigmasp0{dollar} variability due to surface roughness and topographic effects, a {dollar}theta{dollar} and h-based model was developed, which improved the performance of the {dollar}theta{dollar}-based correction model significantly. The algorithm which was used for the determination of h was found to give reasonable soil moisture trends but failed to give a normal solution under dry conditions. A soil moisture inversion algorithm was developed by comparing L-HH SAR {dollar}sigmasp0{dollar} (dB), corrected for surface roughness and topographic effects, with field measurements. The algorithm was found to be consistent with an algorithm developed in a previous study done on other rangelands. Corrected SAR-based soil moisture maps show relatively dry conditions at lower elevations and relatively wet conditions at higher elevations, which is consistent with field observations. Change detection was found to give results similar to those from the corrected SAR, but it tends to give lower soil moisture values than field and corrected SAR-based soil moisture. Out of the three SAR-based approaches (co-polarized SAR in algorithm, corrected SAR, and change detection) used for the determination of m{dollar}rmsb{lcub}v{rcub}{dollar} change detection is simpler and the best for the measurement of soil moisture changes. The corrected SAR approach is relatively difficult to implement but it is good for the areas where we want to measure absolute m{dollar}rmsb{lcub}v{rcub}.{dollar} The hydrologic model tended to overestimate surface m{dollar}rmsb{lcub}v{rcub}{dollar} because of the failure of the model to account for surface evaporation processes unless subsoil was relatively dry.