Synthetic aperture radar data employed for soil moisture estimation in the Piketberg region, South Africa

Information on the distribution of surface soil moisture is important for a number of applications. Due to the high temporal and spatial variability, and consequently the cost of monitoring by field observations, a means of remote monitoring of soil moisture content using remote sensing data is needed. The aim of this study was to test soil moisture retrieval algorithms based on synthetic aperture radar data (SAR). This includes the use of Envisat ASAR and ALOS PALSAR data, which was provided by the European Space Agency. Both linear regression and multiple-polarization models were applied for soil moisture quantification. The results could not be validated due to a lack of distributed field-based measurements but were compared to rainfall figures over the same period. Though inconclusive, the results suggest that the techniques show promise in their ability to quantify surface soil moisture.