Retrieval of soil moisture using electromagnetic models and a Bayesian approach in view of the SAOCOM mission: Study on SARAT images in an agricultural site in Argentina
IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2013, vol., no., pp.739,742, 21-26 July 2013
doi: 10.1109/IGARSS.2013.6721263
Abstract: The aim of this research is to examine the ability of an approach based on Bayesian inference to retrieve surface soil moisture in an experimental agricultural area located in the province of Córdoba, Argentina. Radar images from SARAT sensor were used, as well as measurements of biophysical parameters in the field. Several implementations of the main algorithm were designed to evaluate their different capability to reproduce the ground data. The Bayesian inversion was performed based on electromagnetic model: the Integral Equation Model (IEM) for bare soil, and the Water Cloud Model (WCM) for vegetated fields. For bare soil, the results showed high sensitivity of the algorithms to the different roughness conditions of each plot, while for vegetated areas, the availability of field measurements limited the comparisons between the obtained maps and the in situ data.
keywords: {Bayes methods; hydrological techniques; moisture; soil; Argentina; Bayesian inference approach; Bayesian inversion; Cordoba; SAOCOM mission; SARAT images; SARAT sensor radar images; WCM; agricultural site; bare soil IEM; electromagnetic models; experimental agricultural area; field measurements; integral equation model;surface soil moisture retrieval; vegetated fields; water cloud model; Backscatter; Bayes methods; Mathematical model; Remote sensing; Soil moisture; Vegetation mapping; Bayesian approach; Electromagnetic Models; SAR; SARAT; Soil Moisture}