Soil moisture mapping using ALOS PALSAR and ENVISAT ASAR data over India

Soil moisture is a crucial parameter which is useful in several research fields such as agriculture, meteorology and hydrology. In this paper, the application of fully polarimetric (ALOS PALSAR) and dual polarimetric (ENVISAT ASAR) Synthetic Aperture Radar (SAR) data acquired over several test sites of India for soil moisture mapping is presented. PolSARpro software, Alaska Map Ready, and some programs developed by us were used for the processing of PALSAR data. For soil moisture mapping, surface inversion models such as Dubois et al., Oh et al, and Extended-Bragg (X-Bragg model) models were used. As we do not have ground truth data synchronous with satellite passes, we just compared the results of inversion models and also the seasonal variation of soil moisture with time. The variation in soil moisture pattern in different test sites are clearly seen through soil moisture maps obtained from ALOS PALSAR fully polarimetric data acquired in different dates. We found that Dubois et al. model over estimates soil moisture as compared to Oh et al. model. The soil moisture difference between Oh et al. 1992 model and X-Bragg model estimations is also observed. X-Bragg model fails to invert soil moisture for several fields due to very sensitive to surface charecteristics. For ENVISAT ASAR data processing, NEST 4A software was used. In order to invert soil moisture from backscattering coefficient of ASAR data, linear regression models developed by Baghdadi et al were used with single and dual-pol models. The Soil moisture variation in Vijayawada and Mumbai test sites are clearly seen through soil moisture maps obtained from ENVISAT ASAR dual polarimetric SAR data acquired in two different dates. High soil moisture pattern in Vijayawada test site is observed in Nov, 2005 due to heavy rainfall. The effect of vegetation on soil moisture is also observed for the same site.