Soil moisture estimation in Chambal irrigation command using C-band HH polarization multi-incidence angle Radarsat-1 SAR and IRS LISS III data
Soil moisture is one of the key variables in agricultural water management, particularly in scheduling of irrigation in the major irrigation commands. Several studies have been carried out for modelling of soil moisture using synthetic aperture radar (SAR) which is sensitive to soil dielectric permittivity. However, two critical factors viz. random surface roughness and vegetation cover introduces complexities in the precise estimation of soil moisture. The estimation is further constrained when using single configuration SAR. In the present study, microwave and optical synergy were used wherein soil moisture in the Chambal Irrigation Command, India during 2002-03 winter season, was modelled in two steps. In the first step the surface roughness was modelled taking advantage of multi-incidence angle image acquisition by Radarsat-1 within a short temporal interval with the assumption that the soil moisture has not significantly changed. An output called ‘Roughness Normalized Backscatter Coefficient’ (RNBS) was generated which was used subsequently to correct the vegetation effect. In the second step RNBS was plotted against the normalized difference vegetation index (NDVI) generated from IRS-LISS III sensor as a function of volumetric soil moisture. Based upon the relation between RNBS and NDVI, several polynomial models at different moisture levels were generated and applied to the RNBS image to generate different regimes of soil moisture. The modelled soil moisture was validated based upon the independent samples collected from the field. The proposed methodology is found to be applicable under fallow and sparsely vegetated conditions where the NDVI is less than 0.4.
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