Derivation of soil moisture using modified dubois model with field assisted surface roughness on RISAT-1 data

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Abstract

The study discuss about the soil moisture estimation using dual polarimetric RISAT-1. The semiempirical approach of Modified Dubois Model (MDM) derived by (SrinivasaRao 2013) is worked out using (σ˚HH) and (σ˚HV) for soil moisture estimation using dual polarimetric backscattering image. IRS LISS IV data have been used to analyze the site suitability of different land use/cover types. The retrieval of backscattering coefficient values (σ˚) from SAR is the common principle factor for soil moisture estimation. The surface roughness were measured in the selected sample location, for which the same backscattering values derived from the SAR is linearly correlated showing r2 = 0.93. The estimated surface roughness is used for retrieval of dielectric constant using MDM. The dielectric constant derived from MDM in combination with the Topps model proposed by (Topp 1980), is used to derive satellite based soil moisture estimation. Linear regression analysis was performed and the soil moisture derived from SAR are well correlated with the volumetric soil moisture showing value of r2 = 0.63.

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Thanabalan, P., & Vidhya, R. (2018). Derivation of soil moisture using modified dubois model with field assisted surface roughness on RISAT-1 data. Earth Sciences Research Journal, 22(1), 13–18. https://doi.org/10.15446/esrj.v22n1.59972

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