Assessment of red-edge vegetation descriptors in a modified water cloud model for forward modelling using Sentinel–1A and Sentinel–2 satellite data

Abstract

This study investigates the potential of different vegetation descriptors (V) in the modified water cloud model (MWCM), with a focus on comparing the Red–Edge vegetation indices (VI) based and other vegetation descriptors using Sentinel–1A and Sentinel − 2 satellite data. In order to reduce the influences of vegetation and roughness effectively, a soil geometrical model of equivalent roughness was coupled with a MWCM for the simulation in forward modelling. The optimum value of vegetation extinction coefficient (K VI) and dense vegetation indices ((Formula presented.)) of modified Beer’s law were calculated using non-linear least square optimization technique. After the parameterization of MWCM, the five different types of V for wheat crop were tested for the simulation of backscattering coefficients ((Formula presented.)) at VV polarization. The higher statistical performance indices like coefficient of determination (R2 = 0.96), root-mean-square error (RMSE = 0.17 (dB)) and Nash sutcliffe efficiency (NSE = 0.93) were found for the case of Red-Edge-based vegetation descriptors (for VI = NDVIRE) than others in MWCM. Therefore, this methodology reveals that the VI = NDVIRE by modified Beer’s law can be used effectively as the vegetation parameter in the MWCM for accurate simulation in forward direction over vegetation-covered areas. © 2020 Informa UK Limited, trading as Taylor & Francis Group.