Assessment of dual polarimetric radar vegetation descriptor in modified water cloud model for retrieval of leaf area index using Sentinel -1 (C-band) satellite data

The polarimetric study in terms of energy spectrum (matrix decomposition) and degree of polarization $(m)$ for vegetation targets infer the accuracy of synthetic aperture radar (SAR) sensors and vegetation operational algorithms. In the present work the dual polarimetric radar vegetation index $(\mathrm{D}_{\mathrm{p}}\text{RVI})$ and polarimetric radar vegetation index (PRVI) were used as a radar vegetation descriptor (V) in modified water cloud model (MWCM) for assessment of retrieval accuracy of leaf area index (LAI) for wheat crop in the vegetative cropland using Sentinel -1 (C - band) satellite data. The Jacobian based non-linear least square optimization algorithm was used for the parametrization of MWCM. Further, the inversion methods were adopted for retrieval of LAI at VV polarization. The statistical correlation analysis was indicated that $\mathrm{D}_{\mathrm{p}}\text{RVI}$ employed the better $\mathrm{R}^{2}=0.78$ than PRVI($\mathrm{R}^{2}=0.71$) Thus, the $(\mathrm{D}_{\mathrm{p}}\text{RVI})$ may be alternative tool than optical indices in all weather and in night time acquisition for gap filling in time-series study of crop monitoring.