Crop classification by using dual-pol SAR vegetation indices derived from Sentinel-1 SAR-C data

In the following study, an attempt is made for crop classification of rainy season through analyzing time-series Sentinel-1 SAR data of May 2020 to September 2020. The SVI DP index derived from dual-pol (VV and VH) bands consisting of NRPB ( σ^0vh_ij- σ^0vv_ij/σ^0vh_ij+ σ^0vv_ij ), DPDD (σ^0vh_ij+ σ^0vv_ij)/ √ 2 ), IDPDD ( σ^0vv_(max)- σ^0vv_ij)+σ^0vh_ij/ √ 2 ), and VDDPI (σ^0vh_ij+σ^0vv_ij/ σ^0vv_ij) ratios are utilized for discriminating inter-vegetative boundaries of crop pixels. This study was conducted near Karnal city region, Karnal district, Haryana, India. The Sentinel-1 data has the capability to penetrate thick cloud cover and provide high revisit frequency data for rain-fed crops. Obtained classification achieved higher accuracy in both RF (93.77