PRISMA Hyperspectral Data Analysis for Basmati Rice Discrimination

The PRISMA hyperspectral narrow-band data covering part of the Jind district during the kharif season 2024 were acquired to discriminate between two rice varieties, namely high-yielding variety (HYV) and aromatic Basmati. In the present study, hyperspectral bands were selected from the 240 hyperspectral bands of PRISMA data using Selective Principal Component Analysis (SPCA), which is specifically useful for crop classification. The subset of 9 PRISMA Hyperspectral bands corresponding to the Sentinel-2 MSI bands was selected for rice crop classification and variety discrimination. The main difference between PCA and SPCA is that SPCA chooses only a subset of bands depending on the desired objectives of the study. The first three principal components (PCs) explained over 98% of the variance of all spectral bands. The scatter plots of PC-1 and PC-2 indicated that there is a clear distinction between HYV and Basmati rice varieties. In the present analysis, narrow-band hyperspectral red-edge group indices, such as Ratio Vegetation Index (RVIs), Green Normalised Difference Vegetation Index (GNDVI), Chlorophyll Green Index (Clgreen), Plant Senescence Reflectance Index (PSRI), Normalised Difference Red Edge Index (NDRE), and Plant Senescence Reflectance Index (PSRI) were generated to study their effectiveness for rice variety discrimination. The Spectral Angle Mapper (SAM) algorithm was used for supervised classification, and the results were validated using the time series S1 and S2 classified data. The results of validation indicated that using single-date hyperspectral data with 30 m spatial resolution, it was possible to discriminate between Basmati and HYV rice; however, it was not possible to discriminate between traditional and evolved Basmati rice varieties.