Identifying the spatial distribution of Prosopis Juliflora using Hyperion imagery

Remote Sensing is a powerful tool to identify the vegetation distributions. Hyperspectral remote sensing has a number of bands at the shortest bandwidth to extract the vegetation precisely. The objectives of the present study are to identify the spectral characteristics and to identify the occupation of Prosopis Juliflora using hyperspectral data. In the present research work, the high spectral resolution imagery (10 nm) used to extract the Prosopis Juliflora. In Tamil Nadu, Vellore district is mainly affected by these species and most of the area has been converted to the arid region. The spectral characteristics of Prosopis Juliflora developed using spectroradiometer. The Prosopis Juliflora leaf shows huge reflectance in VNIR (700-1200 nm) region due to their chlorophyll content. The radiance and reflectance of the imagery are generated in BIL format and FLAASH module respectively. Data dimensionality reduction of the hyperspectral imagery carried out using MNF and PPI. The end members of Prosopis Juliflora are identified depends on the total probability score carried out by the methods of BE, SAM and SFF. The per-pixel classification algorithm is used to estimate the distribution of Prosopis Juliflora.