Comparison Of Hyperspectral Vegetation Indices Based On Casi Airborne Data

Hyperspectral imaging have become a critical tool for the vegetation remote sensing since it contains abundant spectral information and can detect the subtle features to accurately monitor the vegetation status. Regarding to the number of bands been used, numerous hyperspectal vegetation indices (VIs) can be roughly divided into two categories: VIs derived from band geometric and VIs derived from band transformation. This study used the Compact Airborne Spectrographic Imager (CASI) data to compare the VI derived from band transformation, taking the Vegetation Index based on the Universal Pattern Decomposition Method (VIUPD) as an example, with four widely used VIs derived from band geometric. The results show that VIUPD can reflect more abundant information than others VIs qualitatively and quantitatively.