ANALYSIS OF SPACEBORNE HYPERION IMAGERY FOR THE ESTIMATION OF FRACTIONAL COVER OF RANGELAND ECOSYSTEMS

The goal of this research was to investigate the potential of hyperspectral Hyperion (EO-1) data to derive fractional cover of rangeland components using constrained linear spectral mixture analysis. Hyperion image data were acquired over the Antelope Creek Ranch located in southern Alberta, Canada in July 2005. These image data were first corrected for the sensor artifacts such as spatial mis-registration between the VNIR and SWIR data and striping. These data were then atmospherically corrected and transformed to surface reflectance, corrected for sensor smile/frown and post-processed to remove residual errors. Iterative Error Analysis was utilized to find image endmembers that acted as inputs to the constrained spectral unmixing. The preliminary results show that spectral unmixing was promising for percent cover estimation of green vegetation and litter/soil, but separation of green grass from green shrub was challenging due to their spectral similarity.