Estimation of snow fraction using AVIRIS simulated ASTER image data

Seasonally snow covered areas of the Earth´s mountain ranges are important components in the global hydrologic cycle. The objective of this study is to develop an automatic snow mapping algorithm at sub-pixel resolution for Advanced Spaceborne Thermal Emission And Reflection (ASTER). It is an EOS-A facility instrument to be launched in this year. The authors have collected a huge amount of AVIRIS image data, from which ASTER spectral measurements can be simulated. The high resolution color infrared photo (1-4m) taken simultaneously as AVIRIS image data can be used to access the snow covered area as the ground truth. By evaluation of the current techniques on selecting spectral endmembers and the effects of terrain on linear unmixing process, an unsupervised snow mapping algorithm has been developed by taking advantages of each technique in selecting spectral endmembers