GeoLearn is designed to enable rapid processing of large size satellite remote sensing data available in HDF EOS format. It has been tested primarily with MODIS land-surface data products. Use and analysis of these datasets are at the heart of a variety of scientific investigations pertaining to the study of the interaction between land-surface and climate, and prediction of terrestrial hydrologic processes.
Developed by: Image Spatial Data Analysis Group (ISDAG) at National Center for Supercomputing Applications (NCSA) and by Hydroclimatology and Terrestrial Hydrology Group (HTHG) at Civil and Environmental Engineering (CEE), UIUC

University of Illinois at Urbana-Champaign
National Center for Supercomputing Applications (NCSA)