Visual Data Mining for Remote Sensing Data Sets

NASA's Earth Observing System (EOS) produces vast quantities of satellite data intended for the study of global climate change, its consequences for life on Earth, and the impact of human activities on it. However, EOS data sets are so large and complex that it is difficult, if not impossible, to understand their large scale structure and draw conclusions that could help inform the debate over climate change. We present here a prototype data mining tool for visualizing structure and exploring these massive data sets. It's use is demonstrated on data from JPL's Multi-angle Imaging SpectroRadiometer.