Visualization of Multispectral and Multisource Data Using an Interactive Image Spreadsheet (iiss)

The next generation of remote sensing observing systems will routinely provide multispectral data from a very large number of sensors. For example, the Landsat-type instrument of the planned Earth observing system (Eos) satellite will be the HIghResolution Imaging Spectrometer (HIRIS). The HIRIS will have 192 channels, compared to seven on the current Landsat Thematic Mapper (TM). Similarly, the next generation of satellite based weather observing instruments like the MODerateresolution Imaging Spectrometer (MODIS), also on the Eos platform, will have up to 100 channels, compared to the five Advanced Very High Resolution Radiometer (AVHRR) channels currently available on the NOAA satellites. New methods for visualizing, interpreting, comparing, and analyzing multispectral time sequential satellite data need to be investigated to fully exploit these data sets efficiently. Papathomas, et al. (1988) provide a review of visualization methods applied to meteorological data sets. Satellite image data must be combined with model derived data, digital terrain data, and geographical maps, for any comprehensive scientific investigation (e.g., climatological and classification studies). Such multisource data sets need to be integrated and geocoded for effective interpretation.