Variability Analysis and Change Characterizationof HSI Data for Urban Mapping

摘要

Urban areas are highly variable in remote sensing data, thus it can be difficult to detect changes over time caused bydevelopment or by movement of specific targets. This research is a first attempt at exploration of repeat flights of 20mspatial resolution imaging spectrometer data to identify and characterize sources and the nature of spectral variability inurban/rural environments. Data for two dates were atmospherically corrected using a MODTRAN-based model toindependently correct each dataset for atmospheric effects. The data were geocorrected and co-registered then croppedto a common spatial coverage. Spectra for individual pixels and for ROIs were extracted from the two datasets andvisual and statistical comparisons were made between spectra to assess the effects of collection parameters andatmospheric corrections. Spectral endmembers were determined for each flightline, mapped using spectral matchingmethods, and compared across flightlines. This approach allowed determination of relatively spectrally invariant areasversus areas with significant spectral change. The combined datasets were used to develop thematic layers and evaluatespectral variability versus changes principally due to urban development.