Summary: This section outlines the classification procedure for the Oregon C-CAP. The three dates of imagery were first reviewed for image quality and shifts between image dates. Training points were used as the dependent variable in a CART (Classification Analysis by Regression Tree) approach. Ancillary data layers were calculated from the TM data and were used as additional independent variables in the analysis. Different versions of the map were produced using different combinations of independent variables. The rough map represented the output from the CART classification routine. Ancillary data were used in spatial models were applied to the rough map to produce the provisional map. This represented a fully automated product. This product was then altered by hand edits to refine the classification. In addition, a percent impervious data layer developed from TM data using high resolution imagery, was imbedded into the classification to define the developed classes. This produced the final-with-edits version which is the final version of the classification and is the one described here.
Pre-processing steps: Each Landsat TM scene was geo-referenced by USGS (United States Geological Survey) EROS Data Center. The Space Imaging staff reviewed the spectral and spatial quality of the imagery. Areas that were greater than 1-2 pixels off were sent back to USGS for reprocessing. The data was geo-referenced to Albers Conical Equal Area, with a spheroid of GRS 1980, and Datum of WGS84.