The Phase I objectives will conduct feasibility studies on selected metropolitan areas where rapid transit systems have been built since the availability off civilian satellite imagery (1972). The feasibility study will select flights where multi--spectral imagery, aerial photography, and land-use analysis are available in archives and are readily adapted to spatial analysis. Secondly. the transit improvements should have been completed for at least 10 years so that significant changes in land uses and land value could have occurred within the study. The feasibility study will determine the availability of the current pattern recognition software to identify land-use categories in sufficient detail to be useful for transit benefit evaluation using mop multi-spectral imagery from several generation of earth observing satellites. The study will determine the utility of change detection software to monitor changes in land-use each over time. The Phase I study will determine the feasibility of integrating land-use analysis software based on raster imagery with vector-based GIS software comment in transportation analysis. The feasibility study will determine the availability or GIS-based assessed valuation parcel databases for transit capital investment analysis. A study designed for Phase II than application will be prepared for two or more metropolitan areas. Anticipated results and
Potential Commercial Applications: With the development and are specific procedures and spatial analysis techniques in phase 22 assess the impact of transit capital investments on land-use and related community development, regional and state transportation planners will be best able to develop and implement policies and plans which creates sustainable and livable communities. Public planners and private developers of transportation and community infrastructure will be able to use the software products and procedures based on government and commercial satellite imagery.
Keywords: Remote Sensing Imagery, Geographic Information Systems, Transit Infrastructure Assessment, Imagery Interpretation, Automatic Land-use Classification.
