Identifying the optimum route for new railroad lead-tracks using traditional field methods is often time-consuming, is costly, and does not allow for easy investigation of alternative routes. The NASA sponsored Affiliated Research Center (ARC) at the University of South Carolina worked with Norfolk Southern Corporation to develop a remote sensing and GISassisted lead-track route selection model. The objective was to compare the traditionally surveyed routes to those derived using the output from the remote sensing and GIs-assisted modeling. The critical element in the design of the model was the calculation of a cost surface. The cost variables for the model were developed based on expert advice from Norfolk Southern employees. The solution employed a raster GIS econometric routing model for the exploration of potential routes using construction cost factors such as grade (cut and fill cost), road crossings, stream crossings, and track cost. The use of remotely sensed data was a key element of the research. The digital elevation model used in the grid-based econometric model was obtained from Light Detection and Ranging (LIDAR) data with accurate 0.3- by 0.3-m (I- by 1-ft) elevation postings. The route selected using the remote sensing and GIS-assisted modeling was similar to the traditionally surveyed route. The GIS-based optimal path lead-track model can be used to identify rapidly a variety of potential routes based on the most important cost factors.
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