Douglas M. Flewelling, Ph.D.
Mark P. Kumler, Ph.D.
When a large number of routes pass through a narrow region or constricted space on a terrain they create bottlenecks, affecting the flow of goods and people through the region. These regions become important in defense, security and rescue operations because of their ability to intercept and influence many routes simultaneously. This paper describes a novel implementation for finding such regions on a terrain through a suite of Python-based geoprocessing tools for ArcMap that apply least-cost path analysis and Monte Carlo simulation to generate a large number of routes on a raster-based cost surface. The implementation is made efficient by resampling the cost surface to a configurable vector grid and by running the simulations using multi-processing. By plotting all the simulated routes on a map, bottlenecks are highlighted. The result is a powerful suite of tools that can be used for planning of rescue missions and troop mobility operations. A hypothetical use case of finding the best paths for an infantry platoon moving across a terrain to its destination is presented in this paper. A cost surface using multi-criteria evaluation is developed and provided as input to the simulation tools which generate hundreds of possible routes between the platoon’s starting point and final destination, identifying areas of the terrain that could become possible bottlenecks or ambush points.
Shinde, S. S. (2013). Vector-based Mobility Modeling (Master's thesis, University of Redlands). Retrieved from https://inspire.redlands.edu/gis_gradproj/204