Integrating social attitudes, spatial data, and Monte Carlo simulation modeling for siting of high voltage power lines

Siting of overhead high-voltage power lines based on physical and regulatory constraints is a challenging spatial optimization problem for which GIS is well suited. Existing techniques typically include rasterization of feature layers; application of a layer weighting and combination scheme through map algebra; and ultimately optimization using least cost path analysis. This approach and the current system of accepting public feedback do not explicitly bring into the modeling process social attitudes associated with the placement of high-voltage power lines. The current needs for expansion and repair of the electrical infrastructure in the United States call for greater cooperation between utilities and the public requiring the inclusion of social attitudes early on in the siting process. In this dissertation, I posit that the inclusion of social data is crucial to the siting process and its integration into the optimization process assists utilities in identifying areas where public opposition challenges the placement of a line. Following this assumption, I present and discuss the results from a survey instrument requesting general attitudes from the public on spatial features to be avoided in the siting process and I present a Monte Carlo simulation analysis integrating survey results with geoprocessing tasks associated with line siting. I also describe the implementation of an open source software tool integrating survey data processing with mapping functions and least cost path tools. I expect that this open source software package will supplement current costing methods for line siting by including public opinion from the outset of the siting process and avoid potential pitfalls that come from doing otherwise.