Development

Siting of energy transmission power lines based on physical and regulatory constraints is a challenging and complicated multivariable spatial optimization problem for which GIS is well suited. Existing techniques typically include rasterization of constraint feature layers; application of a layer weighting and combination scheme using map algebra; and ultimately evaluation of optimal paths using least cost path analysis. Such an approach does not explicitly take into account social attitudes and political pressures associated with placement of overhead high-voltage power lines. Indeed, in the United States, energy companies must consider public opinion about such infrastructure development, and usually do so through the Environmental Impact Statement process. We have observed that this feedback mechanism does not explicitly bring social attitudes and concerns directly into the modeling process and hence we are researching this addition to the siting process. This research project implements a survey instrument designed to get general information from the public on what spatial features a siting project should attempt avoid, and to what degree. Results from the survey are then converted to a weighting scheme and applied to the previously described rasterization, weighting, combination, and least cost path routing process. Because every survey question is likely to produce a frequency distribution of results, a Monte Carlo simulation approach is taken to resample from the survey results distribution a large number of times, resulting in a suite of potential paths for the power line placement. It is expected that a map of the resulting paths will clearly represent strongly favored corridors, as well as those where risk of public dissatisfaction are greatest.

DotSpatial is a free, open source, set of libraries developed on the Microsoft .NET framework which provides projection, visualization, and extensibility features. DotSpatial allows rapid development and deployment of C# and VB.NET based spatial data, analysis, and mapping applications. DotSpatial has been downloaded over 25000 times since the project started in April 2010, has 74 team members. This presentation will provide an introduction to the DotSpatial project including, goals, target users, project status and project roadmap. Additionally, a few representative software application built on DotSpatial will be presented.

Spatial patterns and properties of species richness in natural communities are of keen interest to biogeographers and conservation biologists as they describe key features of the location and distribution of the earth's biological diversity. Patterns of species richness are determined by constituent species range sizes, spatial locations of those ranges, species associations, co-occurrence and species interactions. Analysis of these phenomena at biogeographical scales, i.e. continental to global extents, presents computational and visualization challenges. The creation of species presence/absence matrices is one approach for linking range size and richness patterns. The presence/absence matrix is a gridded data format, where columns represent species and rows represent geographic sites or localities. Each matrix element is coded for the presence (1) or absence (0) of each of hundreds or thousands of species. The presence/absence matrix allows for the interlinking of two concepts: the dispersion field, and the diversity field. The diversity field is the species diversity of all sites in which a particular species occurs. A dispersion field is the set of geographic ranges of all the species occurring in a given site. It has been demonstrated that species diversity of sites and the mean range size of species has a symmetrical relationship with the range size of species and the mean species diversity within those ranges. Null models are used with presence/absence matrices to test hypotheses requiring that large matrices be randomized while maintaining the total value of each row and column constant. By treating these matrices as Boolean grids, we developed highly-optimized swap algorithms to achieve this in a software suite of WPS web services which utilize QGIS as a client.