Efficient Parallel and Distributed Algorithms for GIS Polygonal Overlay Processing

Polygon overlay is one of the complex operations in Geographic Information Systems (GIS). In GIS, a typical polygon tends to be large in size often consisting of thousands of vertices. Sequential algorithms for this problem are in abundance in literature and most of the parallel algorithms concentrate on parallelizing edge intersection phase only. Our research aims to develop parallel algorithms to find overlay for two input polygons which can be extended to handle multiple polygons and implement it on General Purpose Graphics Processing Units (GPGPU) which offers massive parallelism at relatively low cost. Moreover, spatial data files tend to be large in size (in GBs) and the underlying overlay computation is highly irregular and compute intensive. MapReduce paradigm is now standard in industry and academia for processing large-scale data. Motivated by MapReduce programming model, we propose to develop and implement scalable distributed algorithms to solve large-scale overlay processing in this dissertation.