SBIR Phase I: A Multiple Criteria Based Approach to Automate Conflation in Geographical Information Systems

This Small Business Innovation Research (SBIR) Phase I project describes an innovative approach to automating the integration of geographical data from multiple resources. This process is commonly referred to as conflation. The most important aspect of the conflation process is feature matching. Feature matching is the process of merging corresponding geographical features from various datasets. Previous attempts at automatically solving this problem have only focused on the geometrical characteristics of geographical data; yet, there are other aspects of geographical data that should be considered: topological, nonspatial, and spatial. An improved approach to automating the feature matching process that utilizes these other aspects of geographical data is presented. In the context of the growing use of geographical information systems (GIS), the need for tools to process, analyze and conflate geographical data is increasing. Such tools will find application in the Department of Defense, in the drilling and mining industry, in the agriculture industry, and by urban planners and GIS developers.