• Journal of the Korean Geographical Society
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• v.39 no.5 s.104
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• pp.804-818
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• 2004

As spatial data resources become more abundant, the potential for conflict among them increases. Those conflicts can exist between two or many spatial datasets covering the same area and categories. Therefore, it becomes increasingly important to be able to effectively relate these spatial data sources with others then create new spatial datasets with matching geometry and topology. One extensive spatial dataset is US Census Bureau's TIGER file, which includes census tracts, block groups, and blocks. At present, however, census maps often carry information that conflicts with municipally-maintained detailed spatial information. Therefore, in order to fully utilize census maps and their valuable demographic and economic information, the locational information of the census maps must be reconciled with the more accurate municipally-maintained reference maps and imagery. This paper formulates a conceptual framework and two map models of map conflation to make geometrically and topologically consistent source maps according to the reference maps. The first model is based on the cell model of map in which a map is a cell complex consisting of 0-cells, 1-cells, and 2-cells. The second map model is based on a different set of primitive objects that remain homeomorphic even after map generalization. A new hierarchical based map conflation is also presented to be incorporated with physical, logical, and mathematical boundary and to reduce the complexity and computational load. Map conflation principles with iteration are formulated and census maps are used as a conflation example. They consist of attribute embedding, find meaning node, cartographic 0-cell match, cartographic 1-cell match, and map transformation.