Geospatial data integration technology involves fusing equivalent objects from multiple datasets. Due to different acquisition methods of geospatial data, new problem cases arise in data integration systems and thus the complexity of the integration approach increases. There are many data homogenization methods, which determine the assignment of objects via semantic similarity. The algorithms for polygonal geospatial data integration, presented in this paper, are based on geometrical comparison between two datasets. The objective of these algorithms is the assignment of geospatial elements representing the same object in heterogeneous datasets. Depending on semantic information in geospatial data the polygonal shapes have different spatial extent. For this reason two kinds of polygonal geospatial data were analyzed. The methods are discussed and first results are presented. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Stankute, S., & Asche, H. (2010). Geometrical DCC-algorithm for merging polygonal geospatial data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6016 LNCS, pp. 515–527). Springer Verlag. https://doi.org/10.1007/978-3-642-12156-2_39
Mendeley helps you to discover research relevant for your work.