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- W2092874013 abstract "Abstract With a focus on mobile and web mapping, we propose several algorithms for on-the-fly generalization of point data, such as points of interest (POIs) or large point collections. In order to achieve real-time performance, we use a quadtree data structure. With their hierarchical subdivision structure and progressive levels of detail, indices of the quadtree family lend themselves as auxiliary data structures to support algorithms for generalization operations, including selection, simplification, aggregation, and displacement of point data. The spatial index can further be used to generate several local and global measures that can then serve to make educated guesses on the density and proximity of points across map scales, and thus enable control of the operation of the generalization algorithms. An implementation of the proposed algorithms has shown that, and thanks to the quadtree index, real-time performance can be achieved even for large point sets. Furthermore, the quadtree data structure can be extended into a caching structure, which can be used to store pre-computed generalizations; thus, a desired level of detail (LOD) can simply be retrieved from cache. Keywords: mobile and web mappingon-the-fly generalizationreal-time generalizationpoint data generalizationPOIauxiliary data structurequadtree Acknowledgements The research reported in this paper represents a part of the PhD project of the first author. Funding by the Swiss National Science Foundation through project Generalisation for Portrayal in Web and Wireless Mapping (GenW2 +) (SNF No. 200020–138109) is greatfully acknowledged." @default.
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- W2092874013 date "2013-09-01" @default.
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- W2092874013 title "Real-time generalization of point data in mobile and web mapping using quadtrees" @default.
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- W2092874013 doi "https://doi.org/10.1080/15230406.2013.779779" @default.
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