Bereuter, Pia

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Bereuter, Pia

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2013 - 20142
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Enddatum: 2019 × Thema: Cartography ×

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  • Vorschaubild nicht verfügbar
    Publikation
    Generalisation operators
    (Springer, 08.07.2014) Stanislawski, Lawrence V.; Buttenfield, Barbara P.; Bereuter, Pia; Savino, Sandro; Brewer, Cynthia A.; Burghardt, Dirk; Duchêne, Cécile; Mackaness, William [in: Abstracting geographic information in a data rich world. Methodologies and applications of map generalisation]
    This chapter summarises cartographic generalisation operators used to generalise geospatial data. It includes a review of recent approaches that have been tested or implemented to generalise networks, points, or groups. Emphasis is placed on recent advances that permit additional flexibility to tailor generalisation processing in particular geographic contexts, and to permit more advanced types of reasoning about spatial conflicts, preservation of specific feature characteristics, and local variations in geometry, content and enriched attribution. Rather than an exhaustive review of generalisation operators, the chapter devotes more attention to operators associated with network generalisation, which illustrates well the logic behind map generalisation developments. Three case studies demonstrate the application of operators to road thinning, to river network and braid pruning, and to hierarchical point elimination. The chapter closes with some summary comments and future directions.
    04A - Beitrag Sammelband
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    Publikation
    Real-time generalization of point data in mobile and web mapping using quadtrees
    (Taylor & Francis, 29.04.2013) Bereuter, Pia; Weibel, Robert [in: Cartography and Geographic Information Science]
    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.
    01A - Beitrag in wissenschaftlicher Zeitschrift