A Matrix-Based Structure for Vario-Scale Vector Representation over a Wide Range of Map Scales: The Case of River Network Data

Lina Huang, Tinghua Ai, Peter Van Oosterom, Xiongfeng Yan, Min Yang

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    Abstract

    The representation of vector data at variable scales has been widely applied in geographic information systems and map-based services. When the scale changes across a wide range, a complex generalization that involves multiple operations is required to transform the data. To present such complex generalization, we proposed a matrix model to combine different generalization operations into an integration. This study was carried on a set of river network data, where two operations, i.e., network pruning accompanied with river simplification, were hierarchically constructed as the rows and columns of a matrix. The correspondence between generalization operations and scale, and the scale linkage of multiple operations were also explicitly defined. In addition, we developed a vario-scale data structure to store the generalized river network data based on the proposed matrix. The matrix model was validated and assessed by a comparison with traditional methods that conduct generalization operations in sequence. It was shown that the matrix model enabled complex generalization with good generalization quality. Taking advantage of the corresponding vario-scale data structure, the river network data could be obtained at any arbitrary scale, and the vario-scale representation was achieved across a wide scale range.

    Original languageEnglish
    Article number218
    Number of pages20
    JournalISPRS International Journal of Geo-Information
    Volume6
    Issue number7
    DOIs
    Publication statusPublished - 2017

    Keywords

    • Complex generalization
    • Hydrographic network generalization
    • Matrix model
    • Vario-scale representation

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