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  • Wang, Xiao  (6)
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  • 1
    Online Resource
    Online Resource
    Informa UK Limited ; 2021
    In:  The Cartographic Journal Vol. 58, No. 3 ( 2021-07-03), p. 268-289
    In: The Cartographic Journal, Informa UK Limited, Vol. 58, No. 3 ( 2021-07-03), p. 268-289
    Type of Medium: Online Resource
    ISSN: 0008-7041 , 1743-2774
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2113652-X
    SSG: 14,1
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  • 2
    Online Resource
    Online Resource
    Informa UK Limited ; 2020
    In:  International Journal of Cartography Vol. 6, No. 1 ( 2020-01-02), p. 71-98
    In: International Journal of Cartography, Informa UK Limited, Vol. 6, No. 1 ( 2020-01-02), p. 71-98
    Type of Medium: Online Resource
    ISSN: 2372-9333 , 2372-9341
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2836338-3
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  • 3
    Online Resource
    Online Resource
    Informa UK Limited ; 2021
    In:  Geocarto International Vol. 36, No. 15 ( 2021-09-14), p. 1732-1751
    In: Geocarto International, Informa UK Limited, Vol. 36, No. 15 ( 2021-09-14), p. 1732-1751
    Type of Medium: Online Resource
    ISSN: 1010-6049 , 1752-0762
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2109550-4
    SSG: 14
    SSG: 14,1
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  • 4
    Online Resource
    Online Resource
    MDPI AG ; 2019
    In:  ISPRS International Journal of Geo-Information Vol. 8, No. 4 ( 2019-04-02), p. 168-
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 8, No. 4 ( 2019-04-02), p. 168-
    Abstract: Building groups with special patterns are common layouts in urban settlement areas, which should be carefully generalized. Typification is considered as an appropriate operator to generalize building groups with grid patterns. As an important operator in building generalization, the purpose of typification is to reduce the number of objects while preserving the original distribution characteristics as much as possible. This study proposes a mesh-based method to typify buildings with grid patterns. Firstly, the pattern is subdivided into perfect grid or grid-like patterns by considering the completeness of the grids. The proposed typification method consists of three steps: (1) generating mesh from the proximity graph of buildings; (2) eliminating triangular meshes; (3) determining the number, positions, and representations of the newly created buildings with the help of the related meshes. The proposed method is modeled as an iterative process to achieve hierarchical typification results, which provides support to the map multiple representation. The experimental results demonstrate that the mesh-based typification method can achieve satisfying results in the perfect grid pattern, as well as the grid-like pattern. The new distribution of the typified buildings preserves the original pattern characteristics.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2655790-3
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  • 5
    Online Resource
    Online Resource
    Copernicus GmbH ; 2019
    In:  Proceedings of the ICA Vol. 2 ( 2019-07-10), p. 1-8
    In: Proceedings of the ICA, Copernicus GmbH, Vol. 2 ( 2019-07-10), p. 1-8
    Abstract: Abstract. Buildings are among the most important features of cities. In the suburban or rural regions, buildings are normally constructed along the roads, which forms the smooth and consistent patterns so that the building arrangements also can be described with network models. In previous studies, network theory has achieved good performance in cartography and GIS. In this paper, a study of a building-network is proposed, including the concepts, generation methods and centrality analysis. Firstly, with the constraint Delaunay triangulation and the refinement strategy by facing ratio, the building-network is generated by considering the buildings and the proximal segments as the nodes and segments of the network, respectively. Then, centrality analysis is applied on the building-network, aiming to reveal the crucial relationships among buildings, which is useful for understanding the structural properties of the complex network. Four different centrality measures, i.e. degree, closeness, betweenness, and eigenvector centrality, are calculated based on the building-networks. The buildings show different distribution effects and patterns under the four centrality measures. From the results, the degree centrality reveals the local centre of the region; closeness and eigenvector centrality have the ability to cluster buildings into different groups; while betweenness centrality can detect the linear patterns. Therefore, using network theory to analyse buildings can reveal some inner relationships of buildings and has great potential in the application of building pattern detection, classification, clustering and further generalization.
    Type of Medium: Online Resource
    ISSN: 2570-2092
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2019
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  • 6
    Online Resource
    Online Resource
    Copernicus GmbH ; 2018
    In:  Proceedings of the ICA Vol. 1 ( 2018-05-16), p. 1-8
    In: Proceedings of the ICA, Copernicus GmbH, Vol. 1 ( 2018-05-16), p. 1-8
    Abstract: Abstract. This paper presents a new strategy for the generalization of discrete area features by using stroke grouping method and polarization transportation selection. The mentioned stroke is constructed on derive of the refined proximity graph of area features, and the refinement is under the control of four constraints to meet different grouping requirements. The area features which belong to the same stroke are detected into the same group. The stroke-based strategy decomposes the generalization process into two sub-processes by judging whether the area features related to strokes or not. For the area features which belong to the same one stroke, they normally present a linear like pat-tern, and in order to preserve this kind of pattern, typification is chosen as the operator to implement the generalization work. For the remaining area features which are not related by strokes, they are still distributed randomly and discretely, and the selection is chosen to conduct the generalization operation. For the purpose of retaining their original distribution characteristic, a Polarization Transportation (PT) method is introduced to implement the selection operation. Buildings and lakes are selected as the representatives of artificial area feature and natural area feature respectively to take the experiments. The generalized results indicate that by adopting this proposed strategy, the original distribution characteristics of building and lake data can be preserved, and the visual perception is pre-served as before.
    Type of Medium: Online Resource
    ISSN: 2570-2092
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2018
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