2019
DOI: 10.3390/ijgi8050238
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Extracting Main Center Pattern from Road Networks Using Density-Based Clustering with Fuzzy Neighborhood

Abstract: The spatial pattern is a kind of typical structural knowledge that reflects the distribution characteristics of object groups. As an important semantic pattern of road networks, the city center is significant to urban analysis, cartographic generalization and spatial data matching. Previous studies mainly focus on the topological centrality calculation of road network graphs, and pay less attention to the delineation of main centers. Therefore, this study proposes an automatic recognition method of main center… Show more

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Cited by 6 publications
(2 citation statements)
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“…The spatial distributions of these regions indicate that the spatial preference of urban growth may surround the urban centers. The density of road networks and nodes was used to generate the main center area in the literature [60]. Inspired by this, we united these aggregation areas to extract the gravity center of Hangzhou.…”
Section: Discovering City Centers Through Street Name Datamentioning
confidence: 99%
“…The spatial distributions of these regions indicate that the spatial preference of urban growth may surround the urban centers. The density of road networks and nodes was used to generate the main center area in the literature [60]. Inspired by this, we united these aggregation areas to extract the gravity center of Hangzhou.…”
Section: Discovering City Centers Through Street Name Datamentioning
confidence: 99%
“…However, the algorithm is sensitive to noise points and has high time complexity. The density-based clustering algorithm [20] is measured by density correlation between data points; according 2 Wireless Communications and Mobile Computing to the setting threshold, the density of the density exceeds the threshold of the adjacent areas connected data cluster. Compared with partitioning-based clustering, density-based clustering can find the clustering with arbitrary shapes, and the unique outlier processing strategy can process the abnormal data effectively.…”
Section: Introductionmentioning
confidence: 99%