Spatial Distribution and Morphological Identification of Regional Urban Settlements Based on Road Intersections

To measure and present urban size urban spatial forms, in solving problems in the rapid urbanization of China, urban territorial scope identification is essential. Although current commonly used methods can quantitatively identify urban territorial scopes to a certain extent, the results are display...

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Bibliographic Details
Published in:ISPRS international journal of geo-information Vol. 10; no. 4; p. 201
Main Authors: Kong, Liang, He, Zhengwei, Chen, Zhongsheng, Luo, Mingliang, Du, Zhong, Zhu, Fuquan, He, Li
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-04-2021
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Summary:To measure and present urban size urban spatial forms, in solving problems in the rapid urbanization of China, urban territorial scope identification is essential. Although current commonly used methods can quantitatively identify urban territorial scopes to a certain extent, the results are displayed using a continuous and closed curve with medium- and low-resolution images. This makes the acquisition and interpretation of data challenging. In this paper, by extracting discretely distributed urban settlements, road intersections in OpenStreetMap (OSM), electronic maps, and urban expansion curve based on fractal thoughts have been used to present urban territorial scope and spatial form. Guangzhou, Chengdu, Nanjing, and Shijiazhuang cities were chosen as the identification targets. The results showed that the distance threshold corresponding to the principal curvature point of the urban expansion curve plays a vital role in the extraction of urban settlements. Moreover, from the analysis, the optimal distance thresholds of urban settlements in Guangzhou, Chengdu, Nanjing, and Shijiazhuang were 132 m, 204 m, 157 m, and 124 m, respectively, and the corresponding areas of urban territorial scopes were 1099.36 km2, 1076.78 km2, 803.07 km2, and 353.62 km2, respectively. These metrics are consistent with those for the built-up areas.
ISSN:2220-9964
2220-9964
DOI:10.3390/ijgi10040201