Physical Urban Area Identification Based on Geographical Data and Quantitative Attribution of Identification Threshold: A Case Study in Chongqing Municipality, Southwestern China

• Published in: Land (Basel) Vol. 12; no. 1; p. 30
• Main Authors: Wang, Dan, Kong, Liang, Chen, Zhongsheng, Yang, Xia, Luo, Mingliang
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-01-2023
• Subjects: adaptive optimal distance threshold; Cities; Economic factors; Fractals; GDP; geographical data; geographical detector; Gross Domestic Product; Identification; Identification methods; optimal distance threshold; Physical characteristics; physical urban area; Population density; Quantitative analysis; Regions; Remote sensing; Roads; Socioeconomic factors; Topography; Transportation networks; Urban areas; Urban development; urban expansion curve; Urban populations; Urban sprawl; Urbanization; China
• ISSN: 2073-445X; 2073-445X
• DOI: 10.3390/land12010030

Although some methods have identified the physical urban area to a certain extent, the driving factors for the identification threshold have not been studied deeply. In this paper, vector building data and road intersection data are used for comparative validation based on the urban expansion curve method to identify the physical urban area using the meso-city scale. The geographical detector technique is used to detect how and to what extent the urban spatial structure factors, geographical environment factors and social economic factors affect the optimal distance threshold of 22 administrative districts in the Chongqing municipality. The results based on the vector buildings are more precise and show the characteristics of the physical urban area of core-periphery distribution and the distribution along the water corridor. From the results of quantitative attribution, it was found that the road network density, building density, urbanization rate and urban population density, and their interaction with regional GDP, play a critical role in the optimal distance threshold, with the index value of influence degree ≥0.79. Under the influence of different factors, the optimal distance thresholds of 22 administrative districts show adaptive characteristics. Looking forward to the future, this study provides ideas for further research on the morphological characteristics and distribution laws of multi-spatial scale cities.