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Article

Spatial Paradigms in Road Networks and Their Delimitation of Urban Boundaries Based on KDE

1
College of Tourism, Fujian Normal University, Fuzhou 350117, China
2
College of Geographical Science, Fujian Normal University, Fuzhou 350117, China
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College of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350108, China
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College of Material Engineering, Fujian Agriculture and Forestry University, Fuzhou 350108, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(4), 204; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9040204
Received: 18 February 2020 / Revised: 10 March 2020 / Accepted: 26 March 2020 / Published: 28 March 2020
An in-depth analysis of urban road network distribution plays a critical role in understanding the urbanization process. However, effective ways to quantitatively analyze the spatial paradigms of road networks are still lacking, and few studies have utilized road networks to rapidly identify urban areas of a region. Thus, using a fast-developing region in the south-eastern costal region of China, Fuzhou City, as a case, we introduced kernel density estimation (KDE) to characterize road networks and quantified the area’s spatial heterogeneity using exploratory spatial data analysis (ESDA) and semivariance analysis (SA). The results show that there is an uneven spatial distribution of the networks both at the regional and downtown levels. At the regional level, there is a conspicuous polarization in the road distribution, with the KDE being much higher in the urban areas than in the rural areas; at the downtown level, the KDE gradually decreases from the center to the periphery. Quantitatively, the ranges of the spatial dependence of the networks are approximately 25 km for the entire study region and 12 km for the downtown area. Additionally, the spatial variations vary among different directions, with greater variations in the northeast–southwest and the southeast–northwest directions compared with the other directions, which is in line with the urban sprawl policy of the study area. Both the qualitative and quantitative results show that the distribution of road networks has a clear urban–rural dual structure, which indicates that road networks can be an active tool in identifying the urban areas of a region. To this end, we propose a quick and easy method to delimit urban areas using KDE. The extraction results of KDE are better than those of the index-based built-up index (IBI), indicating the effectivity and feasibility of our proposed method to identify the urban areas in the region. This research sheds new light on urbanization development research. View Full-Text
Keywords: kernel density estimation; remote sensing; urbanization; road network; index-based built-up index; urban boundary kernel density estimation; remote sensing; urbanization; road network; index-based built-up index; urban boundary
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MDPI and ACS Style

Lin, Y.; Hu, X.; Lin, M.; Qiu, R.; Lin, J.; Li, B. Spatial Paradigms in Road Networks and Their Delimitation of Urban Boundaries Based on KDE. ISPRS Int. J. Geo-Inf. 2020, 9, 204. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9040204

AMA Style

Lin Y, Hu X, Lin M, Qiu R, Lin J, Li B. Spatial Paradigms in Road Networks and Their Delimitation of Urban Boundaries Based on KDE. ISPRS International Journal of Geo-Information. 2020; 9(4):204. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9040204

Chicago/Turabian Style

Lin, Yuying, Xisheng Hu, Mingshui Lin, Rongzu Qiu, Jinguo Lin, and Baoyin Li. 2020. "Spatial Paradigms in Road Networks and Their Delimitation of Urban Boundaries Based on KDE" ISPRS International Journal of Geo-Information 9, no. 4: 204. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9040204

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