Qinglin Wu

Mr. Qinglin Wu

Institute of Tibetan Plateau Research, Beijing, China
orcid

Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 August 2025
Verified
Conference Paper
Open access
JLJunYong Lin
JunYong Lin
LDLu Dai
Lu Dai
RHRuiqian Han
Ruiqian Han
YSYijie Sui
Yijie Sui
RWRuilin Wang
Ruilin Wang
HXHui Xiong
Hui Xiong

Verified
Journal Article
Open access
PDF file
Liang KongLiang Kong
Liang Kong
Qinglin WuQinglin Wu
Qinglin Wu
JDJie Deng
Jie Deng
BLBai Leichao
Bai Leichao
Zhongsheng ChenZhongsheng Chen
Zhongsheng Chen
MLMingliang Luo
Mingliang Luo
With the deepening of urbanization in China, the coordinated development of cities in different regions is an important part of the sustainable development of the country, and the reasonable quantification of the unbalanced development of cities in different regions is an important issue facing the society nowadays. Previous studies usually use population data to analyze the power-law distribution law to quantify the imbalance of urban development in different regions, but China’s population data span a large number of years and numerous division criteria, and the results obtained from different population data are widely disparate and have obvious limitations. The paper starts from a fractal perspective and utilizes OpenStreetMap (OSM) data to extract national road intersections from 2015 to 2022, calculates critical distance thresholds for eight years using urban expansion curves, generates urban agglomerations in China, and quantifies the imbalance of urban development in different regions by calculating the urban agglomeration power-law index. The results indicate that (1) the critical distance threshold of urban expansion curves exhibits a slight overall increase and stabilizes within the range of 120–130 m, (2) the number of urban agglomerations in China has been increasing significantly year by year, but the power-law index has been decreasing from 1.49 in 2015 to 1.36 in 2022, and (3) the number of urban agglomerations and the power–law index of the Beijing–Tianjin–Hebei, Yangtze River Delta, Pearl River Delta, and Chengdu–Chongqing regions, which is consistent with the national scale trend, indicates that the scale distribution of urban agglomerations in China at this stage does not conform to Zipf’s law, and there is a certain Matthew effect among cities in different geographic areas with a large unevenness. The results of the study can provide new ideas for assessing the coordinated development of cities in different regions. It compensates for the instability of population and economic data in traditional studies.