Differences in Urban Development in China from the Perspective of Point of Interest Spatial Co-Occurrence Patterns

Author:

Dong Guangsheng123ORCID,Li Rui123ORCID,Li Fa4ORCID,Liu Zhaohui123,Wu Huayi123ORCID,Xiang Longgang123ORCID,Yu Wensen5,Jiang Jie67,Zhang Hongping78,Li Fangning9

Affiliation:

1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

2. Hubei Luojia Laboratory, Wuhan 430079, China

3. Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China

4. Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA

5. Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry, Wuyi University, Wuyishan 354300, China

6. Key Laboratory of Urban Spatial Information, Ministry of Natural Resources, Beijing 100044, China

7. School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing 100044, China

8. National Geomatics Center of China, Beijing 100830, China

9. Beijing Urban Construction Exploration & Surveying Design Research Institute Co., Ltd., Beijing 100101, China

Abstract

An imbalance in urban development in China has become a contradiction. Points of Interest (POIs) serve as representations of the spatial distribution of urban functions. Analyzing POI spatial co-occurrence patterns can reveal the agglomeration patterns of urban functions across cities at different levels, providing insights into imbalances in urban development. Using POI data from 297 cities in China, the Word2vec model was employed to model the POI spatial co-occurrence patterns, allowing for the quantification of fine-granular urban functionality. Subsequently, the cities were clustered into five tiers representing different levels of development. An urban hierarchical disparity index and graph were introduced to examine variations in urban functions across different tiers. A significant correlation between POI spatial co-occurrence patterns and the GDP of cities at different levels was demonstrated. This study revealed a notable polarization trend characterized by the development of top-tier cities and lagging tail-end cities. Top-tier cities exhibit advantages in terms of their commercial environments, such as international banks, companies, and transportation facilities. Conversely, tail-end cities face deficiencies in urban infrastructure. It is crucial to coordinate resource allocation and establish sustainable development strategies that foster mutual support between the top-tier and tail-end cities.

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Hubei Provincial Natural Science Foundation of China

Open Project Program of Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry, Wuyi University

Open Fund of Key Laboratory of Urban Spatial Information, Ministry of Natural resources

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Geography, Planning and Development

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