Identification and Classification of Urban Shrinkage in Northeast China

Xiaosong Ma, Qingwu Yan (), Qinke Pan, Xingshan Chen and Guie Li
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Xiaosong Ma: China Research Center for Resource-Based Urban Transformation and Development and Rural Revitalization, China University of Mining and Technology, Xuzhou 221116, China
Qingwu Yan: China Research Center for Resource-Based Urban Transformation and Development and Rural Revitalization, China University of Mining and Technology, Xuzhou 221116, China
Qinke Pan: China Research Center for Resource-Based Urban Transformation and Development and Rural Revitalization, China University of Mining and Technology, Xuzhou 221116, China
Xingshan Chen: China Research Center for Resource-Based Urban Transformation and Development and Rural Revitalization, China University of Mining and Technology, Xuzhou 221116, China
Guie Li: China Research Center for Resource-Based Urban Transformation and Development and Rural Revitalization, China University of Mining and Technology, Xuzhou 221116, China

Land, 2023, vol. 12, issue 6, 1-22

Abstract: The phenomenon of shrinking cities is a significant challenge faced by many cities today. To more accurately identify the leading factors driving urban shrinkage and develop rational recommendations, precise identification and classification of urban shrinkage has become an indispensable part of the process. This paper focuses on the typical population loss region of China’s three northeastern provinces, using 497 identified physical cities as the basic research unit. Based on multi-source geographical big data and utilizing the geographically weighted regression (GWR) model, spatial modeling of population in the three provinces of northeast China was conducted, resulting in spatialized population data, followed by identification and classification of shrinking cities among the physical cities. Cities with a total population change rate of less than 0 are defined as shrinking cities. In cities where the total population change rate is greater than 0, cities with both a city shrinking area ratio and a decreased population ratio greater than 5% are defined as locally shrinking cities. Based on this, 90 (18.1%) shrinking cities and 118 (23.7%) locally shrinking cities were identified within the three provinces of northeast China. The phenomenon of urban shrinkage is distributed throughout various regions, mainly in smaller cities located near larger cities. According to the standards of the urban shrinkage classification model, the spatial pattern of population loss regions was divided into four types, identifying 13 (6.3%) global type, 111 (53.4%) concentrated type, 64 (30.7%) perforated type, and 20 (9.6%) edge type. Analysis of shrinking cities based on their classification revealed that the main reasons for urban shrinkage are the decline and dissolution of large industrial enterprises, abandonment and neglect of buildings, and unreasonable design planning in cities. Economic development and inward population flow can be promoted in shrinking cities by creating job opportunities, improving living standards, developing transportation, adjusting urban planning or concentrating urban population, as well as vigorously developing urban center areas. These measures can provide support for the revival and development of shrinking cities.

Keywords: urban shrinkage; physical cities; population spatialization; spatial patterns of population change (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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