Relationship between the degree and spatial pattern of urban shrinkage based on nighttime light data: a case study of the old industrial area in Northeast China

ABSTRACT

Urban shrinkage is a common phenomenon worldwide, but the relationship between the degree and spatial pattern of urban shrinkage is unclear. This paper takes the old northeastern industrial base, a region with a concentration of shrinking cities in China, as the study area. With the help of multi-source remote sensing images, this study first identified the degree and spatial pattern of urban shrinkage, and then investigated their relationship using the chi-square test. A total of 63 physical urban areas were identified as shrinking cities during the period 2013–2018. Among them, the proportion of cities with moderate and severe shrinking was relatively high. The spatial patterns of urban shrinkage are classified as central shrinkage, peripheral shrinkage, perforation shrinkage and global shrinkage. The results of the chi-square test proved that the spatial pattern and degree of urban shrinkage are correlated. Mild shrinkage was usually peripheral shrinkage; moderate shrinkage was usually central and perforation shrinkage; and severe shrinkage was usually global shrinkage. Identifying the degree and spatial pattern of urban shrinkage and investigating their relationship help deepen the understanding of the urban shrinkage phenomenon at a theoretical level and help urban planners and policy makers propose multidimensional strategies to alleviate the development dilemma of shrinking cities on a practical level.

KEYWORDS:

• Shrinking city
• urban area
• nighttime light data
• urban pattern
• old northeastern industrial base

Acknowledgments

We gratefully acknowledge the grant from the National Natural Science Foundation of China [grant numbers 42171191,42201211,41771172], the Department of Science and Technology of Jilin Province [grant number 20220508025RC] and the China Postdoctoral Science Foundation [grant number 2018M641760].

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Natural Science Foundation of China: [grant numbers 42171191, 42201211, 41771172]; Science and Technology Development Plan Project of Jilin Province, China: [grant number 20220508025RC]; China Postdoctoral Science Foundation [grant number 2018M641760].