Against the backdrop of increasingly prevalent global urban shrinkage, shrinking cities face challenges such as population loss, fiscal pressure, and imbalanced public service provision. The spatial configuration of living service facilities directly impacts residents’ well-being, but these microscale spatial mechanisms within shrinking cities remain underexplored. This study investigates Hegang, a typical shrinking city in Northeast China, using POI data, census data, and road networks. Through kernel density analysis, location quotients, network analysis, and bivariate spatial autocorrelation, the distribution, supply-demand matching, and accessibility of living service facilities at the subdistrict level were evaluated. Results show that 75% of Hegang’s subdistricts experienced population loss between 2010 and 2020, creating a “central growth, peripheral shrinkage” pattern. Shrinking subdistricts exhibit a “high density-low accessibility” paradox. Location quotient analysis reveals oversupply in shrinking subdistricts and undersupply in growing subdistricts. Bivariate spatial autocorrelation analysis indicates a negative correlation between accessibility and population density for most facilities, with 29.4% of subdistricts facing a supply-demand imbalance. This study reveals significant mismatches between facility configuration and resident needs in shrinking cities, providing a theoretical basis and practical guidance for “smart shrinkage” planning, helping to optimize resource allocation and enhance urban livability and sustainable development capacity.
Cao et al. (Thu,) studied this question.