Diagnosing Urban Service Inequality through Grid-Based Spatial Analysis of Multi-Source POI Data: Evidence from Changchun and Hohhot, China

Urban service inequality and intra-urban spatial heterogeneity have become major challenges for sustainable urban development. However, existing studies often rely on administrative-scale statistics or aggregated indicators, which fail to capture fine-scale spatial disparities in urban service distribution. To address this limitation, this study proposes a grid-based spatial diagnostic framework using multi-source Point of Interest (POI) data. A 1 km × 1 km grid system is employed to characterize the spatial distribution of six categories of urban services through service intensity and accessibility indicators, enabling fine-scale identification of spatial inequality patterns. The results reveal significant inter-city differences in urban service organization. Changchun exhibits a relatively balanced polycentric structure with more evenly distributed urban services, whereas Hohhot demonstrates a more centralized monocentric pattern characterized by pronounced deficiencies in accommodation and lifestyle-related services. Both cities exhibit persistent core-periphery disparities, with service accessibility declining significantly toward peripheral areas. The proposed framework provides a transferable and spatially explicit approach for diagnosing urban service inequality, offering methodological support for fine-scale urban planning, infrastructure optimization, and evidence-based governance.