A Geospatial-Enabled Multidimensional Framework for Livability Evaluation in High-Density Cities: Evidence from Hong Kong

Hong Kong faces pressing high-density urban challenges, including high population density, aging demographics, and socio-spatial inequalities. However, traditional methods often lack resident subjectivity and cannot accurately show the distribution of livability within a city, necessitating a refined approach to urban livability assessment. This study developed a multidimensional geospatial framework integrating physical environment, socio-economic, and spatial walkability metrics. Utilizing PCA-AHP hybrid weighting, we calculated a fine-scale objective livability index (OLI), validated against subjective survey data. Results revealed moderate spatial autocorrelation (Moran’s I = 0.469, p < 0.01) of OLI with disparities between central and peripheral areas. And antagonistic tradeoffs emerged where high-density zones sacrifice environmental quality for walkability. Residual analysis further revealed statistically significant spatial mismatches between objective conditions and residents’ perceived well-being, i.e., subjective livability index (SLI), and indicated that areas with balanced dimensions usually had higher SLI. Overall, this study contributes to urban planning by enabling geospatial analytics and objective-subjective comparison, with future extensions incorporating social media data and other types of subjective indicators for people-centric evaluation.