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<p>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 = 0.45,&#xa0;<i>p</i> &lt; 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.</p>

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Mismatch between objective and subjective livability assessment: a case study in Hong Kong

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月1日

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  • Mingzhen Liu,
  • Xiaolin Zhu

摘要

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 = 0.45, 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.