Abstract
With rapid urban growth, metro stations are crucial transportation hubs attracting significant activity. Most studies assess metro stations within Transit-Oriented Development (TOD) frameworks, often overlooking the livability of surrounding areas from a human-centric perspective. This study proposes a multifaceted method to assess livability within a 15-minute travel circle of metro stations, incorporating spatial accessibility, environmental quality, functional diversity, and flow variance. Using Singapore as a case study, we developed a novel framework to calculate Livability Mixed Entropy (LME) utilizing data from Open Street Map (OSM), Street View Imagery (SVI), Place Pulse, Points of Interest (POI), and smart card data. A clustering algorithm that considers complex features and spatial dependencies identified five distinct clusters: Dynamic Urban Core, Serene Residential Area, Convenient Living Area, Cultural and Commercial Intersection, and Emerging Urban District. Our findings highlight the spatial distribution and typological characteristics of these clusters, providing valuable insights for urban planners. This study underscores the importance of tailored urban planning approaches that enhance connectivity, multifunctionality, and accessibility to foster sustainable and high-quality urban living. The LME metric, validated through the Singapore case, offers a robust tool for assessing urban livability and is adaptable to other high-density cities, contributing to sustainable urban development discourse.
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•Created the Liveability Mixed Entropy (LME) metric to assess metro station area livability.•Integrated spatial accessibility, environmental quality, functional diversity, and flow variance for livability assessment.•Used clustering algorithms to identify metro station types from a human-centric perspective.•Focused on Singapore, offering insights for high-density cities worldwide.