Spatiotemporal Characteristics of Built Environment Impacts on Street Vitality in Central Nanchang: A Multiscale Geographically Weighted Regression Approach

Abstract

Exploring the impact of the built environment on street vitality is essential for enhancing urban public spaces. Using the central urban area of Nanchang City as a case study, multi-temporal street vitality is measured with popula-tion heat data. A multi-dimensional built environment indicator system is de-veloped based on macro-scale neighborhood composition and micro-scale street characteristics, using street view imagery, POI data, and OSM road network data. The spatiotemporal variations in the influence of built envi-ronment factors on street vitality are examined through a multiscale geo-graphically weighted regression (MGWR) model. Results reveal that: (1) Street vitality is most prominent between 10:00 and 20:00, with a spatial pattern of "eastern core, western belt, and multiple clustered points" across all time periods. (2) Macro-scale neighborhood composition generally has a stronger impact on street vitality than micro-scale street characteristics. (3) The influence of various built environment factors on street vitality exhibits significant spatiotemporal heterogeneity. Factors like sky view openness and parking lot density show robust spatiotemporal variations, while con-nectivity, facility densities, walkability, street ratio, and green view index have localized spatiotemporal effects.