Assessing the spatial heterogeneous impacts of urban heat island effects on active travel by leveraging social media data

Abstract

This study investigates the impacts of urban heat island (UHI) effects on active travel by leveraging social media data. A multiscale geographically weighted regression (MGWR) model is utilized to investigate the spatial heterogeneity of integrated influences of UHI effects, built environment, and sociodemographic factors on travel frequency for both peri-summer and all-year trips. The investigation is showcased in Greater Melbourne, Australia, where Twitter posts related to active travel were collected and analyzed to identify active travelers’ travel frequency in different suburbs. The results reveal that UHI effects had a significant negative impact on all suburbs, with greater intensity during peri-summer trips. Moreover, the results proved the spatial heterogeneity of the influence of UHI effects on active trips, with a more intensive influence in residential regions with high urban heat index values. Additionally, the density of tram stops, parkland areas, population density, and young adults had significant positive effects, while the unemployment rate and dwellings with one motor vehicle had negative impacts. This study contributes to the field of travel behavior analysis by completing location-contained social media data. Moreover, it identifies areas heavily impacted by UHI effects, enabling targeted measures such as expanding green spaces, using cooling materials, and enhancing energy practices to reduce UHI effects and promote a sustainable urban environment.