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

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 s...

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Main Authors: Teng Li, Zhuo Chen, Shuli Luo, Alexa Delbosc
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Multimodal Transportation
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2772586325000577
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author Teng Li
Zhuo Chen
Shuli Luo
Alexa Delbosc
author_facet Teng Li
Zhuo Chen
Shuli Luo
Alexa Delbosc
author_sort Teng Li
collection DOAJ
description 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.
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spelling doaj-art-39538ebd13cc442d9ba7ea6be40f3eb82025-08-20T02:39:41ZengElsevierMultimodal Transportation2772-58632025-12-014410024310.1016/j.multra.2025.100243Assessing the spatial heterogeneous impacts of urban heat island effects on active travel by leveraging social media dataTeng Li0Zhuo Chen1Shuli Luo2Alexa Delbosc3Department of Civil Engineering, Monash University, 23 College Walk, Clayton 3800, AustraliaDepartment of Civil Engineering, Monash University, 23 College Walk, Clayton 3800, Australia; Corresponding author.Faculty of Humanities and Social Science, Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China,Department of Civil Engineering, Monash University, 23 College Walk, Clayton 3800, AustraliaThis 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.http://www.sciencedirect.com/science/article/pii/S2772586325000577Urban heat islandActive travelTwitterMGWR
spellingShingle Teng Li
Zhuo Chen
Shuli Luo
Alexa Delbosc
Assessing the spatial heterogeneous impacts of urban heat island effects on active travel by leveraging social media data
Multimodal Transportation
Urban heat island
Active travel
Twitter
MGWR
title Assessing the spatial heterogeneous impacts of urban heat island effects on active travel by leveraging social media data
title_full Assessing the spatial heterogeneous impacts of urban heat island effects on active travel by leveraging social media data
title_fullStr Assessing the spatial heterogeneous impacts of urban heat island effects on active travel by leveraging social media data
title_full_unstemmed Assessing the spatial heterogeneous impacts of urban heat island effects on active travel by leveraging social media data
title_short Assessing the spatial heterogeneous impacts of urban heat island effects on active travel by leveraging social media data
title_sort assessing the spatial heterogeneous impacts of urban heat island effects on active travel by leveraging social media data
topic Urban heat island
Active travel
Twitter
MGWR
url http://www.sciencedirect.com/science/article/pii/S2772586325000577
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AT shuliluo assessingthespatialheterogeneousimpactsofurbanheatislandeffectsonactivetravelbyleveragingsocialmediadata
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