Journal of Transport Geography最新文献

{"title":"Does the streetscape built environment matter in explaining crash injury severity among older adults?","authors":"Kaihan Zhang ,&nbsp;Boyou Chen ,&nbsp;Reuben Tamakloe ,&nbsp;Yihang Bai ,&nbsp;Inhi Kim","doi":"10.1016/j.jtrangeo.2025.104540","DOIUrl":"10.1016/j.jtrangeo.2025.104540","url":null,"abstract":"<div><div>Elderly pedestrians, due to physical vulnerability, are among the most at-risk road users. With global aging trends, ensuring safe mobility for older adults, who often rely on walking, presents significant transportation challenges. Effective streetscape design is essential for their safety, yet the impact of streetscape quality on injury severity remains underexplored, largely due to limitations in measuring these environmental features. This study addresses this gap by examining how streetscape features might affect injury severity among elderly pedestrians, employing street view imagery and computer vision. Both crash-related factors and perceived streetscape design features are incorporated into an explainable ensemble learning framework. Using Seoul, South Korea, as a case study, preliminary results indicate that while pedestrian attributes, especially age, are the primary determinants of injury severity, streetscape features such as imageability (visual diversity), greenness, and enclosure also contribute significant explanatory power in predicting elderly injury severity. Specifically, Higher levels of street enclosure and imageability are associated with reduced injury severity, while moderate levels of greenness correlate with lower injury risk. However, exceeding a certain greenness threshold appears to increase risk, suggesting that merely increasing street level greenness does not always yield extra benefits that reduce the likelihood of more severe injuries. Spatial analyses highlight southeast Seoul as a priority for streetscape improvements. These results provide actionable insights for planners, guiding cost-effective interventions to enhance elderly pedestrian safety.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104540"},"PeriodicalIF":6.3,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating human mortality impacts from air pollution as U.S. commuting reaches its extremes","authors":"Yue Jing ,&nbsp;Yujie Hu ,&nbsp;Chen Chen ,&nbsp;Daniel S. Cohan","doi":"10.1016/j.jtrangeo.2025.104541","DOIUrl":"10.1016/j.jtrangeo.2025.104541","url":null,"abstract":"<div><div>Commuting significantly influences environmental quality and public health, thereby shaping urban sustainability. However, the effects of air pollution from vehicle emissions and associated mortality at both lower and upper commuting extremes remain unexplored. This study utilizes nationwide commuting flow and geodemographic segmentation datasets to implement a disaggregated excess commuting framework across 918 U.S. metropolitan regions (MSAs). Three reduced-complexity air quality health effect models are then employed to assess changes in vehicle emissions and related mortality for these extreme scenarios. Results show that achieving the minimum commuting scenario could prevent approximately 1273 premature deaths nationwide, whereas the maximum commuting scenario could result in 3480 additional deaths linked to elevated air pollution. These impacts vary considerably across urban forms and regions, with densely populated, polycentric MSAs accounting for over 70 % of total mortality changes. In some MSAs, health outcomes diverge from emission changes due to geographic factors that influence pollutant dispersion. Overall, the findings highlight the need for targeted policies that promote more sustainable and health-conscious mobility systems.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104541"},"PeriodicalIF":6.3,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing the effects of the transportation environment and green spaces on residents' satisfaction","authors":"Hanyan Li,&nbsp;Jing Ma,&nbsp;Sui Tao","doi":"10.1016/j.jtrangeo.2025.104536","DOIUrl":"10.1016/j.jtrangeo.2025.104536","url":null,"abstract":"<div><div>The transportation environment and green spaces play important roles in well-being. Nonetheless, research on the combined effects of the transportation environment and green spaces on both short-term and long-term satisfaction is scarce. Using survey data from Beijing, this research aims to reveal the mutual relationships among commute satisfaction, daily travel satisfaction and life satisfaction. Furthermore, it examines the role of objective/perceived transportation environment and green spaces in commuting characteristics and satisfaction at different time scales, controlling for urban form factors and socioeconomic attributes. The results reveal that commute, daily travel, and life satisfaction are interrelated and mutually reinforcing. Perceived transport accessibility is related to satisfaction at multiple time scales, whereas travel costs, road connectivity and safety are directly associated with daily travel satisfaction only. Subway density has direct and indirect effects on commute satisfaction and daily travel satisfaction, mediated by perceived transport accessibility and travel costs. Moreover, green space density is indirectly related to satisfaction through its effect on people's perceptions. This study provides policy implications for optimizing the geographical environment to improve residents' well-being.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104536"},"PeriodicalIF":6.3,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Context-dependent effects of built environment on public transit gap: A case study of Taipei Metropolitan Area","authors":"Yao-Feng Liu,&nbsp;Yi-Shih Chung","doi":"10.1016/j.jtrangeo.2025.104542","DOIUrl":"10.1016/j.jtrangeo.2025.104542","url":null,"abstract":"<div><div>This study proposes a two-step evaluation framework to identify and analyze public transit gap, with a focus on disadvantaged populations. First, we construct composite Indices of Public Transit Need (IPTN) and Provision (IPTP) using a set of demographic, infrastructural, and land use variables, weighted via the entropy weight method (EWM). The difference between IPTN and IPTP yields the Index of Public Transit Gap (IPTG), a relative, unitless measure of disparity. Second, a geographically weighted regression (GWR) model is applied to assess how built environment characteristics and road network patterns relate to the IPTG across the Taipei Metropolitan Area (TMA). The results reveal significant spatial heterogeneity: while transit gap is minimal in central Taipei due to dense service networks, peripheral areas exhibit high IPTG values driven by low infrastructure density and socio-demographic need. Commercial land use consistently correlates with reduced transit gaps, whereas residential, agricultural, and industrial land uses show more variable associations. The spatial decomposition of need and provision, combined with GWR analysis, offers nuanced insights for location-specific policy interventions. The proposed framework provides a flexible, scalable tool for diagnosing transit equity issues and can be extended to other metropolitan contexts. Future research should consider longitudinal analysis and compare relative and absolute measures of transit inequality to inform more comprehensive policy development.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104542"},"PeriodicalIF":6.3,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond the plug: Enhancing the user experience at public electric vehicle (EV) charging hubs. Insights from a multi-site UK study","authors":"Labib Azzouz ,&nbsp;Christian Brand ,&nbsp;Tina Fawcett ,&nbsp;Zhaoqi Zhou ,&nbsp;Maryam Altaf","doi":"10.1016/j.jtrangeo.2025.104530","DOIUrl":"10.1016/j.jtrangeo.2025.104530","url":null,"abstract":"<div><div>As electric vehicle (EV) adoption accelerates, the need for accessible, efficient, and inclusive charging infrastructure has become increasingly critical. However, the user experience at public EV charging stations remains largely underexplored. Existing research often focuses narrowly on instrumental dimensions of the charging process, overlooking attitudinal and affective aspects. Addressing this and other gaps, this study investigates diverse instrumental, attitudinal, and affective user experiences at public EV charging hubs, focusing on accessibility, usability, and reliability. An onsite questionnaire gathered data on user demographics, journey characteristics, EV driving patterns, charging habits and preferences, and (30) EV charging experiences. Beyond traditional performance ratings, the study differentiated between expected and actual ‘realised’ experiences, calculating disgruntlement scores and dissatisfaction levels. Findings suggested that expectations were highest for ease of use and payment, availability of functioning rapid chargers, station accessibility, and perceptions of safety, security, and hygiene. Aggregate disgruntlement analysis identified dissatisfaction with remote assistance, mobile app usability, clarity in data sharing and costs, and service information provision. MANOVA results revealed significant cross-hub variations, underscoring the impact of location and site-specific characteristics. Additionally, factors such as age, trip purpose, charging duration, EV driving experience, residential location, and user type significantly influenced experiences. The ‘combined’ influence of hubs and user- and trip-related factors revealed further novel insights. The study concluded by highlighting areas for improvement and interventions. It is hoped that the findings and recommendations discussed will assist policymakers, planners, designers, and operators in creating more efficient, equitable, and inclusive EV charging hubs, supporting wider EV transitions.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104530"},"PeriodicalIF":6.3,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging data gaps for EV demand estimation: A transfer learning approach","authors":"Farnoosh Roozkhosh ,&nbsp;X. Angela Yao ,&nbsp;Behnam Tahmasbi ,&nbsp;Hao Yang ,&nbsp;Gengchen Mai","doi":"10.1016/j.jtrangeo.2025.104539","DOIUrl":"10.1016/j.jtrangeo.2025.104539","url":null,"abstract":"<div><div>Data sparsity poses a significant challenge for training AI models. For Electric Vehicle (EV) demand forecasting, abundant data is available in some states, while others lack sufficient data. Transfer Learning (TL) presents a promising solution for regions with limited data, facilitating more strategic infrastructure planning. Using charging-station location and EV-registration data drawn from state vehicle-registration databases, we build a combined socio-demographic and GIS-based spatial database and apply two distinct TL methodologies: an ensemble-based approach and a neural-network approach. This study develops and compares two TL frameworks: a Random Forest Transfer Learning Model (RFTLM) and an Artificial Neural Network Transfer Learning Model (ANNTLM) to predict demand for Tesla and non-Tesla users in Minnesota (target region) using pre-trained models from Colorado (source region). Although both states have sufficient data, the study treats the target region as a data-scarce area and utilizes only a portion of the available data for the AI model adaptation via transfer learning, while testing the transfer learning model results against the remaining data. We implement semi-supervised pseudo-labeling to augment sparse target samples and evaluate model performance across multiple local data fractions (5 %–90 %). In the proposed approach, the models are trained on a comprehensive dataset of socioeconomic variables and charging accessibility metrics from the source state, then fine-tuned with varying fractions of local data in the target state.</div><div>Results demonstrate that both RFTLM and ANNTLM models significantly improve prediction accuracy as more local data become available. However, even with only 5 % of labeled data from the target region, both TL models yield viable forecasts, underlining the effectiveness of knowledge transfer from data-rich to data-scarce settings. The RFTLM consistently achieves higher accuracy and better explanatory power than the ANNTLM, with key factors such as the overall charging station accessibility (particularly non-Tesla stations), median income, and population density emerging as the most influential features. These findings highlight that TL can mitigate data limitations in demand forecasting, offering a scalable solution for policymakers and planners seeking to expand EV adoption through well-informed, equitable investment in charging infrastructure.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104539"},"PeriodicalIF":6.3,"publicationDate":"2025-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145813888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Platform-induced time-space trade-offs in ride-hailing: Multi-homing as a response to operational constraints","authors":"Chutian Zhuang ,&nbsp;Tianqi Gu ,&nbsp;Inhi Kim ,&nbsp;Hyungchul Chung ,&nbsp;Kaihan Zhang","doi":"10.1016/j.jtrangeo.2025.104533","DOIUrl":"10.1016/j.jtrangeo.2025.104533","url":null,"abstract":"<div><div>This study examines how ride-hailing drivers adjust their time-use and spatial behavior under platform-induced constraints, with a focus on multi-homing—the practice of operating across multiple ride-hailing platforms. Drawing on a city-scale, driver-identified dataset from Suzhou, China, we propose a data-driven framework to identify multi-homing behavior and quantify its impacts using four operational metrics: working hours, travel distance, revenue, and order interval. A common assumption is that full-time multi-homing drivers earn more and work longer than single-platform drivers. However, our results show that this assumption does not hold in the Suzhou market. Instead, multi-homing appears to serve as a behavioral adaptation to regulatory and algorithmic restrictions—allowing drivers to bypass platform-imposed work-hour caps and optimize engagement with temporal demand fluctuations. Using clustering to separate full-time and part-time drivers, and applying Geographically Weighted Random Forest (GWRF) modeling, we further find that multi-platform activity is not spatially concentrated in low-demand or remote areas. These findings reveal that multi-homing is less about spatial expansion and more about temporal strategy and coping with institutional uncertainty. The study contributes to understanding time-space adaptation in digitally mediated mobility, especially amid evolving platform governance. It also underscores the need for time-use models and transport policy to account for the real-time flexibility and constraint navigation strategies employed by gig workers in fragmented digital environments.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104533"},"PeriodicalIF":6.3,"publicationDate":"2025-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145813889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing transgender mobility on public transport through equitable transport policies in a culturally conservative society","authors":"Nazam Ali ,&nbsp;Muhammad Ashraf Javid ,&nbsp;Ryan Cheuk Pong Wong ,&nbsp;Muhammad Abdullah ,&nbsp;Syed Sift-E-Hassan ,&nbsp;Punyaanek Srisurin ,&nbsp;Qudeer Hussain","doi":"10.1016/j.jtrangeo.2025.104532","DOIUrl":"10.1016/j.jtrangeo.2025.104532","url":null,"abstract":"<div><div>Transgender individuals have visible gender expressions that distinguish them from other gender minorities, including lesbian, gay, bisexual or queer individuals. This visibility increases their vulnerability to gender-based violence and harassment in public spaces, and restricts their mobility on public transport and access to basic amenities for healthcare, education and employment. This issue is particularly severe in culturally conservative societies. This study aims to address the issue by exploring public acceptance of transgender individuals on public transport in Pakistan and recommending equitable transport policies for enhancing their mobility. Using the conceptual framework of the theory of planned behavior (TPB), a questionnaire was developed, and 474 responses were collected via an online survey. A multivariate structural equation model (SEM) was developed, and the results reveal that perceived behavioral control and intentions have a positive and significant relationship with transport policy interventions. Regarding the socioeconomic characteristics, male individuals, those with higher education, and those who meet transgender individuals more often, exhibit positive attitudes towards supportive transport policies aimed at enhancing transgender mobility on public transport. According to the findings, numerous equitable transport policies such as providing dedicated spaces and seats on public transport for transgender individuals, implementing dedicated car-sharing programs, enforcing transgender protection acts, and improving public acceptance through education and awareness campaigns, are recommended.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104532"},"PeriodicalIF":6.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the interplay between public transport travel time variability and jobs competition on accessibility inequalities","authors":"Carlos Kaue V. Braga ,&nbsp;Carlos Felipe Grangeiro Loureiro ,&nbsp;Rafael H.M. Pereira","doi":"10.1016/j.jtrangeo.2025.104526","DOIUrl":"10.1016/j.jtrangeo.2025.104526","url":null,"abstract":"<div><div>Recent studies have examined socio-spatial inequalities in public transport accessibility in Global South cities, consistently showing that lower-income groups face reduced access. However, most rely on scheduled GTFS data to estimate travel times, ignoring day-to-day travel time variability caused by congestion or service disruptions. This oversight limits our understanding of how such variability impacts accessibility levels and inequalities – especially when using more robust indicators that account for competition over opportunities. Emerging research points to a complex interplay between travel time variability and competition for activities, with potential to bias inequalities assessments. Yet, these effects remain underexplored. This study addresses such gap by integrating GPS and GTFS data to assess how daily fluctuations in transit performance affect job accessibility and inequality estimates using both cumulative and competition-based metrics. Using data from Fortaleza, Brazil, our findings show that day-to-day variability significantly influences both accessibility levels and inequalities – regardless of the indicator used. When jobs competition is considered, socio-spatial inequalities widen, as variability is generally lower in central areas and higher in the periphery. Moreover, competition-based measures – adding the interaction between the population distribution, the location of job opportunities, and the level-of-service of the public transport system – amplify the effects of variability, leading to greater observed disparities than cumulative metrics. These findings highlight a critical link between transit reliability and accessibility inequalities, underscoring the need for future studies and policy evaluations to consider travel time variability and competition effects when assessing equitable access to opportunities in Global South metropolises.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104526"},"PeriodicalIF":6.3,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Geopolitics and the geography of global shipping","authors":"Pengjun Zhao, Cesar Ducruet, Mengzhu Zhang, Hans-Dietrich Haasis","doi":"10.1016/j.jtrangeo.2025.104531","DOIUrl":"https://doi.org/10.1016/j.jtrangeo.2025.104531","url":null,"abstract":"","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"9 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145785283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}