Journal of Transport Geography最新文献

{"title":"The impact of urban built environment on multi-mode public transportation behavior under abnormal weather conditions","authors":"Xiaoxia Wang ,&nbsp;Xiang Wang ,&nbsp;Zhenlong Fan ,&nbsp;Hong Zou ,&nbsp;Zhicheng Pan ,&nbsp;Peng Liu","doi":"10.1016/j.jtrangeo.2026.104566","DOIUrl":"10.1016/j.jtrangeo.2026.104566","url":null,"abstract":"<div><div>The integration of bike-sharing and metro systems is a key form of multimodal public transport (MPT), vital for alleviating urban traffic congestion. However, as bike-sharing operates in the external environment, it is susceptible to the impacts of the urban built environment and abnormal weather conditions. This study aims to identify the built environment characteristics that influence the resilience of this transfer system during abnormal weather. We established a spatial weight matrix and calculated the Global and Local Moran's I for the “bike-metro variation rate” (BMVR) to explore the spatial correlation of MPT trips among different traffic analysis zones (TAZs). Subsequently, a spatial Durbin model (SDM) was developed to analyze the impact of the urban built environment on MPT transfers under abnormal weather and to determine the spatial spillover effects between the built environments of TAZs. The research findings indicate that: (1) The impact of the urban built environment on BMVR exhibits a positive spatial correlation under abnormal weather. (2) Several built environment variables significantly influence transportation resilience. Specifically, a higher share of the commuting population and a greater density of public service facilities enhance system resilience by mitigating the decline in transfer volumes, whereas higher intersection density exacerbates the impact and reduces resilience. (3) Built environment variables also generate significant spatial spillover effects, revealing that transportation resilience is an area-wide phenomenon influenced by neighboring environments. The results of this study offer targeted guidance for urban planners aiming to build a more robust MPT system capable of withstanding weather-related shocks through the optimization of local built environments.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104566"},"PeriodicalIF":6.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110668","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":"2026-02-01","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":"Probabilistic space-time prisms in road networks with travel time uncertainties","authors":"Hui-Ping Chen ,&nbsp;Zhi-Chun Li ,&nbsp;Bi Yu Chen","doi":"10.1016/j.jtrangeo.2025.104544","DOIUrl":"10.1016/j.jtrangeo.2025.104544","url":null,"abstract":"<div><div>The space-time prism (STP) is a core concept in time geography for scheduling flexible activities given various space-time constraints. However, the classical STP model overlooks travel time uncertainties pervasive in real-world road networks. In this study, we propose a novel model, probabilistic STP, for scheduling flexible activities under travel time uncertainties. This model explicitly quantifies heterogeneous probabilities (or reliabilities) of completing flexible activities at space-time locations within the STP. Solution algorithms are developed to effectively construct probabilistic STPs in real-world road networks. The proposed model is further applied to evaluate accessibility under travel time uncertainties. Two accessibility measures are introduced by explicitly setting distinctive weightings to facilities based on their activity completion probabilities. A comprehensive case study is carried out by using real-world travel time distributions. Results of the case study show the effectiveness of the probabilistic STP model in the evaluations of accessibility to supermarkets.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104544"},"PeriodicalIF":6.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902905","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":"2026-02-01","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":"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":"2026-02-01","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":"Spatiotemporal heterogeneity-aware ridership prediThe calculation results are shction with MGWR-informed attention on CNN-BiLSTM","authors":"Zhenxing Yao ,&nbsp;Haoyue Xu ,&nbsp;Yang Zhao ,&nbsp;Liang Wang ,&nbsp;Xi Yang","doi":"10.1016/j.jtrangeo.2026.104577","DOIUrl":"10.1016/j.jtrangeo.2026.104577","url":null,"abstract":"<div><div>Accurate taxi ridership forecasting plays a vital role in enhancing passenger experience and mitigating the mismatch between taxi supply and demand. However, most existing methods approach the problem from a city-wide perspective, overlooking the spatiotemporal heterogeneity inherent in the built environment. Additionally, traditional forecasting models tend to emphasize temporal dynamics while neglecting spatially varying environmental features, resulting in limited adaptability and predictive accuracy. To address these challenges, this study proposes a novel framework that integrates Multiscale Geographically Weighted Regression (MGWR) as an attention mechanism into a deep learning model to capture the complex interplay between urban form and ridership. MGWR is first used to uncover localized, multiscale dependencies between taxi demand and built environment variables, effectively characterizing regional heterogeneity. These insights are then embedded as spatial attention signals into a CNN-BiLSTM model, enhancing its ability to fuse spatial and temporal patterns for improved ridership forecasting. Extensive experiments on real-world taxi data from Chengdu, China, demonstrate the effectiveness of the proposed method. The results reveal pronounced spatiotemporal heterogeneity: factors such as shopping centers, financial facilities, and bus stops exert stronger effects in central urban areas but show diminishing influence in suburban areas. Temporally, shopping centers contribute more to weekend ridership, while enterprises and residential areas play a greater role during workday commuting peaks. By incorporating these variations, the CNN-BiLSTM-Attention model achieves superior predictive accuracy, with an adjusted R² of 0.91 and much lower than the baseline error. These findings offer practical insights for urban transportation planning and support data-driven decisions for optimizing taxi dispatch and infrastructure design.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104577"},"PeriodicalIF":6.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146153105","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":"Optimized parking lot locations for shared autonomous vehicles: A perspective from minimum route distance","authors":"Sunyu Wang ,&nbsp;Xiangjie Zhao ,&nbsp;Yineng Wang","doi":"10.1016/j.jtrangeo.2026.104576","DOIUrl":"10.1016/j.jtrangeo.2026.104576","url":null,"abstract":"<div><div>Shared autonomous vehicles (SAVs) are revolutionizing urban mobility systems, necessitating significant updates to transportation infrastructure, particularly parking facilities, due to their unique driverless nature and shared operational mode. For SAVs, parking lots not only function as depots for idle vehicles but also serve as origins and destinations of services, thereby impacting their service levels and fleet operational efficiency. Along with the emission reduction initiatives, the strategic planning of parking lot locations for SAVs is a critical issue. In this paper, we propose a two-step optimization framework to locate SAV parking lots. The first step employs a vehicle–trip assignment strategy to explore SAV operations, addressing the high computational costs of simulation methods and the limited problem size of traditional operations research approaches. The second step extends the classical capacitated p-median problem (CPMP) model to a capacitated flow termini median model (CFTMM) for location selection, incorporating dual-node demand to better depict reality. Using Chengdu as a case study, we demonstrate the effectiveness of our framework and gain some actionable insights for urban policymakers and transport network companies. It shows that the CFTMM demonstrates superior performance compared to the two benchmarks by effectively minimizing the empty driving costs to and from parking lots. Moreover, 6500 SAVs can meet all travel demand, with over 75% of SAVs operating during the day and gradually finishing their work after 8 PM. The optimized parking lot location distribution highlights the importance of retaining some parking spaces in the city center and balancing the parking demand of urban and suburban areas. The extended capacitated flow termini median model with dynamics (CFTMM-D) yields comparable results, further confirming the effectiveness and efficiency of CFTMM.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104576"},"PeriodicalIF":6.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146153102","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":"The benefits of digital travel information for informal transport: Insights from app users in Cochabamba, Bolivia","authors":"Aljoscha Minnich ,&nbsp;Juliane Koch ,&nbsp;Marc Hasselwander","doi":"10.1016/j.jtrangeo.2026.104574","DOIUrl":"10.1016/j.jtrangeo.2026.104574","url":null,"abstract":"<div><div>This study provides an in-depth analysis of the impact of a multimodal journey-planning app on users of informal public transport systems in Cochabamba, Bolivia. We analyze survey data (N=648) collected through the Trufi Association NGO’s digital travel app on changes in mobility behavior, satisfaction, and everyday life improvements. Participants report more frequent use of informal transport (49.7%) and an improvement in their everyday lives (75.9%) since using the digital travel information app. A high level of satisfaction with the Trufi Association app is found in the entire sample (85.5%). Using ordinal logistic regressions and non-parametric mean tests, it is mainly young people and women who benefit most from the availability of digital information. We observe that the main motivation for using informal transport in Cochabamba is its low cost, access to locations, and the lack of alternatives. Overall, this study highlights the importance of developing journey-planning apps for informal transport systems in the Global South, offering insights into subsequent satisfaction and improvements in daily life.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104574"},"PeriodicalIF":6.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146135018","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":"2026-02-01","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":"From structure to function: A comprehensive benchmark on the estimation of hubs in air transportation through complex network metrics","authors":"Xiaoqian Sun ,&nbsp;Sebastian Wandelt ,&nbsp;Morton O’Kelly","doi":"10.1016/j.jtrangeo.2025.104535","DOIUrl":"10.1016/j.jtrangeo.2025.104535","url":null,"abstract":"<div><div>Hubs play a critical role in air transportation systems by switching/sorting/collecting and providing a consolidation/breakbulk function. Previous research has extensively employed network centrality measures, including degree, betweenness, and closeness, as primary indicators for identifying hubs within air transportation networks. These metrics serve to quantify an airport’s significance based on its local/global connectivity and influence within the network. However, relying on topological indicators can be misleading due to the lack of empirical flow data, potentially resulting in an inaccurate assessment of an airport’s true importance within the network. In this study, we provide a comprehensive evaluation of how useful complex network metrics are in the task of identifying hubs. Integrating worldwide aircraft movement and passenger origin–destination data, our study offers a comprehensive benchmark for hub identification through structural complex network techniques. The benefits of this research include a more informed usage of the quality obtained from complex network indicators as proxy for indicating the extent of hubs as well as, downstream, an enhanced network planning and optimized resource allocation.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104535"},"PeriodicalIF":6.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146153106","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}