Pub Date : 2026-01-08DOI: 10.1016/j.jtrangeo.2025.104546
Zeyu Wang , Yingjie Liu , Don MacKenzie
This study explores the relationship between the built environment and travel behaviors, emphasizing eye-level visual features and subjective experiences often overlooked in traditional metrics. Using the Semantic-SAM image segmentation model and machine learning, Seattle’s built environment was categorized into three visually distinct clusters based on time series street view imagery collected from 2017 to 2021. Integrating these clusters with three corresponding waves of Puget Sound Travel Surveys revealed clear links between built environments, travel modes, vehicle use, and equity. The findings demonstrate how visually distinct environments shape travel behavior and household changes, emphasizing the possible effect of urban design and infrastructures provided. While Seattle has made strides in creating walkable, transit-accessible neighborhoods, challenges such as equity and automobile dependence remain. This study provides the possibility of complementing traditional built environment metrics with imagery data.
{"title":"Visual clustering of urban environments: Associations with household and travel characteristics","authors":"Zeyu Wang , Yingjie Liu , Don MacKenzie","doi":"10.1016/j.jtrangeo.2025.104546","DOIUrl":"10.1016/j.jtrangeo.2025.104546","url":null,"abstract":"<div><div>This study explores the relationship between the built environment and travel behaviors, emphasizing eye-level visual features and subjective experiences often overlooked in traditional metrics. Using the Semantic-SAM image segmentation model and machine learning, Seattle’s built environment was categorized into three visually distinct clusters based on time series street view imagery collected from 2017 to 2021. Integrating these clusters with three corresponding waves of Puget Sound Travel Surveys revealed clear links between built environments, travel modes, vehicle use, and equity. The findings demonstrate how visually distinct environments shape travel behavior and household changes, emphasizing the possible effect of urban design and infrastructures provided. While Seattle has made strides in creating walkable, transit-accessible neighborhoods, challenges such as equity and automobile dependence remain. This study provides the possibility of complementing traditional built environment metrics with imagery data.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104546"},"PeriodicalIF":6.3,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925971","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}
Pub Date : 2026-01-08DOI: 10.1016/j.jtrangeo.2025.104525
Zhao Wang , Chunlei Xin , Robin Workman , Hang Hu , Xinyuan Yu , Yuxin Tian , Robin Lovelace , Jiupeng Zhang , Haibo Chen
Over 53 % of African road network is unpaved, yet systematic monitoring remains limited. This study introduces a cost-effective machine learning (ML) solution to help local authorities monitor and plan road maintenance. Building on earlier work using high-resolution satellite imagery in Tanzania, the analysis extends to Madagascar, incorporating medium- and low-resolution imagery to reduce costs. Two distinct methodologies were evaluated: traditional ML and multimodal ML. The multimodal ML model achieves 93.2 % accuracy with high-resolution imagery and maintains satisfactory performance with medium (84.0 %) and low-resolution (85.3 %) imagery, aided by transfer learning. The framework demonstrates robust cross-resolution performance across Tanzania and Madagascar contexts. Additionally, a pilot study explored a fine-tuned Large Language-and-Vision Assistant (LLaVA) model, which demonstrated potential for natural language-based condition reporting and maintenance recommendations, offering an interpretable alternative to quantitative classification outputs. Whilst LLaVA currently exhibits lower classification accuracy than the multimodal ML model, multi-turn conversational approaches show promise for enhancing performance whilst maintaining natural language interpretability. This study contributes to Sustainable Development Goal 9.1 by delivering a scalable, affordable strategy to support resilient infrastructure and economic development in low-income regions.
{"title":"Advancing unpaved road assessment in Africa: Leveraging multimodal machine learning and large language-and-vision assistants across satellite imagery resolutions","authors":"Zhao Wang , Chunlei Xin , Robin Workman , Hang Hu , Xinyuan Yu , Yuxin Tian , Robin Lovelace , Jiupeng Zhang , Haibo Chen","doi":"10.1016/j.jtrangeo.2025.104525","DOIUrl":"10.1016/j.jtrangeo.2025.104525","url":null,"abstract":"<div><div>Over 53 % of African road network is unpaved, yet systematic monitoring remains limited. This study introduces a cost-effective machine learning (ML) solution to help local authorities monitor and plan road maintenance. Building on earlier work using high-resolution satellite imagery in Tanzania, the analysis extends to Madagascar, incorporating medium- and low-resolution imagery to reduce costs. Two distinct methodologies were evaluated: traditional ML and multimodal ML. The multimodal ML model achieves 93.2 % accuracy with high-resolution imagery and maintains satisfactory performance with medium (84.0 %) and low-resolution (85.3 %) imagery, aided by transfer learning. The framework demonstrates robust cross-resolution performance across Tanzania and Madagascar contexts. Additionally, a pilot study explored a fine-tuned Large Language-and-Vision Assistant (LLaVA) model, which demonstrated potential for natural language-based condition reporting and maintenance recommendations, offering an interpretable alternative to quantitative classification outputs. Whilst LLaVA currently exhibits lower classification accuracy than the multimodal ML model, multi-turn conversational approaches show promise for enhancing performance whilst maintaining natural language interpretability. This study contributes to Sustainable Development Goal 9.1 by delivering a scalable, affordable strategy to support resilient infrastructure and economic development in low-income regions.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104525"},"PeriodicalIF":6.3,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925974","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}
Pub Date : 2026-01-07DOI: 10.1016/j.jtrangeo.2025.104538
Stefan E. Mabit , David S. Bunch , Anders F. Jensen , Jeppe Rich
The demand for plug-in electric vehicles (PEVs) has increased in many countries, and many studies have focused on the influence of attributes and socio-economic variables. However, only a few studies have analysed the spatial heterogeneity in uptake within a country. In this study, we analyse demand variation across regions, using Denmark as a case example. The analysis applies mixed logit models and hybrid choice models to investigate the extent to which charging access, socio-economic variables, and attitudes can explain spatial differences in demand, using stated preference data from a large Danish consumer survey. Our results show that some socio-economic variables, especially education and gender, have an effect, however, the main factor appears to be attitudes linked to perception differences, which weakens the direct effect of education. When we account for these factors, the coefficients for regional dummy variables become much smaller and mostly insignificant. These results suggest that, given similar regional charging networks, it may be possible to achieve more uniform demand by removing perception barriers related to PEVs.
{"title":"Spatial differences in PEV demand: The case of Denmark","authors":"Stefan E. Mabit , David S. Bunch , Anders F. Jensen , Jeppe Rich","doi":"10.1016/j.jtrangeo.2025.104538","DOIUrl":"10.1016/j.jtrangeo.2025.104538","url":null,"abstract":"<div><div>The demand for plug-in electric vehicles (PEVs) has increased in many countries, and many studies have focused on the influence of attributes and socio-economic variables. However, only a few studies have analysed the spatial heterogeneity in uptake within a country. In this study, we analyse demand variation across regions, using Denmark as a case example. The analysis applies mixed logit models and hybrid choice models to investigate the extent to which charging access, socio-economic variables, and attitudes can explain spatial differences in demand, using stated preference data from a large Danish consumer survey. Our results show that some socio-economic variables, especially education and gender, have an effect, however, the main factor appears to be attitudes linked to perception differences, which weakens the direct effect of education. When we account for these factors, the coefficients for regional dummy variables become much smaller and mostly insignificant. These results suggest that, given similar regional charging networks, it may be possible to achieve more uniform demand by removing perception barriers related to PEVs.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104538"},"PeriodicalIF":6.3,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925972","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}
Pub Date : 2026-01-05DOI: 10.1016/j.jtrangeo.2025.104544
Hui-Ping Chen , Zhi-Chun Li , Bi Yu Chen
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.
{"title":"Probabilistic space-time prisms in road networks with travel time uncertainties","authors":"Hui-Ping Chen , Zhi-Chun Li , 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":"2026-01-05","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}
Pub Date : 2026-01-02DOI: 10.1016/j.jtrangeo.2025.104543
Haiying Jia , Zhenming Wu
The geopolitical conflict between Russia and Ukraine represents one of the most significant geopolitical disruptions in recent decades, profoundly affecting international petroleum trade flows and tanker fleet operation patterns. This study investigates the impact of this geopolitical event on maritime petroleum trade dynamics by analyzing tanker movement data obtained from the Automatic Identification System (AIS) from 2018 to 2023. Through a systematic evaluation, this study quantifies transformations in global maritime petroleum trade structures and tanker fleet productivity, measured by tonne-miles per deadweight. The findings indicate that, despite sanctions, Russian petroleum exports maintained volumetric resilience, there was a considerable market redistribution from European destinations to Asian, African, and South American markets. This restructuring led to notable shifts in fleet productivity, with significant differences across vessel classes and trade lanes. The findings provide critical implications for asset investment decisions, vessel operation strategies, and the development of energy trade networks.
{"title":"The impact of Russia-Ukraine war on international maritime petroleum trade and tanker fleet productivity","authors":"Haiying Jia , Zhenming Wu","doi":"10.1016/j.jtrangeo.2025.104543","DOIUrl":"10.1016/j.jtrangeo.2025.104543","url":null,"abstract":"<div><div>The geopolitical conflict between Russia and Ukraine represents one of the most significant geopolitical disruptions in recent decades, profoundly affecting international petroleum trade flows and tanker fleet operation patterns. This study investigates the impact of this geopolitical event on maritime petroleum trade dynamics by analyzing tanker movement data obtained from the Automatic Identification System (AIS) from 2018 to 2023. Through a systematic evaluation, this study quantifies transformations in global maritime petroleum trade structures and tanker fleet productivity, measured by tonne-miles per deadweight. The findings indicate that, despite sanctions, Russian petroleum exports maintained volumetric resilience, there was a considerable market redistribution from European destinations to Asian, African, and South American markets. This restructuring led to notable shifts in fleet productivity, with significant differences across vessel classes and trade lanes. The findings provide critical implications for asset investment decisions, vessel operation strategies, and the development of energy trade networks.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104543"},"PeriodicalIF":6.3,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884724","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}
Pub Date : 2025-12-31DOI: 10.1016/j.jtrangeo.2025.104545
Yu Huang , Shanqi Zhang , Yang Ju , Kangxu Wang
Rapid transit and transit-oriented development (TOD) have been global strategies for sustainable urban development. However, growing concerns have emerged regarding transit-induced gentrification (TIG) and its impact on residents' changing perceptions of neighborhoods. The interrelationships between TOD and perceived gentrification, as well as their effects on neighborhood satisfaction and sense of community, remain understudied. This study aims to bridge this gap by analyzing surveys from residents living near three metro stations along the new Metro Line 5 in Nanjing, China. Utilizing confirmatory factor analysis (CFA) and structural equation modeling (SEM), we find that: (1) TOD residents were not statistically associated with higher levels of perceived gentrification; (2) the presence of metro was not significantly linked to sense of community, but neighborhood satisfaction regarding transit access and neighborhood amenities; (3) residents with higher levels of perceived gentrification also reported greater neighborhood satisfaction and a stronger sense of community; and (4) renters exhibited lower levels of perceived gentrification and sense of community. This study advances the understanding of transit-induced gentrification by providing empirical evidence from China, offering recommendations for TOD policies that promote inclusive and sustainable community development.
{"title":"Interrelationships between TOD, perceived gentrification, neighborhood satisfaction and sense of community: A case study in Nanjing, China","authors":"Yu Huang , Shanqi Zhang , Yang Ju , Kangxu Wang","doi":"10.1016/j.jtrangeo.2025.104545","DOIUrl":"10.1016/j.jtrangeo.2025.104545","url":null,"abstract":"<div><div>Rapid transit and transit-oriented development (TOD) have been global strategies for sustainable urban development. However, growing concerns have emerged regarding transit-induced gentrification (TIG) and its impact on residents' changing perceptions of neighborhoods. The interrelationships between TOD and perceived gentrification, as well as their effects on <em>neighborhood</em> satisfaction and sense of <em>community</em>, remain understudied. This study aims to bridge this gap by analyzing surveys from residents living near three metro stations along the new Metro Line 5 in Nanjing, China. Utilizing confirmatory factor analysis (CFA) and structural equation modeling (SEM), we find that: (1) TOD residents were not statistically associated with higher levels of perceived gentrification; (2) the presence of metro was not significantly linked to sense of community, but neighborhood satisfaction regarding transit access and neighborhood amenities; (3) residents with higher levels of perceived gentrification also reported greater neighborhood satisfaction and a stronger sense of community; and (4) renters exhibited lower levels of perceived gentrification and sense of community. This study advances the understanding of transit-induced gentrification by providing empirical evidence from China, offering recommendations for TOD policies that promote inclusive and sustainable community development.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104545"},"PeriodicalIF":6.3,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884725","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}
Car dependence is an increasing concern in the current urban and territorial challenges, generating significant environmental and social impacts. As a complex, multidimensional, and processual phenomenon, it requires analysis through interrelated, place-based indicators that reveal the driving forces behind its various dimensions. While existing literature offers a solid framework of predominantly quantitative approaches, it also highlights the need for interpretative methods that consider socio-spatial contexts, the system of preferences, and opportunities. To deal with the processual and multi-dimensional nature of car dependence, this paper explores the drivers and outcomes of car dependence across diverse socio-spatial settings in the Lombardy region (Italy) through two key concepts: car dependence level, which measures the alignment between driver and outcome variables (e.g., low density with high car use); and car dependence dissonance, which captures deviations from expected literature patterns. Using bivariate classification and spatial analysis of its maps, the study identifies the regional and multidimensional nature of car dependence, followed by a cluster analysis that categorises different territorial dynamics. The findings show that while major urban centres tend to display consistent low car dependence, scattered or peripheral zones present greater heterogeneity, challenging common assumptions and suggesting the need for nuanced, context-sensitive mobility strategies.
{"title":"Dependent in their own way: Spatial analysis of car dependence patterns in Lombardy region using bivariate classification","authors":"Jaime Sierra Muñoz , Paola Pucci , Louison Duboz , Biagio Ciuffo","doi":"10.1016/j.jtrangeo.2025.104534","DOIUrl":"10.1016/j.jtrangeo.2025.104534","url":null,"abstract":"<div><div>Car dependence is an increasing concern in the current urban and territorial challenges, generating significant environmental and social impacts. As a complex, multidimensional, and processual phenomenon, it requires analysis through interrelated, place-based indicators that reveal the driving forces behind its various dimensions. While existing literature offers a solid framework of predominantly quantitative approaches, it also highlights the need for interpretative methods that consider socio-spatial contexts, the system of preferences, and opportunities. To deal with the processual and multi-dimensional nature of car dependence, this paper explores the drivers and outcomes of car dependence across diverse socio-spatial settings in the Lombardy region (Italy) through two key concepts: car dependence level, which measures the alignment between driver and outcome variables (e.g., low density with high car use); and car dependence dissonance, which captures deviations from expected literature patterns. Using bivariate classification and spatial analysis of its maps, the study identifies the regional and multidimensional nature of car dependence, followed by a cluster analysis that categorises different territorial dynamics. The findings show that while major urban centres tend to display consistent low car dependence, scattered or peripheral zones present greater heterogeneity, challenging common assumptions and suggesting the need for nuanced, context-sensitive mobility strategies.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104534"},"PeriodicalIF":6.3,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884723","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}
Pub Date : 2025-12-26DOI: 10.1016/j.jtrangeo.2025.104506
Yeray Cara-Santana, Borja Moya-Gómez, Juan Carlos García-Palomares
Gender differences in mobility are common in cities but analyzing them using data from travel surveys is limited by the sample size and the lack of detailed spatial and temporal patterns for different population groups. Big data sources, such as mobile phone data, offer almost ubiquitous data of daily mobility patterns and their changes while including basic socio-demographic characteristics. This paper studies differences in urban mobility from a gender and age perspective following the COVID-19 pandemic, comparing daily patterns of February 2020 and 2023 for the metropolitan region of Madrid. Urban activity, changes in mobility, and the gender gap are analyzed using different temporal and spatial aggregations based on Transport Analysis Zones (TAZ) and travel flows. The results reflect that the gender gap in trips decreases while remaining for the distance travelled for all age groups after COVID-19. Temporal patterns changed with more trips in the daytime and fewer at night, while the distance travelled evolves towards shorter journeys. Although women still make fewer trips and shorter distances, young women have reversed the gender gap between 2020 and 2023. This paper highlights how gender and age are longitudinal and transversal factors shaping mobility over an individual's life course and how COVID-19 seems to have accelerated pre-existing changing trends in urban mobility. Understanding the nature and relevance of the social dynamics and the differences between each population group is essential for supporting the study of urban segregation and helping authorities manage mobility in the territory.
{"title":"Using mobile phone data to explore gender and age gaps in urban mobility. Revealing the changes after COVID-19 in the metropolitan region of Madrid (Spain)","authors":"Yeray Cara-Santana, Borja Moya-Gómez, Juan Carlos García-Palomares","doi":"10.1016/j.jtrangeo.2025.104506","DOIUrl":"10.1016/j.jtrangeo.2025.104506","url":null,"abstract":"<div><div>Gender differences in mobility are common in cities but analyzing them using data from travel surveys is limited by the sample size and the lack of detailed spatial and temporal patterns for different population groups. Big data sources, such as mobile phone data, offer almost ubiquitous data of daily mobility patterns and their changes while including basic socio-demographic characteristics. This paper studies differences in urban mobility from a gender and age perspective following the COVID-19 pandemic, comparing daily patterns of February 2020 and 2023 for the metropolitan region of Madrid. Urban activity, changes in mobility, and the gender gap are analyzed using different temporal and spatial aggregations based on Transport Analysis Zones (TAZ) and travel flows. The results reflect that the gender gap in trips decreases while remaining for the distance travelled for all age groups after COVID-19. Temporal patterns changed with more trips in the daytime and fewer at night, while the distance travelled evolves towards shorter journeys. Although women still make fewer trips and shorter distances, young women have reversed the gender gap between 2020 and 2023. This paper highlights how gender and age are longitudinal and transversal factors shaping mobility over an individual's life course and how COVID-19 seems to have accelerated pre-existing changing trends in urban mobility. Understanding the nature and relevance of the social dynamics and the differences between each population group is essential for supporting the study of urban segregation and helping authorities manage mobility in the territory.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104506"},"PeriodicalIF":6.3,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841306","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}
Pub Date : 2025-12-26DOI: 10.1016/j.jtrangeo.2025.104537
Yin Dou , Xinyi Wang , Rolf Moeckel
The relationship between urban rail transit networks (URTN) and urban spatial structure (USS) is foundational to transport geography and urban planning. However, this relationship is often viewed through a static lens that overlooks the complex, long-term process of their interaction. This study challenges the conventional paradigm of transit ‘guiding’ development by proposing and empirically demonstrating a model of ‘asynchronous co-evolution,’ where infrastructure and urban form mutually shape each other across time and space, often with significant lags. We investigate this process through a 45-year analysis (1975–2020) of the Munich Metropolitan Area (MMA), a mature transit metropolis. Using complex network analysis for station centrality and socioeconomic data for population and building volume, we assess the spatiotemporal dynamics of their coupling. Our findings reveal a long-term trajectory from corridor-led suburbanization to networked urban renaissance, a process characterized by persistent discoordination. Crucially, we identify a stark divergence in development logic between the urban core (within 10 km) and the periphery (beyond 10 km); the latter exhibits characteristics of Transit-Adjacent Development (TAD) driven by car dependency, rather than genuine Transit-Oriented Development (TOD). By framing the URTN-USS relationship as a dynamic and spatially contingent process, this research offers a more nuanced understanding of TOD and provides critical insights for adaptive planning in evolving metropolitan regions.
{"title":"An asynchronous co-evolution: The spatiotemporal dynamics of rail transit and urban structure in the Munich Metropolitan Area (1975–2020)","authors":"Yin Dou , Xinyi Wang , Rolf Moeckel","doi":"10.1016/j.jtrangeo.2025.104537","DOIUrl":"10.1016/j.jtrangeo.2025.104537","url":null,"abstract":"<div><div>The relationship between urban rail transit networks (URTN) and urban spatial structure (USS) is foundational to transport geography and urban planning. However, this relationship is often viewed through a static lens that overlooks the complex, long-term process of their interaction. This study challenges the conventional paradigm of transit ‘guiding’ development by proposing and empirically demonstrating a model of ‘asynchronous co-evolution,’ where infrastructure and urban form mutually shape each other across time and space, often with significant lags. We investigate this process through a 45-year analysis (1975–2020) of the Munich Metropolitan Area (MMA), a mature transit metropolis. Using complex network analysis for station centrality and socioeconomic data for population and building volume, we assess the spatiotemporal dynamics of their coupling. Our findings reveal a long-term trajectory from corridor-led suburbanization to networked urban renaissance, a process characterized by persistent discoordination. Crucially, we identify a stark divergence in development logic between the urban core (within 10 km) and the periphery (beyond 10 km); the latter exhibits characteristics of Transit-Adjacent Development (TAD) driven by car dependency, rather than genuine Transit-Oriented Development (TOD). By framing the URTN-USS relationship as a dynamic and spatially contingent process, this research offers a more nuanced understanding of TOD and provides critical insights for adaptive planning in evolving metropolitan regions.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104537"},"PeriodicalIF":6.3,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145841308","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}
Pub Date : 2025-12-26DOI: 10.1016/j.jtrangeo.2025.104528
Francesco De Fabiis, Marco Baldini, Pierluigi Coppola
Bikeability, defined as the perceived quality of a bike trip, is gaining increasing attention due to the growing focus on active mobility in sustainable urban mobility plans. The higher the bikeability, the more attractive cycling becomes for short- to medium-distance urban travels. However, this relationship may depend on user profiles, trip characteristics, and the geographical context. This study explores these factors from a gender perspective (men and women) with a focus on context: large, medium and small cities; urban, extra-urban, or dedicated bike paths. To this aim, revealed preference data from the Lombardy Region (sample size: 745, observations: 1017) were analysed using Hybrid Choice Models. The results indicate that bikeability is influenced by four latent constructs, namely the perception of ‘Conflict with Other Vehicles’, ‘Quality of Urban Space’, ‘Quality of Bike Path’, and ‘Physical and Mental Fatigue’, alongside variables such as ‘Presence of Other Cyclists’ and ‘Ambient Temperature’. Gender differences emerge in evaluating these constructs. For instance, women cycling in highly populated cities perceive a higher level of conflict with other vehicles compared to both men and women cycling in less populated areas. The findings provide insights for tailored policies that take gender differences and geographical contexts into account to enhance overall bikeability levels.
{"title":"The impact of geographical context on Bikeability perception: A gender-difference analysis","authors":"Francesco De Fabiis, Marco Baldini, Pierluigi Coppola","doi":"10.1016/j.jtrangeo.2025.104528","DOIUrl":"10.1016/j.jtrangeo.2025.104528","url":null,"abstract":"<div><div>Bikeability, defined as the perceived quality of a bike trip, is gaining increasing attention due to the growing focus on active mobility in sustainable urban mobility plans. The higher the bikeability, the more attractive cycling becomes for short- to medium-distance urban travels. However, this relationship may depend on user profiles, trip characteristics, and the geographical context. This study explores these factors from a gender perspective (men and women) with a focus on context: large, medium and small cities; urban, extra-urban, or dedicated bike paths. To this aim, revealed preference data from the Lombardy Region (sample size: 745, observations: 1017) were analysed using Hybrid Choice Models. The results indicate that bikeability is influenced by four latent constructs, namely the perception of ‘Conflict with Other Vehicles’, ‘Quality of Urban Space’, ‘Quality of Bike Path’, and ‘Physical and Mental Fatigue’, alongside variables such as ‘Presence of Other Cyclists’ and ‘Ambient Temperature’. Gender differences emerge in evaluating these constructs. For instance, women cycling in highly populated cities perceive a higher level of conflict with other vehicles compared to both men and women cycling in less populated areas. The findings provide insights for tailored policies that take gender differences and geographical contexts into account to enhance overall bikeability levels.</div></div>","PeriodicalId":48413,"journal":{"name":"Journal of Transport Geography","volume":"131 ","pages":"Article 104528"},"PeriodicalIF":6.3,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840686","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}
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