Journal of Transport Geography最新文献

Food accessibility has been a subject of growing interest due to its impact on public health outcomes. This paper describes a spatial analysis method to identify gaps in geographic food access and correlate them with a variety of demographic and socioeconomic factors. The proposed food accessibility metric is the square footage of supermarkets that can be reached within 10 min travel time by walking, biking, driving, and 30 min travel time by walk/transit. The spatial analysis is conducted for the centroids of each census tract within a study area, and the approach is illustrated with an application for the state of Massachusetts. Correlations between demographic and socioeconomic explanatory variables and food accessibility are explored using the Gradient Boosted machine learning model. More specifically, the explanatory variables are percent minority population, percent of population in poverty, vehicle ownership, and population density. The spatial analysis shows a strong correlation between food accessibility and population density. The machine learning model is then used to identify gaps in food accessibility for each transportation mode while controlling for community characteristics. The residuals of the model reveal which communities have the lowest food accessibility relative to other similar communities within the state. This research provides a quantitative method to identify communities that have reduced access to food relative to state-wide trends. Lastly, it provides insights for where policy interventions would be valuable for improving food access in addition to recommendations on increasing food accessibility.

As the sharing economy expands in China, the emergence of ride-hailing services has diminished the market share of the taxi industry. As a regulated and publicly convenient service with a dedicated customer base, traditional taxi industry needs to improve its own competitiveness and maintain its market share. However, the specific circumstances under which taxis can gain a competitive edge over ride-hailing services are not well-understood. Aiming to uncover the competitive potential of taxis in the ride-source market, this study proposes a methodology to explore the Competition and Cooperation Relationship (CCR) between taxis and ride-hailing services on a multidimensional spatio-temporal scale. By taking Beijing, China as a case study, we first compare different impacts of Points of Interest (POI) on the traffic volume of taxis/ride-hailing services through Geographically and Temporally Weighted Regression (GTWR) models, and explore the corresponding times and locations where taxis/ride-hailing services are more likely to attract passengers. Based on the findings that there are strong correlations between traffic volume and spatio-temporal conditions, we establish the Competition-Cooperation Index (CCI) as a quantitative measure to characterize the CCR and then analyze the spatio-temporal distribution of CCI to identify the times and locations where taxis hold advantages in cooperative or competitive relationship relative to ride-hailing services. Furthermore, we investigate the underlying reasons for these patterns, discovering that CCI has a close connection with land use. The results of our analysis show that taxis exhibit competitive advantages over ride-hailing services under some specific circumstances and can further enhance their competitiveness by proposed targeted measures. The findings of this study provide valuable insights for both industries in formulating growth strategies and for governmental agencies in setting policies.

The increase in the share of motorization in short-distance trips is a significant contributor to the decline in the share of active travel (AT) and will further pose a challenge to sustainable transport. While many studies have explored the relationship between the built environment (BE) and AT, few have focused on short trips. Additionally, most studies have ignored the important role of the streetscape. To address these gaps, this study utilizes street view big data to quantify street view elements and applies extreme gradient boosting decision trees (XGBoost) to 2020 household travel data in Wuhan. The results indicate that streetscape attributes are more important than land use in predicting short-distance AT, with streetscape being more than 40% relative importance in both models. The contribution of almost all streetscape elements cannot be ignored. Among them, the percentage of driveways showed the highest predictive power. Among land use attributes, population density has the highest relative importance. In addition, most of the independent variables are nonlinearly correlated with the explanatory variables, and this study quantified these association thresholds. These results suggest that optimizing the street built environment has the potential to promote a shift from short-distance driving to AT. The quantification of correlation thresholds provides precise empirical evidence for built environment interventions that promote short-distance AT.

From a global perspective, climate change mitigation requires countries to consider Low-Carbon Development (LCD) policies, including “Low-Carbon Transport (LCT)” and decarbonization options, which should be ideally developed within a place-based scope. Due to the complex structure of the transportation sector, mitigation actions require not only technological but also behavioral shifts, which can be challenged by the existing legislative and socio-economic structure of a region. Therefore, it is essential to identify and assess barriers and opportunities (B&Os) as a necessary initial phase in the development of national mitigation strategies. Turkey voluntarily started climate change mitigation by preparing the legislative and political infrastructure as a part of the European Union Harmonization Process. Detection of B&Os in other dimensions required an in-depth evaluation of existing LCT barriers and instruments (B&Is) in the IPCC literature in terms of their applicability and priority for Turkey. A focus group study with transport sector representatives was conducted to evaluate 15 barriers and 19 instruments (proposing 285 B&I matrix combinations), followed by a brain-writing exercise that revealed 12 main barriers (i.e., a lack of measurable targets, an imbalanced modal split, a lack of institutional coordination and data archiving, etc.). Various opportunities have been identified, such as the increased utilization of Intelligent Transportation Systems and the timely adoption of vehicle and fuel technologies in the EU region. These opportunities would not only contribute to the development of a national climate change mitigation strategy but also facilitate the implementation of place-based action plans, including climate change action plans and sustainable urban mobility plans at the city level.

Although much of the existing research on regional airports focuses on their contribution to regional economic development, regional airports in England, as in other deregulated markets, operate in a highly competitive market and not all have been able to sustain commercial flights. This paper examines the factors that have led to the cessation of commercial air services at English regional airports following liberalisation of the European air transport market in 1992. Six factors which have contributed to air service cessation are identified and potential futures for smaller regional airports discussed.

Evacuation after hurricane impacts appear (post-impact evacuation) has been underemphasized in empirical evacuation studies. This study uses well-examined factors for pre-impact evacuation and novel factors for post-impact evacuation in a sequential logit model for pre- and post-impact evacuation choices. Results show that the evacuation warning is the only factor that affected both pre-impact and post-impact evacuations. Demographics and housing characteristics are significant factors for pre-impact evacuation but not for post-impact evacuation, while residential damages and durations of utility outages are significant situational factors for post-impact evacuation. The durations of water and power outages had additive effects on the probability of evacuating after hurricane impact. Based on the results, we argue that the conventional assumption that sheltered-in-place residents will remain in the affected area, and the restoration planning and assistance generated with that premise will not be aligned with the demand of residents facing inhabitable living situations with damaged residences and prolonged utility outages. Agencies should consider extending the evacuation planning time horizon for storm events likely to induce severe damages and outages and prepare for evacuation during disrupted conditions.

Due to its flexibility, pro-environmental characteristics, and its contribution to solving the first or last kilometer’ problem, sharing bike has become a popular travel option for many residents, especially for short trips. This study analyses the impact of extreme temperatures on residents' shared travel and the bike-sharing industry by combining the full-sample travel data, meteorological data, and POI data in Hohhot, China. Based on the temporal and spatial characteristics of residents' travel, five patterns are distinguished by K-means clustering: basic trips, short-distance trips, round trips, time tolerance trips and distance tolerance trips. The main conclusions of the research are as follows: i) extremely low temperatures can increase the possibility of short-distance trips and round trips but reduce long-duration or long-distance travel. Extremely high temperature has a positive effect on residents' round trips and time tolerance trips but suppress short-distance trips and distance tolerance trips; ii) for long-duration or long-distance shared travel, extremely low temperature enhance the connection between sharing bikes and other modes of transportation, but the extremely high temperature has the opposite impact; iii) extreme temperature causes less substitution of sharing bikes for other vehicles in round trips. However, residents in basic trip mode prefer to use sharing bikes instead of vehicles at extremely high temperatures; iv) the total annual economic loss of shared travel caused by extreme temperatures reached 31,393.82 CNY. In addition, many residents abandon sharing bikes in favor of cars at extreme temperatures, leading to additional carbon emissions of 2585.29 kg/year. The study also provides profound policy implications for the bike-sharing industry and green travel.

Severe weather events, such as snowfall, flooding and storms, may affect wide geographical areas and adversely impact discrete transport infrastructure networks (e.g. road, rail) at the same time, thus revealing the existence of geographic interdependencies between these networks. In this paper, we develop two accessibility-based measures to assess the impact of geographic interdependency on resilience based on the concepts of redundancy and substitutability, respectively. These measures are applied to the railway and long-distance bus networks in Scotland. Results reveal that the combined effect of redundancy and substitutability on the accessibility of locations offered by these discrete modes is reduced due to geographic interdependencies, with the extent of losses being positively associated with the spatial footprint of potential events. The results can be used to identify parts of the network where the potential impacts of geographic interdependencies are greatest, and thus require more in-depth scrutiny by network managers.

Although researchers and policymakers have proposed several ideas for improving the travel experiences of Persons with Disabilities (PWDs), they still face several barriers, especially in developing countries. This calls for a new sociological perspective aimed at contextualizing local disability policies and theories to create a disability-friendly society. This paper contextualizes the Ghana disability law through the lenses of Giddens' theory of structuration for the first time to understand the lived transportation barriers for PWDs. Questionnaire surveys involving 664 PWDs with physical, visual, auditory, and speaking impairments, key informant interviews, and field observations were triangulated. Results showed that all agents and structures, namely discrimination/facility managers' attitude, driver attitude, pedestrian behavior, design of facilities, and accessibility, are creating transportation barriers for PWDs in Ghana. Participants voiced exclusion from the design and implementation of transport facilities. Notably, discriminatory attitudes from commuters, drivers, and facility managers make PWDs feel marginalized. The lack of disability-friendly public buses/paratransit services and assistive technologies impedes PWDs' mobility to work, school, and health facilities. These findings show that although the Ghana disability law makes provisions for PWDs' mobility needs, there is weak enforcement. Thus, beyond improving infrastructure and access for PWDs, societal reorientation and enhanced enforcement of the laws are needed to foster empathy towards PWDs. The reorientation-based approach requires enhanced public sensitization, law enforcement, and regular consultation of PWDs in transport planning to improve the social order.

The COVID-19 pandemic has had an unprecedented impact on mobility patterns resulting in a significant literature investigating travel behaviours over the course of the pandemic. Missing from much existing work on pandemic mobility is an explicit handling of the time-of-day of travel, which in previous literature has been shown to be an important factor in understanding mobility and, importantly, in understanding the impact on transport networks. In this article, we present a novel analysis of anonymised individual daily mobility patterns in the UK over a 30-month period covering the COVID-19 pandemic using privacy-preserving mobile phone GPS data, collected via integration of software development kits (SDKs) into mobile apps. Our analysis is based on time series clustering of mobility profiles at an hourly level of resolution and enables us to characterize five distinct daily mobility patterns. This typology appears remarkably robust over time, albeit with varying levels of each pattern during the course of the study period. We analyse the relative frequency of these patterns in relation to two dimensions of neighbourhood deprivation in England, with a particular focus on understanding mobility post-lockdown and for over a year after the final restrictions were lifted in the UK. Our results show that although overall mobility patterns have largely returned to their pre-pandemic levels, there remain persistent inequalities in relation to ‘traditional commute’, ‘highly mobile’ and ‘out in the evening’ activity patterns. This finding is expected to have important ongoing policy implications.