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Zones are the building blocks of urban analysis. Fields ranging from demographics to transport planning routinely use zones - spatially contiguous areal units that break-up continuous space into discrete chunks - as the foundation for diverse analysis techniques. Key methods such as origin-destination analysis and choropleth mapping rely on zones with appropriate sizes, shapes and coverage. However, existing zoning systems are sub-optimal in many urban analysis contexts, for three main reasons: 1) administrative zoning systems are often based on somewhat arbitrary factors; 2) zoning systems that are evidence-based (e.g., based on equal population size) are often highly variable in size and shape, reducing their utility for inter-city comparison; and 3) official zoning systems in many places simply do not exist or are unavailable. We set out to develop a flexible, open and scalable solution to these problems. The result is the zonebuilder project (with R, Rust and Python implementations), which was used to create the ClockBoard zoning system. ClockBoard consists of 12 segments emanating from a central place and divided by concentric rings with radii that increase in line with the triangular number sequence (1, 3, 6 km etc). 'ClockBoards' thus create a consistent visual frame of reference for monocentric cities that is reminiscent of clocks and a dartboard. This paper outlines the design and potential uses of the ClockBoard zoning system in the historical context, and discusses future avenues for research into the design and assessment of zoning systems.

Geographic analysis has long supported transport plans that are appropriate to local contexts. Many incumbent ‘tools of the trade’ are proprietary and were developed to support growth in motor traffic, limiting their utility for transport planners who have been tasked with twenty-first century objectives such as enabling citizen participation, reducing pollution, and increasing levels of physical activity by getting more people walking and cycling. Geographic techniques—such as route analysis, network editing, localised impact assessment and interactive map visualisation—have great potential to support modern transport planning priorities. The aim of this paper is to explore emerging open source tools for geographic analysis in transport planning, with reference to the literature and a review of open source tools that are already being used. A key finding is that a growing number of options exist, challenging the current landscape of proprietary tools. These can be classified as command-line interface, graphical user interface or web-based user interface tools and by the framework in which they were implemented, with numerous tools released as R, Python and JavaScript packages, and QGIS plugins. The review found a diverse and rapidly evolving ‘ecosystem’ tools, with 25 tools that were designed for geographic analysis to support transport planning outlined in terms of their popularity and functionality based on online documentation. They ranged in size from single-purpose tools such as the QGIS plugin AwaP to sophisticated stand-alone multi-modal traffic simulation software such as MATSim, SUMO and Veins. Building on their ability to re-use the most effective components from other open source projects, developers of open source transport planning tools can avoid ‘reinventing the wheel’ and focus on innovation, the ‘gamified’ A/B Street https://github.com/dabreegster/abstreet/#abstreet simulation software, based on OpenStreetMap, a case in point. The paper, the source code of which can be found at https://github.com/robinlovelace/open-gat, concludes that, although many of the tools reviewed are still evolving and further research is needed to understand their relative strengths and barriers to uptake, open source tools for geographic analysis in transport planning already hold great potential to help generate the strategic visions of change and evidence that is needed by transport planners in the twenty-first century.

The development and delivery of ICT-based persuasive strategies for the adoption of more environmental-friendly modes of transport is an emerging strategy to help tackle the problem of excessive us...

A large and growing body of evidence suggests fundamental changes are needed in transport systems, to tackle issues such as air pollution, physical inactivity and climate change. Transport models can play a major role in tackling these issues through the transport planning process, but they have historically been focussed on motorised modes (especially cars) and available only to professional transport planners working within the existing paradigm. Building on the principles of open access software, first developed in the context of geographic information systems, this paper develops and discusses the concept of open access transport models, which we define as models that are both developed using open source software and are available to be used by the public without the need for specialist training or the purchase of software licences. We explore the future potential of open access transport models to support the transition away from fossil fuels in the transport sector. We do this with reference to the literature on the use of tools in the planning process, and by exploring an example that is already in use: the ‘Propensity to Cycle Tool’. We conclude that open access transport models can be a leverage point in the planning process due to their ability to provide robust, transparent and actionable evidence that is available to a range of stakeholders, not just professional transport planners. Open access transport models represent a disruptive technology deserving further research and development, by planners, researchers and citizen scientists, including open source software developers and advocacy groups but, in order to fulfil their potential, they will require both financial and policy support from government bodies.

Bikeability, the extent to which a route network enables cycling for everyday travel, is a frequently cited theme for increasing and diversifying cycling uptake and therefore one that attracts much research attention. Indexes designed to quantify bikeability typically generate a single bikeability value for a single locality. Important to transport planners making and evaluating infrastructure decisions, however, is how well-connected by bike are pairs of localities. For this, it is necessary to estimate the bikeability of plausible routes connecting different parts of a city. We approximate routes for all origin-destination trips cycled in the London Cycle Hire Scheme for 2018 and estimate the bikeability of each route, linking to the newly released London Cycle Infrastructure Database. We then divide the area of inner London covered by the bikeshare scheme into ‘villages’ and profile how bikeability varies for trips connecting those villages – we call this connected bikeability. Our bikeability scores vary geographically with certain localities in London better connected by bike than others. A key finding is that higher levels of connected bikeability are conferred to origin-destination village pairs of strategic importance, aligning with the stated ambition of recent cycling infrastructure interventions. The geography of connected bikeability maps to the commuting needs of London’s workers and we find some evidence that connected bikeability has a positive association with observed cycling activity, especially so when studying patterns of cycling to job-rich villages.

A lack of cycle parking is a known barrier to promoting the uptake of cycling in urban areas. Unlike cars that can be parked on the roadside with little additional infrastructure, bikes usually require dedicated parking facilities. The existing research and guidance on where cycle parking should be provided primarily focuses on key destinations such as train stations or schools. Thus, there is a gap in knowledge about the amount of general-purpose cycle parking required and how it should be distributed across a city. This paper presents a novel method for analysing and prioritising the spatial distribution of cycle parking. The method draws on established portfolio management techniques but applies them in a spatial context. Using the case study of London, we demonstrate that it is possible to identify areas that have a deficit of cycle parking as well as locations that have the most significant potential for increasing cycling uptake by providing additional cycle parking.

Cycling can be particularly beneficial for socioeconomically disadvantaged populations. First, because it can allow them to access opportunities that by other modes they may not afford. Secondly, because it can increase their physical activity levels and, consequently, improve their health. We analyse the extent to which socioeconomic disadvantage impacts on cycling participation in England, for both leisure and utility cycling. Then, we explore the extent to which this impact could be explained by the environment in which disadvantaged populations live. The study population includes 167,178 individuals, residing in 2,931 areas, and 326 Local Authorities. Data on individual factors were drawn from the Active Lives Survey, and data on environmental factors from several sources. Descriptive statistics and multilevel logistic models were estimated. The likelihood of cycling is lower among people living in deprived areas than among people living in non-deprived areas. This difference is significant for leisure, but also for utility cycling when controlling for individual and environmental factors. The study also found that cycling infrastructure and greater levels of cyclability are higher in deprived areas than in non-deprived areas. This suggests that infrastructure and cyclability are not enough to increase cycling levels among disadvantaged populations. Further research on other barriers to cycling among disadvantaged populations is required.

The London Congestion Charge (LCC) is a transport policy with a precise spatial footprint. As such, its impact on the transport system can be expected to vary over space, providing an opportunity to explore the geographical reach of local transport interventions. This paper assesses whether the exemption of Hybrid Electric Vehicles (HEVs) from the LCC affected the registration rate of these vehicles in Greater London and the surrounding areas. The analysis uses official data on the number of HEVs registered across the local authorities of the United Kingdom. This dataset is assessed using [1] exploratory spatial analysis to determine the degree of spatial variation in HEV registrations, [2] area classifications to consider if HEV registrations diminish as nearness to the LCC recedes, and [3] spatial regression models to evaluate the association between distance to the LCC and HEV registrations, controlling for other area characteristics (i.e. socioeconomic, household, and transport system variables). The results clearly show that nearness to the LCC is positively associated with HEV registrations, implying that this form of transport policy is effective at promoting the adoption of low emission vehicles.

Large and unofficial data sets, for instance those gathered from social media, are increasingly being used in geographical research and explored as decision support tools for policy development. Social media data have the potential to provide new insight into phenomena about which there is little information from conventional sources. Within this context, this paper explores the potential of social media data to evaluate the aesthetic management of landscape. Specifically, this project utilises the perceptions of visitors to the Pennine Way National Trail, which passes through land managed under the Environmental Stewardship Scheme (ESS). The method analyses sentiment in trail users’ public Twitter messages (tweets) with the aim of assessing the extent to which the ESS maintains landscape character within the trail corridor. The method demonstrates the importance of filtering social media data to convert it into useful information. After filtering, the results are based on 161 messages directly related to the trail. Although small, this sample illustrates the potential for social media to be used as a cheap and increasingly abundant source of information. We suggest that social media data in this context should be seen as a resource that can complement, rather than replace, conventional data sources such as questionnaires and interviews. Furthermore, we provide guidance on how social media could be effectively used by conservation bodies, such as Natural England, which are charged with the management of areas of environmental value worldwide.

When extreme weather events occur, people often turn to social media platforms to share information, opinions and experiences. One of the topics commonly discussed is the role climate change may or may not have played in influencing an event. Here, we examine Twitter posts that mentioned climate change in the context of three high-magnitude extreme weather events – Hurricane Irene, Hurricane Sandy and Snowstorm Jonas – in order to assess how the framing of the topic and the attention paid to it can vary between events. We also examine the role that contextual factors can play in shaping climate change coverage on the platform. We find that criticism of climate change denial dominated during Irene, while political and ideological struggle frames dominated during Sandy. Discourse during Jonas was, in contrast, more divided between posts about the scientific links between climate change and the events, and posts contesting climate science in general. The focus on political and ideological struggle frames during Sandy reflects the event’s occurrence at a time when the Occupy movement was active and the 2012 US Presidential Election was nearing. These factors, we suggest, could also contribute to climate change being a more prominent discussion point during Sandy than during Irene or Jonas. The Jonas frames, meanwhile, hint at lesser public understanding of how climate change may influence cold weather events when compared with tropical storms. Overall, our findings demonstrate how event characteristics and short-term socio-political context can play a critical role in determining the lenses through which climate change is viewed.

In many large Latin American urban areas such as the Sao Paulo Metropolitan Region (SPMR), growing social and economic inequalities are embedded through high spatial inequality in the provision of state schools and affordable public transport to these schools. This paper sheds light on the transport-education inequality nexus with reference to school accessibility by public transport in the SPMR. To assess school accessibility, we develop an accessibility index which combines information on the spatial distribution of adolescents, the location of existing schools, and the public transport provision serving the school catchment area into a single measure. The index is used to measure school accessibility locally across 633 areas within the SPMR. We use the index to simulate the impact of a policy aiming at increasing the centralisation of public secondary education provision, and find that it negatively affects public transport accessibility for students with the lowest levels of accessibility. These results illustrate how existing inequalities can be amplified by variable accessibility to schools across income groups and geographical space. The research suggests that educational inequality impacts of school agglomeration policies should be considered before centralisation takes place.

There has been much excitement amongst quantitative geographers about newly available datasets, characterised by high volume, velocity and variety. This phenomenon is often labelled as 'Big Data' and has contributed to methodological and empirical advances, particularly in the areas of visualisation and analysis of social networks. However, a fourth v - veracity (or lack thereof) - has been conspicuously lacking from the literature. This paper sets out to test the potential for verifying large datasets. It does this by cross-comparing three unrelated estimates of retail flows --- human movements from home locations to shopping centres --- derived from the following geo-coded sources: 1) a major mobile telephone service provider; 2) a commercial consumer survey; and 3) geotagged Twitter messages. Three spatial interaction models also provided estimates of flow: constrained and unconstrained versions of the 'gravity model' and the recently developed 'radiation model'. We found positive relationships between all data-based and theoretical sources of estimated retail flows. Based on the analysis, the mobile telephone data fitted the modelled flows and consumer survey data closely, while flows obtained directly from the Twitter data diverged from other sources. The research highlights the importance of verification in flow data derived from new sources and demonstrates methods for achieving this.

Urban Travel is an imposing book. Its 600+ pages are written in academic prose, interspersed with detailed quotations, high-quality graphics and a smattering of mathematics, deliberately placed in each chapter’s meticulous endnotes to increase readability. The chapters are ordered roughly chronologically, covering the entire gamut of computational transport forecasting models from the early developments in the US and UK (Chapters 2 and 3) through discrete choice modelling approaches (Chapters 4 and 5), activity-based and network equilibrium approaches (Chapters 6 and 7), the practice of travel forecasting (Chapters 8 and 9) to computational aspects of the field (Chapter 10) and prospects for the future (Chapter 11). The introductory and concluding chapters astutely synthesise these substantial strands of thought into a single narrative.

Getting people cycling is an increasingly common objective in transport planning institutions worldwide. A growing evidence base indicates that high quality infrastructure can boost local cycling rates. Yet for infrastructure and other cycling measures to be effective, it is important to intervene in the right places, such as along 'desire lines' of high latent demand. This creates the need for tools and methods to help answer the question 'where to build?'. Following a brief review of the policy and research context related to this question, this paper describes the design, features and potential applications of such a tool. The Propensity to Cycle Tool (PCT) is an online, interactive planning support system which was initially developed to explore and map cycling potential across England (see www.pct.bike). Based on origin-destination data, it models and visualises cycling levels at area, desire line, route and route network levels, for current levels of cycling, and for scenario-based 'cycling futures'. Four scenarios are presented, including 'Go Dutch' and 'Ebikes', which explore what would happen if English people cycled as much as Dutch people and the potential impact of electric cycles on cycling uptake. The cost effectiveness of investment depends not only on the number of additional trips cycled, but on wider impacts such as health and carbon benefits. The PCT reports these at area, desire line, and route level for each scenario. The PCT is open source, facilitating the creation of additional scenarios and its deployment in new contexts. We conclude that the PCT illustrates the potential of online tools to inform transport decisions and raises the wider issue of how models should be used in transport planning., Comment: Paper submitted for peer review. 9 figures

The daily trip to work is ubiquitous, yet its characteristics differ widely from person to person and place to place. This is manifested in statistics on mode and distance of travel, which vary depending on a range of factors that operate at different scales. This heterogeneity is problematic for decision makers tasked with encouraging more sustainable commuter patterns. Numerical models, based on real commuting data, have great potential to aid the decision making process. However, we contend that new approaches are needed to advance knowledge about the social and geographical factors that relate to the diversity of commuter patterns, if policies targeted to specific individuals or places are to be effective. To this end, the paper presents a spatial microsimulation approach, which combines individual-level survey data with geographically aggregated census results to tackle the problem. This method overcomes the limitations imposed by the lack of available geocoded micro-data. Further, it allows a range of scales of analysis to be pursued in parallel and provides insights into both the types of area and individual that would benefit most from specific interventions.

Cycling has a range of health, environmental and economic benefits compared with motorised forms of transport. There is a need to encourage more cycling, yet previous evaluations of cycling promotion schemes have been inconclusive about what works. A case study of a cycling promotion scheme at the University of Sheffield – the Cycle Challenge – is used in this paper to examine commuting behaviour and long-term behavioural shifts towards cycling in response to outside intervention at the organisational level. The Cycle Challenge was designed to encourage more people at the University to cycle through inter-departmental competition. Cycling behaviour was recorded before the Cycle Challenge and two years after the scheme’s completion. It was found that seventy five percent of participants who were not already regular cyclists reported increased cycling, yet the overall impact of this shift was limited because the majority of participants already cycled regularly. This failure to attract new cyclists suggests recruiting non-cyclists should be a priority in future schemes. Moreover, our study has methodological implications. Current strategies for evaluating the positive impact of cycle initiatives may overestimate the savings by neglecting the tendency of people to resume routine behaviour in the long run. Studies evaluating modal shift should therefore include provision for monitoring long-term behavioural change to provide input into estimated economic, environmental or health metrics of success.