As transport planning support systems (TPSS) such as models, frameworks and dashboards grow in prevalence among devolved, combined and regional authorities, it is essential to understand how these systems are being applied, and the institutional framework around them. To what extent do TPSS, and the abductions they make about society as it really is, impact transport policy outcomes? And how do systemic barriers shape the way that GIS systems can be used in practice? We use interviews with practitioners across England’s sub-national transport bodies (STBs) to understand contemporary attitudes surrounding TPSS and their use cases, clarifying existing assumptions regarding transport modelling. We find that in England there is a vicious cycle comprising a lack of multi-level governance and an overly austere funding model for local and regional authorities that hinder the possibilities for truly data-driven decision-making.

Background:Metro systems are essential for urban mobility but often expose commuters to particulate matter (PM) at levels far above roadside air. The London Underground (LU), the world's oldest metro, supports ∼4 million daily journeys and has elevated PM2.5 concentrations dominated by iron-rich particles from mechanical abrasion. These exposures raise concerns about long-term health effects. Methods:Using the Office for National Statistics Longitudinal Study (ONS-LS), we analysed two retrospective cohorts of economically active adults (≥16 years) living and working in London and recorded in the 1991, 2001, or 2011 Censuses. Cohort 1 (n = 7,343) compared LU commuters with above-ground rail users. Cohort 2 (n = 4,094) examined dose-response patterns between externally linked cumulative LU PM2.5 exposure and health outcomes. Exposure estimates combined Transport for London data, PM2.5 measurements, and geospatial modelling. Outcomes were all-cause mortality (1991 to 2017) and cancer incidence (1991 to 2015). Analyses used inverse probability weighting and the parametric g-formula. Results:Most LU commuters were estimated to encounter hourly PM2.5 levels >100 μg/m3. LU users were 1.93% (95% CI: 0.58-3.66) less likely to survive the follow-up period than above-ground rail users, while cancer risk differences were negligible. No dose-response pattern emerged, and a hypothetical 50% PM2.5 reduction produced minimal survival change. Conclusions:LU commuters experience PM2.5 concentrations roughly 8-10 times higher than above-ground levels. Mortality risk appeared slightly elevated, though uncertainty remains. Findings highlight the need for better exposure assessment and further research on metro-related PM.

This paper explores the nuances of car dependence in England and Wales by identifying four distinct archetypes that span structural and conscious forms. Employing the 2011 England and Wales Census, archetype prevalence is mapped across the study area at the LSOA level, and a demographic analysis is performed. We find that while dependence exists across the study area, structural dependence is found more in rural areas, particularly the east coast of England and Wales, while conscious dependence is more prevalent in and around urban centers. The demographic makeup of each archetype differs significantly, with disability, socio-economic class, and ethnicity arising as notable significant indicators. This work highlights that an equitable transition to a sustainable transport system requires geographically and demographically specific policies tailored to the unique needs of each archetype. This transition away from car dependence, especially internal combustion engine vehicles, is imperative for a just and climate-resilient transport system.

A perception that proximity to good schools pushes house prices up is common and one factor that contributed to a shift in the secondary-school admissions policy away from proximity-based criteria in Brighton, England, in 2008. This decoupling of proximity was expected to reduce perceived house price inflation near good schools. But is this link as strong as many believe, or are other factors more important? We examine 81,000 residential transactions in Brighton between 2000 and 2019, assessing the effect of schools alongside other contextual factors such as building attributes, accessibility to jobs, deprivation, and macro price trends, as well as the impact of the policy change in 2008. We find that after accounting for local neighbourhood confounders and a general upward drift in property prices, proximity to good schools has only a limited impact on house prices, with other local factors often playing an often more important role. The admissions policy reform has little discernible impact on prices.

BACKGROUND:Particulate matter emissions from residential wood burning are rising in many countries. Long-term exposure to fine particulate matter is strongly linked with adverse health effects including cardiovascular and respiratory disease. Policymakers and scientists need accurate tools to identify residential wood burning hotspots. However, current methods rely on spatially-misaligned, out-of-date data sources, reducing their practical utility and portability to other contexts. Furthermore, the socio-economic characteristics of residential wood burning in high income countries are poorly understood. METHODS:We used open data from 26 million Energy Performance Certificates (EPCs) for properties in England and Wales from 2009-2025 to map the concentration and prevalence of wood burners within small areas. We evaluated our method against the UK national wood burning emissions inventory using national air pollution monitoring networks. We used novel open data linkages to characterise associations between area-level prevalence of wood burners and socio-economic factors including deprivation, ethnicity, and age. FINDINGS:We identified substantial spatial heterogeneity in the concentration of wood burners, with the highest concentrations in affluent urban areas. Our concentration metric was more strongly correlated with peaks in winter PM2.5 at urban monitoring sites than estimates from the UK national emissions inventory. Prevalence of wood burners was positively correlated with age and negatively correlated with measures of social deprivation. Prevalence of wood burners in EPCs has increased since 2009. CONCLUSIONS:EPCs are a valuable data source which policymakers can use to target local interventions or extend existing restrictions on solid fuel burning. Our method is transparent, up-to-date, and portable to other countries where similar EPC data is available. The relationship between social deprivation and prevalence of wood burning heat sources highlights important issues of environmental justice. Epidemiological analyses of wood smoke exposures and health should carefully account for the confounding effects of age, deprivation, and ethnicity.

Spatial interaction models (SIMs) are a core tool in spatial data modelling to predict spatial flows and understand their underpinning factors. SIMs have been applied to provide data insights and support decision making in multiple settings, notably in transport, human mobility, migration and epidemiology. While considerable progress has been made on advancing the theoretical and methodological underpinnings of SIMs, key challenges remain to facilitate the application of SIMs, extend existing modelling approaches, and leverage the opportunities afforded by Big Data. We identify three key challenges: reproducibility, calibration and Big Data modelling. We propose a blueprint to tackle these challenges by identifying four areas of development: (1) to enable essential infrastructure to facilitate the training, calibration and reproducibility of SIMs; (2) to embrace modelling frameworks to capture spatial, temporal and population heterogeneity; (3) to enhance statistical inference to accommodate Big Data analysis; and, (4) to integrate data science approaches to enhance SIM-generated predictions and statistical inference

Build-to-Rent (BTR) developments have expanded rapidly in the UK since 2013, often advertised as providing better quality rented accommodation for university-educated Millennials than available elsewhere in the private rental sector. However, the implications of this type of housing development, and especially its affordability, are poorly understood at the city scale, partly due to a lack of evidence of where these developments cluster and what they add to the housing stock in terms of property type, amenities and cost. This article draws on data relating to 373 BTR developments in London (representing over 40,000 housing units) to show that developments are clustered where transport-related infrastructural investments have opened 'rent gaps' that can be exploited by developers. Exploring how these BTR schemes are marketed, the article shows that this accommodation is typically provided through new short-term 'subscription services' which allow developers to rent property at a premium. Questioning whether BTRs really add affordable 'local' homes to the city, the article concludes that BTR provides 'quick-fix' rental accommodation which is doing little to solve London's housing crisis. We focus on the London BTR market and how the expansion of this housing type is reshaping the sociospatial geographies of the city. (sic) 2013 (sic)(sic)(sic), (sic)(sic)(sic)(sic)(BTR) (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic) 373 (sic) BTR (sic)(sic)(sic)(sic)((sic)(sic) 40,000 (sic)(sic)(sic)(sic)(sic))(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic)"(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic)".(sic)(sic)(sic)(sic)(sic)(sic) BTR (sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic)"(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic) BTR (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)"(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic), BTR (sic)(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic) BTR (sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

Reducing urban inequalities is at the forefront of the global sustainable development agenda, as well as national and local policies. While existing measures of inequality are mostly focused on income and wealth, it is widely recognised that non-monetary disparities such as in health, education, and housing play a crucial role in creating and reinforcing inequalities. Transport plays a central role in mitigating inequalities by enhancing access to employment, education, and essential services. It is also directly and indirectly related to disparities in housing, neighbourhoods, and health. Policymakers increasingly recognize the potential of transport policies in addressing inequalities; however, the effects of interventions need to be understood beyond the transport sector only and should consider wider impacts. In this review, we concentrate on three interlinked sectors – housing, land-use, and transportation – where local governments possess some capacity to influence the processes by which inequalities are created and exacerbated. Currently, empirical research on inequalities within these domains is fragmented. Models and datasets used for scenario testing, planning, and intervention evaluation are often disjointed, sector-focused, and rarely consider distributional effects. Our aim is to critically review the literature across different disciplines and perspectives and propose future interdisciplinary directions towards better measurement and modelling of transport-associated inequalities.

People's use of the rail transit system varies over space. Previous literature suggests there is a social equity dimension in the distribution of benefits from new urban transit systems, but how this varies spatially is poorly evidenced. The research aims to examine the spatial differences in the use of rail transit and associated transport equity. Using a case study of Chongqing, a geographically weighted regression (GWR) model is used to reveal the spatial variation in parameter estimates, complementing the traditional multivariate global model. The analysis demonstrates the effect of rail transit in facilitating people's travel and mitigating transport-related social inequity, including for those with mobility disadvantages and living in areas with poor access to public transport. The results emphasise the necessity of associated development strategies and transport policies in favour of socially disadvantaged groups, such as low fare levels. Implications for planning interventions are proposed based on the model results.

Poor energy efficiency of homes is a major problem with urgent environmental and social implications. Housing in the UK relies heavily on fossil fuels for energy supply and has some of the lowest energy efficiency in Europe. We explore spatial variations in energy efficiency across England using data from Energy Performance Certificates (EPCs), which cover approximately half of the residential stock (14M homes between 2008-22). We examine variations between authorities after accounting for the composition of the housing stock in terms of its fixed characteristics of property type, building age and size. We explore variations in terms of geographical and social context (region, urban-rural and deprivation), which gives a picture of the scale of the challenge each faces. We also examine variations in relation to the more readily upgraded factors, such as glazing types, and in relation to local participation in improvement programmes which gives some insight into local actions or progress achieved.

Urban transit systems have differential impacts across population groups, including the perceptions of impacts. Nevertheless, the evaluation of difference in perceived benefits of transport investment is under researched, and few attempts have been made to quantify the extent to which transport provision meets users' requirements. This paper explores how the impact of rail transit on development and regeneration differs across different income groups and migrants, assessing equity dimensions that arise through surveys on residents' perceptions, using evidence from Chongqing, China. The analysis utilises both MANOVA and discriminant analysis. The result shows that the lowest income group perceives they benefit least from the rail transit impacts, while the highest income group perceives they benefit most. There is a significant unequal perceived benefit distribution between migrants and local residents within the low-income groups. Reflections are made on policies and planning interventions which might be introduced to achieve greater social equity in impacts.

As China transforms and experiences massive rural-to-urban migration, the destination decisions and family structures of internal migrants have become increasingly diverse. This study investigates how the family structures of married migrants with children relate to the geography of their migration destinations. Our analysis reveals that the family structures of married migrant workers are systematically related to the geography of their migration destinations, with couple migrants relatively more likely to be located in mega cities while entire family migrants are more likely to locate in less developed regions. Furthermore, this study found that migrant workers with different migration paths have distinct preferences for their destinations. Migrant workers who initially migrate with their whole families tend to avoid economically developed areas, whereas those transitioning from lone to couple migration are more inclined to move to developed eastern regions and mega cities. Those finding highlights the importance of family dynamics and social factors in shaping migration decisions, providing a more comprehensive perspective on the factors that influence destination beyond purely economic considerations.

Neighbourhoods are fundamental spatial units to present social phenomena in urban studies. Many studies use administrative boundaries such as census tracts as representations of neighbourhoods, but such boundaries may poorly represent the underlying social structures and physical attributes which might help define more vernacular conceptions and dialectical evolution of these zones. In this paper, using the goal of creating a new set of ‘Strategic Neighbourhoods’ for Transport for London (TfL) as vehicle for analysis, we evaluate two contrasting spatially and socially focused methodologies of neighbourhood generation. In comparing the outputs of a tertiary-communities (T-Communities) method and a combined Principal Component Analysis (PCA) and Minimum Spanning Tree (MST) cluster analysis method with an earlier iteration of Strategic Neighbourhoods defined by TfL, indices including neighbourhood size, intra-class correlation coefficient (ICC), and the number of community centres are calculated to evaluate their relative performance which demonstrate that both methods create neighbourhood boundaries that can better capture intra-group social homogeneity and are more suitable for analysis than the original SNA boundaries. These results are discussed in the context of the dialectic relationship between neighbourhood outcomes, spatial structures, and social characteristics, leading to more widely relevant conclusions that neighbourhood boundary delineation should combine spatial structure, social attributes, and experimental knowledge to effectively sub-divide urban activity.

This paper presents a masters level geographic information systems and science course (CASA0005) developed by the Bartlett Centre for Advanced Spatial Analysis (CASA), University College London (UCL).CASA0005 is a compulsory module for both MSc programs within the department, running annually in the autumn term with between 100 and 150 enrolled students.During the summer of 2019 the module was transformed from static practicals with some legacy content related to commercial software to an online interactive book primarily for the open source R data science programming language written using the Bookdown package (Xie, 2016). Resource storyThe geographic information systems and science course (CASA0005) is a core module on the CASA MSc and MRes programmes.Originally conceived primarily using ESRI's ArcMap with some Quantum GIS (QGIS), in recent years, consecutive module leaders and module staff, namely the authors of this paper, have transitioned and developed the content to R, with some QGIS.This reflects feedback from alumni, academia and industry that value programmatic and importantly reproducible GIS analysis.The course is representative of the expertise of the module staff with point pattern originating from Adam Dennett, raster analysis from Andrew MacLachlan and geographical regression a collaboration between the two.

Housing is a major source of inequality in England, but most house price variation studies are conducted at national or regional scale or, conversely, in a specific city. Detailed research at sub-regional level is missing, especially for the period after the global financial crisis. This research addresses this gap with an analysis of variation at local authority level across England between 2009 and 2016. A novel house price per square meter (HPM) dataset is used to control for property size effects in transaction price variation. The effects of two spatial levels (local authority (LA)-and Middle Layer Super Output) together with three time categorizations (quarterly, half-yearly, and yearly) is systematically explored using multilevel models. Results show that the time categorization effects are essentially identical and extremely small, in comparison with the LA effects. As annual effects provide the best model fit, LA annual house price trajectories are explored further. Overall higher HPM LAs grew faster over the 80-year period than lower HPM LAs. More locally the spatial pattern shows some variation in the overall pattern, with some LAs near London or Bristol exhibiting higher relative percentage HPM increases with a relatively lower initial HPM compared with their neighbors.