Environment and Planning B: Urban Analytics and City Science

doi: 10.1177/23998083261432384pmid: N/A

Beecham, Roger; Arribas-Bel, Dani

doi: 10.1177/23998083261431404pmid: N/A

Beecham, Roger; Tennekes, Martijn; Wood, Jo

doi: 10.1177/23998083251374737pmid: N/A

We present gridmappr, an R package that automates the process of generating gridmaps – small multiple data graphics of regular size, laid out with an approximate geographic arrangement. Given a set of real geographic point locations, gridmappr allocates points to a regularly sized grid of stated row–column dimensions. This allocation is constrained such that the distance between points in real and grid space is minimised and with a parameter that affects how compactly points are allocated to the regular grid. For geographies with features such as large bodies of water, fixed spacers can be introduced – reserved cells that cannot be allocated points. Layout examples are presented using different parameterisations, and code for generating a family of information-rich glyphmap and origin-destination maps is demonstrated using standard ggplot2.

Credit, Kevin; Farah, Irene; Talen, Emily; Anselin, Luc; Ghomrawi, Hassan

doi: 10.1177/23998083251377116pmid: N/A

This paper describes a straightforward method for calculating an open-source Walkable Accessibility Score (WAS) that measures walkability at the block group scale based on walking distance to business establishments, schools, and parks. Exploratory analysis of the WAS reveals high concentrations of walkable accessibility in the centres of the densest and/or largest cities. Our optimised specification (decay = 0.008, upper = 800, k = 30) performs very well, achieving a Spearman rank correlation of 0.912 with proprietary Walk Score® values (for 2011). We provided pre-calculated data for each year from 1997 to 2019 and Python code for calculating the WAS at the project’s GitHub repository. The method is particularly useful in that it uses simple Euclidean distance calculations, and thus can be run at scale on a laptop or personal computer.

Huck, Jonathan

doi: 10.1177/23998083251378340pmid: N/A

The QGIS ‘Polygon Divider’ plugin solves the problem of partitioning an arbitrarily complex polygon into an irregular grid of equal area rectangles, which has a range of applications for city science and GIS more broadly. This is achieved by the iterative partition of the polygon using cutlines that are located using Brent’s method, which is an efficient optimisation algorithm. At the time of release, this was the only tool with such functionality in a major GIS platform, though the functionality has since been replicated.

Nelson, Ruth; Warnier, Martijn; Verma, Trivik

doi: 10.1177/23998083251387382pmid: N/A

Evaluating accessibility based on multiple notions of justice allows for a multi-perspective analysis of the trade-offs between the benefits and burdens associated with the provision of infrastructure. This presents a challenge due to a lack of metrics which operationalise multiple notions of justice for comparative purposes. It is further complicated by the reliance on General Transit Feed Specification (GTFS) data to do many kinds of accessibility analyses, which is often not freely available and accessible, especially in data scarce regions. This paper presents the MAP open-source software package that allows for the incorporation of multiple notions of justice in accessibility analysis. Firstly, MAP supports the development of an Urban Network Model based on open-access data. Secondly, using this model it enables the calculation of Neighbourhood Reach Centrality, a cumulative accessibility metric. Finally, it allows for the evaluation of accessibility based on three comparative metrics of spatial justice visualised through maps. For illustrative purposes, data sets from the City of Cape Town in South Africa are provided as a ready-to-use data-product. This software package offers an efficient method for incorporating spatial justice considerations into accessibility analysis offering the potential to be used as a boundary object within interdisciplinary teams of researchers, policy-analysts, transport engineers, and other stakeholders.

Deakin, Will; Wang, Zhao; Parry, Josiah; Lovelace, Robin

doi: 10.1177/23998083251387986pmid: N/A

Route network datasets are fundamental to transport models, serving as both inputs for analysis and outputs for visualization and decision-making. The increasing complexity of route network data from sources like OpenStreetMap allows for more detailed modelling of sustainable transport modes such as walking and cycling. However, this level of detail can introduce challenges for the clear visualization and interpretation of model results. A common problem is the representation of single transport corridors by multiple parallel lines, which can create visual clutter and obscure important patterns in transport flows. The purpose of the work presented in this paper is to provide a basis for computationally efficient analysis and visualization of route networks for strategic transport planning, where intricate geometries, such as parallel or ‘braided’ linestrings, are unhelpful. We present and evaluate two distinct methods for simplifying complex route networks that are intended to be used as a ‘pre-processing’ step to speed up and improve the results of strategic transport network analysis, modelling, and visualization workflows. First, we present skeletonization, an approach that uses ‘thinning’ of rasterized network data to extract a simplified representation of the network. Second, we present a Voronoi-based approach using Voronoi diagrams to identify centrelines. We demonstrate the practical application of these methods using the ‘Simplified network’ layer in the Transport for Scotland-funded Network Planning Tool, a publicly accessible resource at https://www.npt.scot. To support reproducible research, we implement the methods in the open-source parenx Python package, enabling their use alongside other open source tools for transport planning, research, and educational applications.

Morgan, Malcolm

doi: 10.1177/23998083251401613pmid: N/A

Carbon & Place (https://www.carbon.place) is an ongoing research project to produce a free family of web tools intended to explain the spatial variation in per-capita carbon footprints across Great Britain and how they can be reduced. The tools present results via interactive maps using GIS data, small area statistics, surveys, and models to aid planners, policymakers, and communities in understanding their climate impact. Local people can benefit from disaggregated analysis as it can be more personally relevant and account for local circumstances and needs. This paper provides an overview of the project, its open-source website, and analysis pipeline, as well as reporting on its progress to date and future work.

Huo, Jingeng; Shi, Zhenqin; Zhu, Wenbo; Yan, Yanhui; Xue, Hua

doi: 10.1177/23998083251343146pmid: N/A

Urban development model is transitioning from disorderly sprawl to compact growth. In this process, urban growth boundary (UGB) is important for preventing excessive spatial expansion and optimizing land use structure. However, few existing studies have focused on delineation strategies that integrate both rigid and elastic UGBs. Taking Zhengzhou as a case study, we developed a framework for delineating rigid and elastic UGBs involving identification of basic farmland and ecological protection zone, evaluation of land suitability, and multi-scenario simulation of urban development. The results showed that urban space increased significantly by 210.56 km2 from 2000 to 2020, which posed risks of imbalanced land use structure. Identified basic farmland and ecological protection zone covered 41.99 km2 and 57.68 km2, respectively. Their scope was prohibited for urban construction and was used as guidance to delineate rigid UGB, which covered 712.21 km2. Sustainable development scenario was considered as dominant paradigm for urban development. Therefore, it was used as guidance to delineate elastic UGB, which covered 595.55 km2. These findings confirm the effectiveness of a delineation strategy that combines rigid and elastic UGBs in maintaining ecological security and constraining spatial sprawl. Additionally, technical references for delineating UGB are provided for cities facing compact growth demands.

Hou, Huiqiao; Pawlak, Jacek; Sivakumar, Aruna

doi: 10.1177/23998083251343715pmid: N/A

Arrivals and departures lie at the intersection of travel and building occupancy behaviours which dominate the landscape of energy demand in urban areas. Although transport and building systems are clearly linked, existing studies rarely consider the interactions between these systems in their modelling frameworks, thus restricting the policy-relevant scenarios that can be tested. This paper contributes to the field of data-driven energy modelling by proposing a flexible framework to integrate the modelling of travel and building occupancy behaviours, in which a travel simulator is coupled with a building occupancy model through a proposed mesoscopic link. The framework is operationalised in the context of the South Kensington Campus, Imperial College London, using the UK Time Use Survey data and Wi-Fi traceable logs. Implementing the framework for a hypothetical transport incident (i.e. sudden closure of the nearest underground station) generates people’s occupancy and circulation patterns across buildings, thus providing actionable insights for district-level smart grid planning and management. From a district planning perspective, occupancy schedules and dynamics in closed buildings are sensitive to incidents, whereas open and shared buildings are relatively stable. This finding indicates the need for flexible energy controls and smart grids with energy storage. From a building management perspective, occupancy durations generally reduce when affected by incidents, suggesting shortening the schedules of heating, ventilation and air-conditioning systems. From a facility management perspective, big changes in occupancy of closed buildings indicate unstable demands for the surrounding equipment (e.g. e-scooters, chargers), and efficiencies may be gained by allocating spaces/schedules to meet the dynamic demand.