Abstract

Spatial accessibility reflects the ease of reaching valuable destinations (Levinson & Wu, 2020). This concept has proved to play a fundamental role in a multitude of spatial dynamics within society, the environment, and the economy, including public transport ridership, land prices (Bourassa et al., 2021; Verduzco Torres, 2023a), public health (Chen et al., 2023), and unemployment rates (Bastiaanssen et al., 2022). Constructing accessibility measures requires the development of a comprehensive travel matrix (TTM) which represents the cost of movement from various origins to all potential destinations where services are available. Additionally, this needs the identification of land use and the specific location of facilities. While the integration of accessibility measures into analytical processes can strengthen planning and research towards a sustainable future, developing them from scratch requires specific technical skills, can be time-consuming, and demands considerable computational resources. ‘AccessUK’ is an open-source tool for the R programming language designed to streamline the integration of accessibility measures into R workflows focusing on Great Britain (GB) (Verduzco Torres, 2023b), thereby unlocking the potential of spatial data and analysis by informing decision-making processes and supporting sustainable practices across diverse sectors. The tool focuses on sustainable transport modes, namely public transport, walking, and cycling. It specifically enables users to: (1) get ready-to-use accessibility measures for a range of urban and regional services; (2) compute tailored accessibility measures using a set of pre-computed TTM for public transport, walking, and cycling for services not previously included in the dataset; (3) calculate new accessibility measures based on user-generated TTMs and service locations. AccessUK employs 'DuckDB', a relational database management system optimised for analytical workloads, which facilitates the rapid execution of queries without necessitating the full data load into virtual memory. This mitigates common computational challenges associated with large TTMs. The precomputed accessibility measures are sourced from a dataset series developed by the Urban Big Data Centre (UBDC) for 42,000 small areal units, known as Lower Layer Super Output Areas (LSOA) in England and Wales, and Data Zones (DZ) in Scotland. The methodologies and records are detailed in Verduzco Torres and McArthur (2024; 2024). The readily available measures encompass accessibility to employment, hospitals, pharmacies, general medical practices, schools, supermarkets, urban centres, as well as parks and public gardens. Getting precomputed accessibility measures into an R workflow is streamlined by inputting the geocode for an LSOA or DZ, or an array thereof, along with the desired mode and type of service. As the spatial analytical framework is based on the 2011 Census geographies, these measures can be smoothly incorporated into a variety of datasets and analyses through table joins. To compute customised accessibility measures, one simply inputs a georeferenced list of new facilities or services, selects the transport mode, and sets one or several time thresholds. Then, the tool employs pre-computed TTMs and returns a set of accessibility measures at the LSOA/DZ level. This is particularly advantageous for users who need to estimate access to customised facilities quickly using sustainable transport modes. For more advanced users, the tool provides a rapid and efficient accessibility function, allowing the computation of entirely new measures. This enables flexibility regarding the geographic unit of aggregation beyond the GB. While the use of DuckDB in the background helps analysts handle large-scale TTMs without the common issue of insufficient virtual memory, it requires users to provide their own TTM and location data of services. AccessUK is in development, with several aspects awaiting enhancement and limitations yet to be addressed. Currently, the tool requires the one-time per installation download of precomputed TTM and accessibility measures onto a local drive. Future updates are expected to facilitate access to specific data segments directly from a remote server through an API. Additionally, the current requirement for new service locations to be pre-aggregated in a table by geocode, via spatial operations, is scheduled for improvement; subsequent versions aim to allow for the direct input of spatial points. Presently, the tool provides only cumulative-type measures, with plans to expand its capabilities to include other types, such as gravity-based measures. Despite these forthcoming advancements, AccessUK stands as one of the most user-friendly resource for a broader range of analysts seeking to augment their work with accessibility measures tied to efficient modes of transport for a sustainable future.