Advancing a Participated GIS-based Policy Tool for Addressing the Needs of People with Impaired Mobility in Urban Environments.

Description

Project Background and Aims

Global initiatives such as the United Nations’ Sustainable Development Goal 11 emphasise the need for inclusive, safe, and accessible cities, particularly for vulnerable populations. In the UK, policies like the Equality Act 2010 and the Disability Action Plan mandate accessibility improvements, yet urban infrastructure often falls short for individuals with mobility impairments. Existing Geographic Information System (GIS) applications primarily focus on route planning rather than comprehensive accessibility assessment, and many rely on city-specific or ad-hoc datasets that limit their broader applicability.

This project aims to develop a GIS-based policy tool that systematically evaluates and enhances urban accessibility for mobility-impaired individuals. The tool will integrate urban environment characteristics, spatial distribution of the impaired population, and sociodemographic factors to generate a street-level accessibility index. Machine learning algorithms will assess pedestrian infrastructure quality using street imagery, providing a data-driven approach to identifying accessibility gaps. A web-based GIS tool will be developed to support policymakers, urban planners, and advocacy groups in prioritising interventions. Liverpool (UK) will serve as the case study.

Candidate Responsibilities

The selected candidate will take a lead role as regards all the phases of the project. They will expect to conduct activities pertaining:

• The collection of secondary data pertaining the scopes of the project, from both national and local sources.
• Engaging with stakeholders, including disability advocacy groups and policymakers.
• Using machine learning techniques to develop an algorithm able to quantify the quality of the pedestrian facility from street imagery.
• Conducting tasks related to spatial data processing and analysis.
• Implementing a network-based accessibility measure that incorporates multiple dimensions (street design, social dimensions, and individual-health related ones).
• Developing a web-based interactive GIS tool to display the facets of the accessibility measure.
• Liaising with urban planners and policymakers to integrate research findings into practical applications.

The candidate will be expected to author three research papers describing the different stages of the research and the intermediate achievements. Moreover, they will present findings to an academic audience, by attending conferences or workshops. Finally, together with the rest of the team, they will produce a policy report with a set of recommendations.

Skill requirements

Minimum requirements include:

• A bachelor’s or master’s degree in human Geography, Geographic or Geoinformation (Data) Science, Computer Science, Urban Geography, or an equivalent title.
• A proficient level of written and spoken English (C1 Level).

The project requires the following essential skills:

• Ability to analyse spatial vector data.
• GIS applications, and coding skills in R and / or Python.
• An interest in spatial networks and machine learning algorithms.

Desirable skills include knowledge and experience using machine learning and network analysis. Experience in conducting focus groups and collecting qualitative data or input will be considered an asset.

Supervision, Partner and Training

The candidate will be part of the Geographic Data Science Lab, Department of Geography and Planning, University of Liverpool. The supervision team includes Dr. Gabriele Filomena, Dr. Olga Gkountouna, and Dr. Ron Mahabir at the University of Liverpool. They will support the candidate throughout their project with regular meetings and will provide guidance and support to favour not only the successful completion of the project, but also the development of the candidate as an independent researcher.

The project is supported by the Liverpool City Region Combined Authority (LCRCA). LCRCA – in the person of Alex Naughton - will serve as a strategic policy advisor and sounding board throughout the project and will also constitute a potential target for the adoption of the policy tool after the project concludes. They will provide knowledge about the case study area and offer guidance on the design of the policy tool.

Professor Ed Manley, at the University of Leeds, will also be part of the supervision team.

A Personal Development Programme will be devised by the candidate and supervisory team. Training opportunities will be accessible through the University of Liverpool (within Geography and related social sciences and the engage@liverpool programme of training and workshops), and the Northwest Social Science Doctoral Training Partnership (NWSSDTP). The candidate will be encouraged to participate in the NWSSDTP’s Methods programme, with reference to the Quantitative Methods or New forms of data/digital methods themes.