Discovering the way: Automated Machine Learning improvement of Ordnance Survey path network data

Qualification: PhD

Department: Geography

Application deadline: 9 August 2020

Start date: 28 September 2020

Overview

Supervisors

Project description

Geospatial Artificial Intelligence (GeoAI) is an emerging field (Li, 2020) that aims to combine methods and concepts in geographic information science with the transformative innovations in machine learning, particularly deep learning, and big data to create novel approaches to spatial data science (De Sabbata and Liu, 2019). The collection of geospatial data is a critical activity that faces many challenges, including high cost and variable data quality (Ballatore and Zipf, 2015). Current advances in GeoAI promise to enable more effective methods to detect and correct issues in complex real-world data.

Footpaths provide valuable opportunities for outdoor activities and exploration in UK, and in the urban environment are an important component of last-mile services. By investigating a novel spatially explicit machine learning technique that combines least-cost path network analysis this project aims to further improve the quality and completeness of OS MasterMap® Highways Network – Paths, the most accurate and authoritative path network dataset for Great Britain.The project will:

  • Extract a body of known footpaths from historic sources and current OS walking routes.
  • Develop a spatially explicit model to predict the location of footpaths based on a least-cost path (LCP) network analysis of topographic and environmental characteristics.
  • Apply a Deep Learning approach to identifying potential footpaths through graph link prediction.
  • Compare predicted paths with the OS MasterMap® Highways Network – Paths data and establish a methodology to automatically update the OS path network.

This PhD offers the opportunity to work with two leading academic organisations (University of Leicester and Birkbeck) supported by the Ordnance Survey, Great Britain's national mapping agency.

Funding

Funding

This project is funded by Ordnance Survey and provides:

  • Stipend at UKRI rates of £15,285 per year and tuition fees at UK/EU rates for 3 Years
  • The project will also include RTSG money.
  • The project is subject to pending contract agreements.

Entry requirements

Entry requirements

UK Bachelor Degree with at least 2:1 in a relevant subject or overseas equivalent. 

University of Leicester English language requirements apply (where applicable).

Informal enquiries

Informal enquiries

Project enquiries

Application enquiries

How to apply

How to apply

Please use the 'Apply button' at the bottom of the page and select September 2020 entry.

In the funding section of the application please indicate you wish to be considered for the GGE de Sabbata OS Studentship.

In the proposal section please provide the name of the supervisors and project title (a proposal is not required).

With the application, please include:

  • CV 
  • Personal statement explaining your interest in the project, your experience and why we should consider you
  • Degree Certificates and Transcripts of study already completed and if possible transcript to date of study currently being undertaken
  • Evidence of English language proficiency if applicable
  • In the reference section please enter the contact details of your two referees in the text boxes provided or upload letters of reference if already available.

Eligibility

Eligibility

This project is available for UK/EU applicants only.