Geospatial Data Science

A-Z

University of Glasgow

Geospatial Data Science

Location: Glasgow, United Kingdom
Funding: - View a full list of our current scholarships
Application deadline: See university guidance

About the project

Postgraduate research

Geospatial Data Science PhD

Our Online Application Form and Applicant Self Service will be unavailable from 08:00-14:00 (GMT) on Thursday 29 October for essential maintenance. We apologise for any inconvenience caused.

PhD: 3-4 years full-time; 6-8 years part-time; Thesis of Max 80,000 words

Self-funded projects

+++

Indicative Data Science: Extracting 3D Models of Cities from Unavailability and Degradation of Global Navigation Satellite Systems (GNSS)

This project will implement a crowdsourcing-based approach to create accurate 3D models from the free to use and globally available data of Global Navigation Satellite Systems (GNSS).

The effects of urban features, such as buildings and trees, on GNSS signals, i.e. signal blockage and obstruction, and attenuation, will help to recognise the shape, size, and materials of urban features, through the application of statistical, machine learning (ML) and artificial intelligence (AI) techniques.

The use of freely accessible raw GNSS data, which can be accessed on any current Android device, will enable the production of up to date 3D models at no or low cost, of particular value in developing regions where these models are not currently available.

GNSS

GNSS is the most widely used positioning technique because of free-to-use, privacy-preserving, and globally available signals. However, GNSS signals can be blocked, reflected and/or attenuated by objects, e.g. trees, buildings, walls and windows. While blockage, attenuation and reflection of GNSS signals are common in urban canyons and indoors, making the positioning unreliable, inaccurate or impossible, the affected received signals can act as an indicator of the structure of the surrounding environments.

This means, for example, if the signals are blocked or attenuated, then the size and shape of the obstacles or the type of media/material the signals have gone through or been reflected by can be understood. This needs the precise locations of satellites, and the receiver, and also predicted signal strength level at each location and time.

The crowdsource-based framework, i.e. a mobile app for data capture and a web mapping application for upload of GNSS raw data, will allow the project to have well-distributed data both in space and time. This will ultimately lead to higher quality (more spatially and temporally accurate, complete, precise) 3D models.

However due to the complexity of data, as neither the receiving mobile devices nor the broadcasting satellites are fixed, some novel data mining techniques, based on already existing statistical, ML, and AI techniques, need to be developed during this fellowship. They will handle the high volume, the velocity of change, and the complexity of the spatio-temporal GNSS raw data with high levels of veracity. The spatio-temporal patterns will be used for creating and updating the 3D models of cities at a high level of detail (LoDs), i.e. approximating the façade and the building materials, e.g. windows, from which the signals are reflected or have gone through. The 3D models will feed into 3D-mapping aided GNSS positioning (and integrated with other signals e.g. WiFi) which can ultimately provide more continuous and accurate GNSS positioning in urban canyons and indoors.

---

+++

Developing methods embracing challenges of new forms of data

We develop theoretical and applied solutions to the challenges of 'new forms of data' such as missingness and biases. Our Indicative Data Science project looks at developing solutions based on the mindset that considers the bias, missingness, or low quality as a useful source of data to make inference about the underlying reasons for the missingness and bias.

In the era of big data, open data, social media, and crowdsourced data when 'we are drowning in data', gaps and unavailability, representativeness, and bias issues associated with them may indicate some hidden problems or reasons of biases and missingness. These novel solutions allow us to understand the data, society, and cities better.

---

+++

Colouring Glasgow

Colouring Glasgow is a knowledge exchange platform that provides open statistical data about the city's buildings and the dynamic behaviour of the stock. We're working to collate, collect, generate, verify over fifty types of data and to visualise many of these datasets.

Our information comes from many different sources. As we are unable to vouch for data accuracy, we are experimenting with how to present data sources, how data are edited over time, and how to ask for data verification, to help you to check reliability and judge how suitable the data are for your intended use. Your help in checking and adding data is very much appreciated.

---

+++

Intelligent Navigation Services

This extremely multi-disciplinary research theme looks at different aspects of navigation including positioning and localisation, path finding and routing algorithms, sense of direction, human computer interaction, cognitive navigation, intelligent mobility, and artificial intelligence.

---

+++

Sensor fusion and Signals of Opportunity

We look at different positioning signals and state-of-the-art sensor data to understand the mobility and movement of people in a non-intrusive way, model occupancy of buildings and energy consumption, better urban planning and use of space, and more recently for contact tracing and social distancing purposes.

---

+++

Explainable AI (XAI) for geospatial data modelling

Machine learning and artificial intelligence (ML/AI) have been increasingly used to model geospatial phenomena. However, ML/AI models are often considered as 'black box’ approaches that their internal mechanisms cannot be understood easily by humans. This raises problems around model transparency, bias, discrimination, trustworthiness, and accountability, all of which have strong technical and ethical implications. This project focuses on the fundamental aspects of XAI and aims to develop novel methods to improve the explainability of AI-based geospatial modelling.

---

+++

Understanding Polycentric Urban Systems with Geospatial Data Science

A polycentric urban system refers to a system of multiple physically independent but connected urban agglomerations. It has been widely observed as an empirical reality and envisioned by policymakers as a sustainable development tool worldwide. This project aims to develop an innovative methodological framework to measure polycentric urban systems at multiple scales across different geographical contexts.

---

+++

Built environment and collective human behaviors

The proliferation of geospatial data and the advancement of computational methods allow us to delineate the built environment and observe collective behaviors in fine detail. Against this backdrop, this project aims to understand the relationship between the built environment and collective human behaviors by combining geospatial data and computational methods.

---

Overview

Our Geospatial Data Science programme is suitable for students wishing to pursue a PhD and undertake innovative research in a wide range of subjects which aligns to one of our Geospatial Data Science themes, including:

geostatistics
geospatial data quality
new forms of geospatial data such as crowdsourced data to help improve our understanding and location-based services to the societies.

Study options

full-time (years) | part-time (years)

Phd | 3-4 | 6-8

Entry requirements

2.1 Honours degree or equivalent

English language requirements

For applicants from non-English speaking countries, as defined by the UK Government , the University sets a minimum English language proficiency level.

Accepted English language tests

We accept a wide range of English language tests for entry to this programme. Tests must have been taken within 2 years 5 months of programme start date, and requirements must be met using a single test.

International English Language Testing System (IELTS) Academic and Academic Online (not General Training)

6.5 with no subtests under 6.0
IELTS One Skill Retake Accepted
We do not accept General Training

TOEFL iBT (including MyBest and Home Edition)

Tests taken up to 20 January 2026

Tests taken from 21 January 2026

90 Overall , no subtest lower than Reading 20; Listening 19; Speaking 19; Writing 21
92 Overall , no subtest lower than 4.5

Pearsons PTE Academic (test centre only)

65 overall with no subtest less than Reading 60; Listening 60; Speaking 65; Writing 60

Cambridge C1 Advanced and C2 Proficiency

176 overall, no subtest less than 169

Oxford ELLT

7 overall with no subtest less than 6

LanguageCert Academic SELT/Academic/Academic Online

70 overall with no subtest less than 60

Password Skills Plus

6.5 overall with no subtest less than 6.0

Trinity College Integrated Skills in English II

96 overall with no subtest less than 90

Kaplan Test of English

Any two subtests at 480 or higher, and any two subtests at 450 or higher

PSI Skills for English

B2 Pass with Merit

Duolingo English Test

120 overall with Writing at 120 and no subtest less than 110

Oxford Test of English Advanced

140 Overall with any two subtests at 126 or higher, and any two subtests at 136 or higher

Alternatives to English Language qualification

Degree from majority-English speaking country (as defined by the UKVI including Canada if taught in English)

TNE degree for UK University taught at a campus outside of the UK.

Students must have studied for a minimum of their final year at Undergraduate level, or 9 months at Master's level, and must have completed their degree in that majority-English speaking country within 6 years of programme start.
Students must be awarded the degree by the UK university and must have completed the degree within 6 years of programme start.

Pre-sessional courses

The University of Glasgow accepts evidence of the required language level from the English for Academic Study Unit Pre-sessional courses. We would strongly encourage you to consider the pre-sessional courses at the University of Glasgow's English for Academic Study (EAS) Unit. Our Pre-sessional courses are the best way to bring your English up to entry level for University study. Our courses give you:

For more detail on our pre-sessional courses please see:

We can also consider the pre-sessional courses accredited by the below BALEAP approved institutions to meet the language requirements for admission to our postgraduate taught degrees:

direct entry to your University programme for successful students (no need to take IELTS)
essential academic skills to help you study effectively at University
flexible entry dates so you can join the right course for your level.
Pre-sessional courses
Heriot Watt
Kingston Upon Thames
Middlesex University
Manchester University
Reading University
Edinburgh University
ST Andrews University
UCL
Durham

2027/28

Prices are based on the annual fee for full-time study. Fees for part-time study are half the full-time fee.

Irish nationals who are living in the Common Travel Area of the UK, EU nationals with settled or pre-settled status, and Internationals with Indefinite Leave to remain status can also qualify for home fee status.

UK: To be confirmed [26/27 fee was £5,238]
International & EU: £33,708
Fee status and policies

Alumni discount

We offer a 15% tuition fee discount to eligible self-funded alumni starting a Postgraduate Taught (PGT) Masters or Postgraduate Research (PGR) programme in the 2027/28 academic year.

This includes University of Glasgow graduates and those who have completed a Study Abroad programme, Exchange programme, International Summer School or Erasmus programme with us. This discount can be awarded alongside most University scholarships. No additional application is required.

Full details of our Alumni Discount

Possible additional fees

Depending on the nature of the research project, some students will be expected to pay a bench fee (also known as research support costs) to cover additional costs. The exact amount will be provided in the offer letter.

Re-submission by a research student £540
Submission for a higher degree by published work £1,355
Submission of thesis after deadline lapsed £350
Submission by staff in receipt of staff scholarship £790

Funding

View a full list of our current scholarships

Support

The vibrancy of our research environment derives from our large body of postgraduate students.

We take an integrated approach to study at Glasgow, bringing together internationally leading expertise in physical and human geography, geology and geomatics.

Our postgraduate students benefit from many fieldwork opportunities, ranging from short day excursions close to Glasgow to longer residential field trips, which may involved overseas travel.

The School has close links with industry. We arrange many guest speakers and there are also informal opportunities to meet people from industry at open events. Projects may be carried out in conjunction with industry.

You will be part of a Graduate School which provides the highest level of support to its students.

The overall aim of our Graduate School is to provide a world-leading environment for students which is intellectually stimulating, encourages them to contribute to culture, society and the economy and enables them to become leaders in a global environment.

We have a diverse community of over 750 students from more than 50 countries who work in innovative and transformative disciplinary and interdisciplinary fields. An important part of our work is to bring our students together and to ensure they consider themselves an important part of the University’s academic community.

Being part of our Graduate School community will be of huge advantage to you in your studies and beyond and we offer students a number of benefits in addition to exceptional teaching and supervision, including:

Over the last five years, we have helped over 600 students to complete their research studies and our students have gone on to take up prestigious posts in industries across the world.

Email: scieng-gradschool@glasgow.ac.uk

A wide-ranging and responsive research student training programme which enables you to enhance your skills and successfully complete your studies.
Mobility scholarships of up to £4000 to enable you to undertake work in collaboration with an international partner.
A diverse programme of activities which will ensure you feel part of the wider-research community (including our biannual science slam event).
A residential trip for all new research students.
The opportunity to engage with industry-partners through training, placements and events.
Professionally accredited programmes.
Unique Masters programmes run in collaboration with other organisations.
State-of-the-art facilities including the James Watt Nanofabrication Centre and the Kelvin Nanocharacterisation Centre .
Highly-rated support for international students.

Identify potential supervisors

All Postgraduate Research Students are allocated a supervisor who will act as the main source of academic support and research mentoring. You may want to identify a potential supervisor and contact them to discuss your research proposal before you apply. Please note, even if you have spoken to an academic staff member about your proposal you still need to submit an online application form.

You can find relevant academic staff members with our staff research interests search .

Required documents

Before applying please make sure you gather the following supporting documentation: