Geospatial Artificial Intelligence MSc

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Module information is intended to provide an example of what you will study.

Our teaching is informed by research. Course content changes periodically to reflect developments in the discipline, the requirements of external bodies and partners, and student feedback.

Full details of the modules on offer will be published through the Programme Regulations and Specifications ahead of each academic year. This usually happens in May.

To find out more please see our terms and conditions.

Optional modules availability

Some courses have optional modules. Student demand for optional modules may affect availability.

You’ll be taught using a range of methods, including:

• lectures  
• seminars  
• practical lab/workshop sessions  
• field work
• group work
• case studies 

Depending on your modules, you'll be assessed through a combination of:

• Case study
• Computer assessment
• Dissertation
• Lab exercise
• Practical lab report
• Poster
• Portfolio
• Problem-solving exercises
• Reflective log
• Written exercise

In Semester 3, you’ll complete a 60-credit independent research project, including a written dissertation. Most projects involve industry collaboration and let you explore a topic of personal or professional interest. 

You’ll receive one-to-one academic guidance via a personal tutor and a dedicated dissertation supervisor. Tutors are available during office hours, and you’ll benefit from a supportive research environment throughout the course. 

Your teaching will be led by experts in their fields, including: 

Professor Jon Mills specialises in: 

• Development and assessment of new and integrated earth observation sensor systems and platforms 
• Novel methods and models for fusing multi-modal earth observation data 
• AI/machine learning for image information extraction 

Dr Craig Robson specialises in: 

• Using spatial data through data-science approaches to solve complex problems 
• The application of digital technologies such as AI, ML, BIM and digital twins in Engineering contexts and for exploring the impacts of climate change 
• Data handling and management for complex, diverse geospatial datasets 
• Approaches for data visualisation and decision support tools for real-time decision making 

Professor Peter Clarke specialises in: 

• Using global satellite geodesy to observe the seasonal water cycle, climate change, sea level, and glacial isostatic adjustment 
• Global geodetic reference frames – the basis of all spatial data 
• Geodetic observations of the earthquake cycle and associated geophysical inverse theory and data assimilation methods 

Dr Maria-Valasia Peppa specialises in: 

• Integrating multimodal and multiscale geospatial data and Earth Observations from various sources (e.g. drones, satellites, laser scanners, digital cameras, GNSS etc) 
• Applying photogrammetric, remote sensing, and computer vision techniques to real-world problems relating to the natural and built environment 
• Applying AI/machine learning with drone and satellite imagery to monitor water security-related challenges 

Dr Achraf Koulali Idrissi specialises in: 

• Using geodetic observations to study the active deformation of the Earth’s crust 
• Measuring 3D crustal movements to understand better modes of strain accumulation on major faults and the Earth’s rheology 
• Measuring the glacial isostatic adjustment in Antarctica using satellite geodetic observations. 
• Applying advanced machine learning methods, including physics-informed approaches, to extract meaningful geophysical signals from complex datasets. 

Dr Henny Mills specialises in: 

• Engineering Surveying – Delivering in-depth instruction on modern surveying techniques and instrumentation, including total stations, GNSS, and levelling, with emphasis on their application in engineering and the built environment. 
• Spatial Data Engineering – Providing expertise in the design, processing, and management of spatial datasets using geospatial databases, with a focus on ensuring data integrity, interoperability, and practical application in engineering contexts. 
• Building Information Modelling (BIM) – Instructing on BIM methodologies and tools for the digital representation of physical and functional characteristics of built environments, highlighting workflows, collaboration, and lifecycle data integration in engineering projects. 

Dr Alistair Ford specialises in: 

• Development of transport cost models through complex network analysis 
• Cellular automata modelling and multi-criteria analysis 
• Development of decision-support tools within commercial GIS software 

Xiang Xie specialises in: 

• Digital transformation of the built environment 
• Digital twin for existing built assets 
• Data-centric facilities asset management 
• Energy informatics for the decarbonisation of buildings 
• Whole-life carbon assessment for urban infrastructure 

Professor Philip James specialises in: 

• Data management and big data systems 
• Spatial data, maps, and mapping technologies 
• Web-based information system development 
• Data fusion and integration for analytics and visualisation 
• Smart cities: technical design, citizen participation, and governance 
• Sustainable and accessible data systems for research and public use