CEG8733 : Applied AI and Geospatial Sustainability (Inactive)
- Inactive for Year: 2025/26
- Module Leader(s): Dr Alistair Ford
- Lecturer: Dr Maria-Valasia Peppa, Professor Philip James, Dr Craig Robson
- Owning School: Engineering
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 2 Credit Value: | 20 |
| ECTS Credits: | 10.0 |
| European Credit Transfer System | |
Aims
To understand and apply Artificial Intelligence (AI) concepts and methods in geospatial applications to address multiscale sustainability challenges. To develop industry relevant advanced geospatial data management, analysis and modelling skills.
Outline Of Syllabus
Students will be introduced to the United Nations Sustainability goals and wider challenges facing the society in the 21st century, such as the Sendai Disaster Risk Reduction Framework. The role of geospatial data, analysis, simulation and decision support in addressing these challenges will be investigated alongside the use of modern Artificial Intelligence (AI) approaches. Students will be taught core AI and machine learning concepts and shown how these underpin the use of modern unsupervised and supervised machine learning and deep learning methods and tools within geospatial sustainability analysis. The transformative application of Large Language Models, multi-objective optimisation evolutionary computing along with network complexity and agent-based models will also be explored. Students will be introduced to how these approaches can be coupled and integrated within flexible open-source workflows using the geospatial software stack and, open and FAIR data principles.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 1 | 3:00 | 3:00 | Submission of contents page for assessed essay/review |
| Guided Independent Study | Assessment preparation and completion | 1 | 2:00 | 2:00 | Online quiz |
| Guided Independent Study | Assessment preparation and completion | 1 | 20:00 | 20:00 | Literature critique/review |
| Scheduled Learning And Teaching Activities | Lecture | 24 | 1:00 | 24:00 | N/A |
| Guided Independent Study | Assessment preparation and completion | 1 | 20:00 | 20:00 | Computer assessment |
| Scheduled Learning And Teaching Activities | Practical | 8 | 3:00 | 24:00 | 8 computer practicals covering use of AI within geospatial sustainability applications |
| Guided Independent Study | Directed research and reading | 24 | 1:00 | 24:00 | Lecture review/reading |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 4 | 1:00 | 4:00 | Clinics for follow ups from practical classes and ahead of coursework submission |
| Guided Independent Study | Independent study | 79 | 1:00 | 79:00 | Further reading and coursework preparation |
| Total | 200:00 |
Teaching Rationale And Relationship
Lectures convey the core concepts, theories, and methods. Practicals enable the principles introduced in lectures to be put into practice, learned and assimilated through hands-on examples. The practicals have been developed to enable students to work independently towards submission of the computer assessment. Post-practical clinics will allow students to seek clarification on key concepts and practical methods. Tutorial sessions are provided to assist students with the development of their assessed essay and will cover geospatial specific research study skills.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Report | 2 | M | 50 | Geospatial AI implementation computer assessment. Utilization of methods from one of the AI practicals applied to an extended piece of analysis with report write-up (approx 2,000 words) |
| Essay | 2 | M | 50 | Literature critique/review of geospatial AI for a sustainability challenge. Students choose a sustainability challenge/goal to study and evaluate how Geospatial AI has/could be used to address it (2,500 words). |
Formative Assessments
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Essay | 2 | M | Submission of contents page for assessed essay. |
Assessment Rationale And Relationship
The geospatial AI implementation computer assessment extends experience and understanding gained during computer practicals applied to a real-world sustainability challenge. The Literature critique/review of geospatial AI for a sustainability challenge allow students to develop a deeper understanding of how state of the art geospatial AI has been applied to address sustainability challenges and also will allow students to enhance their broader research skills.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CEG8733's Timetable