CEG3719 : Geospatial Data, Analytics and AI
- Offered for Year: 2024/25
- Available for Study Abroad and Exchange students, subject to proof of pre-requisite knowledge.
- Module Leader(s): Professor Stuart Barr
- Co-Module Leader: Dr Alistair Ford
- Lecturer: 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 1 Credit Value: | 10 |
| Semester 2 Credit Value: | 10 |
| ECTS Credits: | 10.0 |
| European Credit Transfer System | |
Aims
This module aims to develop students’ knowledge of the applied use of geospatial data engineering and analytics to address substantive engineering, environmental and social challenges. The module will explore how modern geospatial data handling, standards, ethics, analysis, simulation modelling and visualisation approaches can be applied help deliver many of the UN sustainable development goals, climate resilience, robust infrastructure systems and sustainable urban planning.
Outline Of Syllabus
The module syllabus will explore the open source approaches employed in applied geospatial data engineering including:
Open source geospatial data
Spatial data and metadata standards
FAIR geospatial data and software
Open source web stack
Spatial databases and data management
Spatial Data Infrastructures (SDIs)
Geospatial data portals and APIs
The data engineering skills and knowledge will be further developed via coverage of the modern analytics and simulation modelling approaches that are transforming the applied utilization of geospatial data within engineering and environmental applications, including:
Fundamental quantitative methods
Modifiable Aerial Unit Problem (MAUP) and Ecological Fallacy
Applied spatial statistics
Spatial and geographical regression analysis
Unsupervised geospatial machine learning
Applied supervised geospatial machine learning
Applied geospatial AI methods
Spatial interaction models
Cellular Automata (CA) and agent-based modelling
Applied geospatial network analysis
Geospatial visualization and decision support
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 1 | 2:00 | 2:00 | Completion of examination |
| Guided Independent Study | Assessment preparation and completion | 1 | 30:00 | 30:00 | N/A |
| Guided Independent Study | Assessment preparation and completion | 1 | 32:00 | 32:00 | Exam revision |
| Scheduled Learning And Teaching Activities | Lecture | 26 | 1:00 | 26:00 | N/A |
| Guided Independent Study | Assessment preparation and completion | 2 | 19:00 | 38:00 | Work for assesed practical |
| Guided Independent Study | Directed research and reading | 26 | 1:00 | 26:00 | Post lecture reading |
| Scheduled Learning And Teaching Activities | Practical | 12 | 3:00 | 36:00 | N/A |
| Scheduled Learning And Teaching Activities | Workshops | 2 | 1:00 | 2:00 | Project workshops; 1 in each semester |
| Scheduled Learning And Teaching Activities | Workshops | 8 | 1:00 | 8:00 | Applied case-study student seminars; 4 each semester |
| Total | 200:00 |
Jointly Taught With
| Code | Title |
|---|---|
| CEG8719 | Geospatial Data, Analytics and AI with Project |
Teaching Rationale And Relationship
Lectures are used to present the underlying theory and principles of the use of geospatial data engineering and analysis. Practical sessions will allow students to apply the theory in relation to real world applied environmental applications. Seminar workshops will expose students to cutting edge research and show how environmental applications routinely employ high-level geospatial data/analysis/modelling concepts. There will be a project workshop in each semester relating to assessment requirements.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Exams
| Description | Length | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|---|
| Written Examination | 120 | 2 | A | 50 | N/A |
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Computer assessment | 1 | M | 25 | Report - write up of computer practical, in order to evaluate technical skills. |
| Computer assessment | 2 | M | 25 | Report - write up of computer practical, in order to evaluate technical skills. |
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 |
|---|---|---|---|
| Oral Presentation | 1 | M | Semester 1 applied student seminars |
| Oral Presentation | 2 | M | Semester 2 applied student seminars |
Assessment Rationale And Relationship
The computer practical reports will assess the computational skills and understanding of students to implement geospatial open standards data acquisition, management and delivery, along with their ability to undertake advanced analysis and modelling for real-world applications. Progress in non-assessed practicals will be confirmed by formative assessments to be completed within the practical session. Workshop seminars will help reinforce student understanding of the module content and help develop student presentation skills. The exam will develop independent research and critical review skills and assess ability to synthesise and present information.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CEG3719's Timetable