EAE5053 Advanced spatial analysis and modelling
Faculty of Science
EAE5053 Advanced spatial analysis and modelling is a level 5, 6-credit-point, postgraduate unit from the Faculty of Science, offered in 2027 in Semester 2 at Clayton. It has no prerequisites and unlocks 2 units.
- Credit points
- 6
- Offered in 2027
- Semester 2
- Clayton
- Assessment
- No exam
- 3 tasks
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Requisites
Before EAE5053
No prerequisites or corequisites.
After EAE5053
2 units list EAE5053 as a prerequisite or corequisite.
Overview
This unit aims to develop advanced knowledge and skills in spatial analysis and modelling within GIS. It covers spatial regression models, and the application of modern machine learning and deep learning algorithms to solve real-world geospatial problems . It also introduces methods and techniques for integrating advanced analysis and modelling tools with GIS or extending GIS functionality using the Python programming language to build new tools and custom GIS solutions. The unit will equip you with highly valued spatial analysis and modelling skills by the geospatial industry and research community.
Offerings in 2027
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Clayton | On campus |
Assessment
- Practical workDemonstration40%
- Theory quizzes.Quiz / Test30%
- Group projectWritten30%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Build a strong foundation in modern spatial analysis and modelling techniques;
- 2
Understand the assumptions and limitations of spatial analysis techniques;
- 3
Grasp skills in selecting appropriate spatial analysis and modelling techniques for a specific problem;
- 4
Gain practical experience in developing and applying a range of spatial analysis and modelling methods in a GIS;
- 5
Interpret, evaluate and communicate the results from spatial analysis and modelling.
Workload and teaching
- Workshops24 hours
- Practical activities24 hours
- Teaching approachActive learning
- 1-hour lecture videos;
- 2-hour workshops;
- 3-hour practicals/projects and
- 6-hour independent study per week
The unit is composed of online pre-recorded lecture videos, recommended readings, two-hour workshops, and three-hour computer-based practicals/projects on a weekly basis. The workshops are designed to engage you in learning through (1) reviewing and discussing key concepts introduced in the online lecture videos, or (2) presenting case studies and collectively conducting spatial analysis and modelling to solve selected problems. The workshops and lecture videos are to explain the concepts and principles and demonstrate how they are applied to address the real-world problems. Practicals help develop skills and competency. The projects are designed to help develop the ability to apply the learnt knowledge and skills to solve complex problems.
Learning resources
Recommended resources
Zhu, X. (2024) Geographical Information Systems: A Practical Approach, second edition. Routledge, UK.
Stein A., van der Meer F., and Gorte B. (1999) Spatial Statistics for Remote Sensing. Springer, Netherlands.
Fotheringham, A., Brundson, C, and M. Charlton (2002) Geographically weighted regression: the analysis of spatially varying relationships, John Wiley and Sons, 2002.
Chivite, I., Giner, N., Carpenter C. (2026) Exploring GeoAI: Tools and Workflows. ESRI
Chivite, I., Giner, N., Artz, M. (2025) GeoAI: Artificial Intelligence in GIS. ESRI
Other readings to be advised during the course.
Technology resources
Software: ArcGIS Pro (campus licensed).
Contacts
- Chief Examiners
- Dr Angela Afonso Rodrigues
Common questions
What are the prerequisites for EAE5053?
EAE5053 has no prerequisites.
What can I take after EAE5053?
EAE5053 is a prerequisite or corequisite for 2 units, including EAE5015 and EAE5018.
When is EAE5053 offered?
In 2027, EAE5053 runs in Semester 2 at Clayton.
Does EAE5053 have an exam?
No. EAE5053 has 3 assessment tasks and no exam.