EAE5068 Spatial data analysis
Faculty of Science
EAE5068 Spatial data analysis is a level 5, 6-credit-point, postgraduate unit from the Faculty of Science, offered in 2027 in Semester 1 at Clayton. It has no prerequisites.
- Credit points
- 6
- Offered in 2027
- Semester 1
- Clayton
- Assessment
- No exam
- 2 tasks
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Requisites
Before EAE5068
No prerequisites or corequisites besides the enrolment rules below.
After EAE5068
No unit lists EAE5068 as a prerequisite in the 2027 handbook.
Enrolment rules
COREQUISITE: Enrolment in the Master of Science or Master of Geographical Information Science and Technology.
PROHIBITION: EAE4068
Overview
This unit aims to teach the knowledge and skills for exploring the spatial patterns that result from social and physical processes on or near the Earth's surface. It examines the theories and methods of quantitative geography, including spatial data exploration, hypothetic testing and spatial predictive modelling, provides practical training in fundamental tools of spatial analysis in GIS, and develops skills in finding, understanding and applying appropriate spatial analysis tools, and correctly interpreting and presenting the results.
Offerings in 2027
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Clayton | On campus |
Assessment
- PracticalsDemonstration50%
- Project50%
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
To understand the concepts and nature of spatial data analysis.
- 2
To understand the geographical concepts of distance, adjacency and interaction and how fundamental they are in performing spatial data analysis.
- 3
To understand and apply different approaches to spatial data exploration.
- 4
To understand spatial statistics, assumptions and how they are used to explain spatial patterns and processes.
- 5
To demonstrate competency in the use of spatial data analysis tools.
- 6
To be able to interpret and communicate effectively the results of spatial data analysis.
- 7
To demonstrate the ability to plan, design and implement a spatial data analysis project.
Workload and teaching
- Workshops12 hours
- Practical activities24 hours
- Teaching approachActive learning
12 hours per week consisting of:
- One 1-hour workshop;
- One 2-hour practical and
- Nine hours of independent study per week
Contacts
- Chief Examiners
- Dr Xuan Zhu
- Unit Coordinators
- Dr Xuan Zhu
Common questions
What are the prerequisites for EAE5068?
EAE5068 has no prerequisites, but enrolment rules apply.
When is EAE5068 offered?
In 2027, EAE5068 runs in Semester 1 at Clayton.
Does EAE5068 have an exam?
No. EAE5068 has 2 assessment tasks and no exam.