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Course profile

Spatial Analysis & Modelling (GEOM3002)

Study period
Sem 2 2025
Location
St Lucia
Attendance mode
In Person

Course overview

Study period
Semester 2, 2025 (28/07/2025 - 22/11/2025)
Study level
Undergraduate
Location
St Lucia
Attendance mode
In Person
Units
2
Administrative campus
St Lucia
Coordinating unit
The Environment School

This course develops skills and a deeper understanding to conduct detailed analysis in geographical information systems (GIS) using basic statistical methods and spatial analysis. Students learn to analyse spatial patterns and relate these to processes in the natural environment and human spatial behaviour. Students also gain knowledge and skills to develop geoprocessing models and for making decisions related to planning and management.

This course is designed to build on and extend the knowledge and skills that students acquired in a GIS introductory course or through their experience using GIS elsewhere. It focuses on various spatial analysis and modelling techniques and geo-visualisation for applications relating to the natural and built environments and human activities.

Lectures present concepts and give examples for analysing spatial data to address common problems concerning the physical and human geographical processes, patterns and relationships. Students work on example problems in practicals using GIS.

Course requirements

Assumed background

Students are expected to have completed a GIS course (GEOM2001 or GEOM2002) or demonstrated equivalent learning and experience.

Prerequisites

You'll need to complete the following courses before enrolling in this one:

GEOM2001 or 2002

Incompatible

You can't enrol in this course if you've already completed the following:

GEOM7002 or GEOS3300 or GEOS7301

Course contact

Course staff

Lecturer

Timetable

The timetable for this course is available on the UQ Public Timetable.

Additional timetable information

The course uses Blackboard. You may find up-to-date schedules and due dates in the Blackboard menus for Lectures and Assessment, and from announcements.

Aims and outcomes

This course aims to equip students with: 1)ᅠᅠᅠᅠᅠ advanced knowledge and skills in spatial analysis and modelling using GIS; and 2)ᅠᅠᅠᅠᅠ applied spatial skills to use GIS to address geographical, environmental and planning problems in the real world.

Learning outcomes

After successfully completing this course you should be able to:

LO1.

Understand conceptual models involving spatial data analysis

LO2.

Design geoprocessing models to solve application problems

LO3.

Apply statistical techniques to explore spatial data patterns and relationships

LO4.

Perform spatial analysis and modelling to data along networks

LO5.

Choose and apply appropriate spatial analysis methods to solve geographical problems

LO6.

Understand and appreciate the emerging sources of big data and geocomputation techniques

LO7.

Interpret and effectively communicate spatial data and analytical output to non-expert audiences

Assessment

Assessment summary

Category Assessment task Weight Due date
Tutorial/ Problem Set Assignment 1: Accessibility modelling 25%

10/09/2025 2:00 pm

Tutorial/ Problem Set Assignment 2: Spatial statistical analysis 25%

8/10/2025 2:00 pm

Presentation, Project Assignment 3: StoryMap presentation 20%

29/10/2025 2:00 pm

Examination End of Semester Exam
  • Hurdle
  • Identity Verified
30%

End of Semester Exam Period

8/11/2025 - 22/11/2025

A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.

Assessment details

Assignment 1: Accessibility modelling

Mode
Written
Category
Tutorial/ Problem Set
Weight
25%
Due date

10/09/2025 2:00 pm

Task description

This assignment 1 is based on lectures and practicals you learnt in the first FOUR weeks. The questions will be provided at the end of Practicals 1-3. You need to submit this assignment through Turnitin by the due date. 

Submission guidelines

Online submission by Turnitin only by the due date and time. No hard copy or assignment cover sheets are required. Submission via email is not accepted. You should also retain an identical electronic copy of the work submitted.

Deferral or extension

You may be able to apply for an extension.

See the Additional assessment information section below for information relating to extension applications.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (the assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date.

For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period). 

Assignment 2: Spatial statistical analysis

Mode
Written
Category
Tutorial/ Problem Set
Weight
25%
Due date

8/10/2025 2:00 pm

Task description

This assignment 2 is based mainly on the lectures and practicals you learnt in Weeks 5-8. The questions will be provided at the end of Practicals 4-6. You need to submit this assignment through Turnitin by the due date.

Submission guidelines

Online submission by Turnitin only by the due date and time. No hard copy or assignment cover sheets are required. Submission via email is not accepted. You should also retain an identical electronic copy of the work submitted.

Deferral or extension

You may be able to apply for an extension.

See the Additional assessment information section below for information relating to extension applications.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (the assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date.

For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period). 

Assignment 3: StoryMap presentation

Mode
Product/ Artefact/ Multimedia, Written
Category
Presentation, Project
Weight
20%
Due date

29/10/2025 2:00 pm

Task description

For this assignment you will develop an online StoryMap following best practice for GIS communication. Details on this assignment requirement will be provided via BB during the course.

Submission guidelines

Online submission by Turnitin only by the due date and time. No hard copy or assignment cover sheets are required. Submission via email is not accepted. You should also retain an identical electronic copy of the work submitted.

Deferral or extension

You may be able to apply for an extension.

See the Additional assessment information section below for information relating to extension applications.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (the assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date.

For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period). 

End of Semester Exam

  • Hurdle
  • Identity Verified
Mode
Written
Category
Examination
Weight
30%
Due date

End of Semester Exam Period

8/11/2025 - 22/11/2025

Task description

This End of Semester exam consists of multiple choice questions, as well as short answer and problem-solving questions related to spatial data models and analysis. The questions are based on lecture and reading contents and its applications throughout the semester. This assessment task evaluates students' abilities, skills and knowledge without the aid of Artificial Intelligence (AI).

Hurdle requirements

See ADDITIONAL COURSE GRADING INFORMATION for the hurdle relating to this assessment item.

Exam details

Planning time 10 minutes
Duration 90 minutes
Calculator options

(In person) Casio FX82 series only or UQ approved and labelled calculator

Open/closed book Closed book examination - specified written materials permitted
Materials

One A4 sheet of handwritten or typed notes, double sided, is permitted

One unmarked bilingual dictionary is permitted

Exam platform Paper based
Invigilation

Invigilated in person

Submission guidelines

Deferral or extension

You may be able to defer this exam.

Course grading

Full criteria for each grade is available in the Assessment Procedure.

Grade Description
1 (Low Fail)

Absence of evidence of achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 0%

2 (Fail)

Minimal evidence of achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 30%

3 (Marginal Fail)

Demonstrated evidence of developing achievement of course learning outcomes

Course grade description: The minimum percentage required for this grade is: 45%

4 (Pass)

Demonstrated evidence of functional achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 50%

5 (Credit)

Demonstrated evidence of proficient achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 65%

6 (Distinction)

Demonstrated evidence of advanced achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 75%

7 (High Distinction)

Demonstrated evidence of exceptional achievement of course learning outcomes.

Course grade description: The minimum percentage required for this grade is: 85%

Additional course grading information

Assessment Hurdle

In order to pass this course, you must meet the following requirements (if you do not meet these requirements, the maximum grade you will receive will be a 3):

You must obtain 45% or more in the End of Semester Exam.

Supplementary assessment

Supplementary assessment is available for this course.

Should you fail a course with a grade of 3, you may be eligible for supplementary assessment. Refer to the UQ website for information on supplementary assessment and how to apply.

Supplementary assessment provides an additional opportunity to demonstrate you have achieved all the required learning outcomes for a course.

If you apply and are granted supplementary assessment, the type of supplementary assessment set will consider which learning outcome(s) have not been met.

Supplementary assessment can take any form (such as a written report, oral presentation, examination or other appropriate assessment) and may test specific learning outcomes tailored to the individual student, or all learning outcomes.

To receive a passing grade of 3S4, you must obtain a mark of 50% or more on the supplementary assessment.

Additional assessment information

*** All assessments in this course are individual work. This includes all data collection, analysis, mapping and writing must be your own original work ***


Applications for Extensions to Assessment Due Dates


Use of Artificial Intelligence (AI) and Machine Translation (MT)

Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance.

A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.

Learning resources

You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.

Library resources

Library resources are available on the UQ Library website.

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

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Learning period Activity type Topic
Week 1

(28 Jul - 03 Aug)

Lecture

Introduction to spatial analysis and modelling: Spatial analysis as a process and course overview

No practical this week

Week 2

(04 Aug - 10 Aug)

Lecture

Measuring Spatial Connectivity I: Network Analysis

Prac 1 Land suitability modelling using ModelBuilder in ArcGIS Pro

Week 3

(11 Aug - 17 Aug)

General contact hours

Teaching free week

No lecture (Public holiday on Wednesday 13/08)

No practical this week

Week 4

(18 Aug - 24 Aug)

Lecture

Measuring Spatial Connectivity II: Accessibility modelling

Prac 2 Spatial Network Analysis using ArcGIS Pro

Week 5

(25 Aug - 31 Aug)

Lecture

Spatial Analysis of Point Data I: Describing spatial distributions

Prac 3 Spatial accessibility modelling using ArcGIS pro

Week 6

(01 Sep - 07 Sep)

Lecture

Spatial Analysis of Point Data II: Analysing spatial patterns

No practical this week; work on your Assignment 1

Week 7

(08 Sep - 14 Sep)

Lecture

Spatial Autocorrelation: Global and local spatial autocorrelation techniques

Prac 4 Measuring spatial distributions and patterns

Week 8

(15 Sep - 21 Sep)

Lecture

Modelling Geographical Relationships: Regression analysis; indicator mapping; Geographically Weighted Regression

Prac 5 Modelling geographical relationships

Week 9

(22 Sep - 28 Sep)

Lecture

Spatio-Temporal Analysis: Measuring change over time

Prac 6 Spatial change analysis

Week 10

(06 Oct - 12 Oct)

Lecture

GIS communication

Prac 7 Using StoryMaps for effective GIS communication

Week 11

(13 Oct - 19 Oct)

Lecture

Geo-computation and Big data analytics: Selected methods and applications

Work on your StoryMap Project

Week 12

(20 Oct - 26 Oct)

Lecture

GIS beyond University: current trend in industry and the future

(Guest Lecture from an ESRI expert)

Work on your StoryMap Project

Week 13

(27 Oct - 02 Nov)

Lecture

Summary of course and preparation for exam

Course revision

Policies and procedures

University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.