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GEOM7002-Spatial Analysis &Modelling
SemesterSem 2 2023| Administrative Campus:St Lucia | Mode: External Printed:24 July 2024,06:13 pm
This printed course profileis valid at the date and time specifed above.The course profile may be subject to change during the semester-the online version is the authoritative version.
1.General Course Information
1.1 Course Details Course Code:GEOM7002
Course Title:Spatial Analyss &Modelling
Coordinating Unit:School of theEnvironment Semester:Semester 2,2023
Mode:External
Level:Postgraduate Coursework
Delivery Location:External (administered at St Lucia) Number of Units:2
Pre-Requisites:GEOM7005 or GEOM7006
Incompatible:GEOM3002 or GEOS3300 or GEOM7301
Course Description: Thiscourse develops skill and a deeper understanding to conduct detaild analysisin geographicalinformation systems (GIS)
using basic statistical methodsand spatial analysis.Students learn to analyse spatial patterns and relate these to processes inthe natural
environment andhuman spatial behaviour.Students also gain knowledge and skils to develop geoprocessing modelsand for makingdecisions related to planning and management.
Assumed Background:Students are expected to have completed aGIS course(GEOM2001 or GEOM2002)or demonstrated equivalentlearning and experience.
1.2 Course Introduction
This course is designed to build on and extend the knowledgeand skils thatstudents acquired in a GIS introductory course or through their experience using GIs elsewhere.It focus 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 toaddress common problems concerning the physical and human
geographical processes,patterns and relationships.Students work onexample problems inpracticals using GIS.Assessment is based upon 1)one project which consists of a project proposal and a report,2)oneusing StoryMap to communicating GIS data and analysis to non-expert audiences; and 3)a final exam
Course Changes in Response to Previous Student Feedback
In response to the technological development in thefeld we are migratingfrom desktop GIS(ArcGIS)to ArcGIS Proin the practicalsin this course.
1.3 Course Staff
Course Coordinator: Professor Yan Liu
1.4 Timetable
Timetables are availableon the UQ Public Timetable.(https://my.uq.edu.au/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.
2.1 Course Aims
This course aims to equip students with:
1) advanced knowledge and skills in spatial analysisand modelling using GIS;and
2) applied spatial skills to use GIS to address geographical,environmental and planning problems in the real world.
4.Teaching &Learning Activities
4.1 Learning Activities
Recording of Lectures:Please be aware that teachingat UQ may be recorded for the benefit of student learning.If you would prefer not tobe
captured either by voice or image,please advise your course coordinator before class so accommodations can be made.Forfurtherinformation see PPL3.20.06 RecordingofTeaching at UQ(0).
|
Date |
Activity |
Learning Objectivěs |
|
24Jul23-28 Ju|23 |
Introduction to spatial analysis and modelling(Lecture):Course overview,spatial analysis as a process; modelbuilder No practical this week Readings/Ref:Grekousis(Chapter 1);de Smith et al (Chapter 3);Blackboard |
1,2,3,4,5,6,7 |
|
31 Jul23-04 Aug 23 |
Measuring spatial connectivity I(Lecture):Network Analysis Prac 1Land Suitability Modelling using ModelBuilder in ArcGIS Pro Readings/Ref:Grekousis (Chapter 7);de Smith et al (Chapter 7);Blackboard |
3,4,5,7 |
|
07 Aug 23-11 Aug 23 |
Measuring spatial connectivity ll(Lecture):Accessibility modelling Prao 2 Spatial Network Analysis using ArcGIS Pro Readings/Ref:Grekousis(Chapter 2);de Smith et al (Chapter 5.1;5.2);Blackboard |
1,2,4.5,7 |
|
14 Aug 23-18Aug 23 |
SpatialAnalysis of Point Data l (Lecture):Describing spatial distributions Prac 3 Spatal accessibiity modelling Readings/Ref:Grekousis (Chapter 3);Blackboard |
2,3,4,5 |
|
21 Aug 23-25 Aug 23 |
Spatial Analysis of Point Data ll(Lecture):Analysing spatial patterns No prao this week,work on your Assignment 1 Readings/Ref:Grekousis (Chapter 3);Blackboard |
2,3,4,5 |
|
28 Aug 23-01 Sep 23 |
SpatialAutocorrelation (Lecture):Global and local spatial autocorrelation techniques,hot spot analysis Prac 4 Measuring spatial distributions and patterns Readings/Ref:Grekousis (Chapter 4);de Smith et al (Chapter 5.5);Blackboard |
2,3,4.5 |
|
04 Sep 23-08 Sep 23 |
Modelling Geographical Relationships(Lecture):Regression analysis indicator mapping;Geographically Weighted Regression Prac 5 Modelling geographical relationships Readings/Ref:Grekousis (Chapter 6);de Smith et al (Chapter 5.6);Blackboard |
3,4,5,7 |
|
11 Sep 23-15 Sep 23 |
Spatio-Temporal Analysis (Lecture):Measuring change over time Prac6 Spatial change analysis Readings/Ref:de Smith et al;Blackboard |
2,3,5,7 |
|
18 Sep 23-22 Sep 23 |
Teaching free week (Independent Study):No lecture and prac,work on your Assignment 2 Readings/Ref:Grekousis (Chapter 1-4,6);Blackboard |
1,3,4,5,7 |
|
020ct 23-060ct 23 |
GIS communication (Lecture):Prac 7 Using StoryMaps for effective GIS communication Readings/Ref:Blackboard |
1,5,7 |
|
09 Oct 23-130ct 23 |
Spatial modelling and geocomputation(Lecture):Concepts and selected methods Work on your StoryMap Project during practical time. Readings/Ref:de Smith et al(Chapter 8);Blackboard |
1,4,5,7 |
|
160ct 23-200ct 23 |
Big data analytics (Lecture):Selected methods and applications Work on your StoryMap Project during practical time. Readings/Ref:de Smith et al (Chapter 9);Blackboard |
2,4,5,6,7 |
|
230ct 23-270ct 23 |
Summary of course and preparation for exam(Revision) Readings/Ref:Grekousis;de Smith et al;Blackboard |
1,2,3,4,5,6,7 |
4.2 Other Teaching and Learning Activities Information
Lectures,Lab based practicals,project based learning using GIS
5.Assessment
5.1 Assessment Summary
This is a summary of the assessment in the course.For detailed information on each assessment,see 5.5 AssessmentDetail below.
coVID-19 IMPACTS:UQ will make every effort to teach and assessas outlined inthis course profile.However the ongoing impacts of COVID-19,
including changes to Government heathrestictionsthat may be implemented duringthe Semester could resultin changes tothis course,incuding assessment.We continueto strive to ensure the learning actvites for this course remain accessible to students as far as is practicable,so that the learning objectives can bemet.For further information and ongoing updates see https://about.uq.edu.au/coronavirus/students.
|
Assessment Task |
Due Date |
Weighting |
Learning Objectives |
|
Assignment 1 Spatial analysis and modelling l |
29 Aug2314:00 |
25% |
1,2,4,5 |
|
Assignment 2 Spatial analysis and modelling Ⅱ |
03 Oct 2314:00 |
25% |
1,2,3,5 |
|
Presentation Slides StoryMapPresentation |
240ct 2314:00 |
20% |
2.5,7 |
|
Exam-during Exam Period(Centra) Final |
Examination Period |
30% |
1,2,3,4,5,6,7 |
5.2 Course Grading
Example criteria for each of the grades can be found in PPL3.10.02 Assessment Procedures(https//pplapp.uq.edu.au/content/3.10.02- assessment#Procedures)-section 7 Appendix.
Grade X:No assessable work received.
Grade 1,Low Fail:Absence of evidence of achievement of course learning outcomes: 1-24.4%
Grade 2,Fail:Minimal evidence of achievement of course learning outcomes: 24.5-44.4%
Grade 3,Marginal Fail:Demonstrated evidence of developing achievement of course learning outcomes: 44.5-49.4%
To receiveapassing gradestudent will need to obtain aminimum of 50%in thefinalexam.
Grade 4,Pass:Demonstrated evidence of functional achievement of course learning outcomes: 49.5-64.4%
To receivea passing grade student willneed to obtain a minimum of 50%in the finalexam
Grade 5,Credit:Demonstrated evidence of proficient achievement of course learning outcomes: 64.5-74.4%
To receiveapassing gradestudent will need to obtain aminimum of 50%in thefinalexam.
Grade 6,Distinction:Demonstrated evidence of advancedachievement of courselearning outcomes: 74.5-84.4%
To receiveapassing gradestudent will need to obtain aminimum of 50%in the finalexam.
Grade 7,High Distinction:Demonstrated evidence of exceptional achievement of course learning outcomes: 84.5%+
To receiveapassing gradestudent will need to obtain aminimum of 50%in thefinal exam.
Other Requirements &Comments:
Thefinalgrade for the course will typically fallwithin the above mentioned ranges.
Assessment Hurdle-To receive a passing gradestudent will need to obtain a minimumof 50%in the finalexam