SPA501 Advanced GIS Applications and Modelling (8)


This subject challenges the student to utilise their entire learned spatial toolbox on a real-world modelling problem. The subject teaches students how to turn tools into models, and introduces the idea of developing applications from those models. Students will employ vector, raster and 3-dimensional analysis to provide creative solutions to a planning problem. Tasks will be tackled in a structured manner, using flowcharting, project management, background research and formal reporting. Uncertainty management is also addressed. As such it is a capstone subject (i.e. a subject that integrates your prior learning in other subjects) for GIS and remote sensing. The subject has no residential school. Students completing this subject have the ability to apply advanced knowledge and skills in GIS and remote sensing to lead a spatial analysis project through its entire life cycle, from concept to solution and final report.

+ Subject Availability Modes and Location

Session 2
DistanceAlbury-Wodonga Campus
Continuing students should consult the SAL for current offering details: SPA501
Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject information

Duration Grading System School:
One session.HD/FLSchool of Environmental Sciences

Assumed Knowledge

Students enrolling in this subject are assumed to have successfully completed GIS studies of at least third year undergraduate level or equivalent.

Enrolment restrictions

Incompatible subject(s)

Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to apply their advanced knowledge and skills in GIS and remote sensing to lead a spatial analysis project through its entire life cycle, from concept to solution and final report
  • have the ability to plan the steps required to turn a spatial analysis solution into a deliverable such as an application or plug-in
  • be able to apply critical thinking to use and intelligently convert information between, vector, raster, and 3D modelling
  • have the ability to incorporate uncertainty and error into confidence metrics for model output
  • have professional skills such as the appropriate use of published research in specialist application areas to develop models using mathematics and spatial analysis
  • have demonstrated the application of knowledge (includes the understanding of recent developements in the discipline) and skills to plan and execute a substantial research based capstone experience and/or piece of scholarship


The subject will cover the following topics:
  • Project management
  • Process flowcharting and model design
  • Report and proposal writing
  • Types of spatial models
  • Model/software integration
  • Practical uncertainty management
  • Three-dimensional, raster, vector modelling tools


The information contained in the 2016 CSU Handbook was accurate at the date of publication: 06 September 2016. The University reserves the right to vary the information at any time without notice.