SPA120 Introduction to Spatial Analysis and Modelling (8)

This subject introduces the student to the range and complexity of data used with a GIS from a management perspective. Data input devices are considered along with the need for data exchange. Data modelling within the GIS and problems of scale, resolution and sampling are considered. Practical work emphasises the concepts of data analysis and modelling. It also introduces the student to a qualitative understanding of some aspects of spatial statistics. This subject forms a basis for further study in other modules.

No offerings have been identified for this subject in 2019.

Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System



One session


School of Environmental Sciences

Assumed Knowledge

Learning Outcomes

Upon successful completion of this subject, students should:
  • Appreciate the range and complexity of data used with a GIS;
  • Appreciate the variety and uses of externally and internally sourced data;
  • Become aware of the equipment and methods used to observe and collect spatial data including the need for data exchange;
  • Understand how data is stored in GIS, data modelling including problems of scale resolution and sampling;
  • Understand how the 'world' can be decomposed into a linked set of thematic, spatial and temporal domains and their representation in spatial databases;
  • Appreciate the differences between GIS and mapping software;
  • Have examined introductory concepts relating to the visualisation, exploration and modelling of spatial data.


This subject will cover the following topics:

List and describe data types and datasets used in GIS; Understand the need to integrate different and similar data types; Role of geocodes, tags and identifiers outlining their role in linking spatial and aspatial data; Identify, list and describe (including advantages and disadvantages) some of the spatial datasets that may be sourced externally from public or private organisations, as well as that which may be internally sourced; Discuss some of the issues associated with data exchange; List and describe some of the methods used to capture spatial data; List and describe the various ways data can be modelled and stored for GIS purposes, including the advantages and disadvantages of data structures used in GIS; Construct simple Entity-Relationship diagrams for use in GIS; Understand some of the problems relating to modelling of the 'real world' including that of scale, dimensionality of spatial objects; Use computer based techniques to examine in a qualitative manner some of the principles of spatial data analysis.


For further information about courses and subjects outlined in the CSU handbook please contact:

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The information contained in the CSU Handbook was accurate at the date of publication: May 2019. The University reserves the right to vary the information at any time without notice.