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No offerings have been identified for this subject in 2016

SPA320 Current Issues in GIS (8)

Abstract

This subject covers a wide range of current, new and interesting topics closely related to GIS. Over time the content areas will change, however for the present this subject deals with the scientific foundations for the handling of geographic information as well as an analysis of the computational models underlying spatial information management.

+ Subject Availability Modes and Location

Continuing students should consult the SAL for current offering details prior to contacting their course coordinator: SPA320
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 sessionHD/FLSchool of Environmental Sciences

Assumed Knowledge

SPA200 or SPA220

Learning Outcomes

Upon successful completion of this subject, students should:
Have developed an appreciation of the scientific foundation for the handling and analysis of computer based geographically referenced information;
Have been encouraged to learn of the wide range of computational models underlying spatial information management;
Have considered the main themes underlying geographic information system processing central to the development of GIS; including database issues, spatial analysis, spatial decision making, visualisation and applications.

Syllabus

The subject will cover the following topics:
The curriculum content will change as the subject matter changes. For the present the curriculum is listed below. It is expected that each offering of this subject will reflect current emphases in the development of GIS integration of database systems and computational support for high level modelling of spatio temporal phenomena. Automatic GIS data capture and conversion; Computer assisted tools for cartographic data capture; Automatic generalisation systems for large scale topographic maps; GIS modelling incorporating remotely sensed data; Models and algorithms for GIS; The temporal dimension in GIS; The place of massively parallel computing in GIS; Exploratory data analysis in GIS; Visualising spatial associations;. Probable and fuzzy models in GIS; Error simulation in GIS using neural networks; Spatial structure of error in some GIS data; Modelling environmental systems with GIS; Expert systems and GIS; Output design issues; Real time data capture.

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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.