Undergraduate - UnitAZA3259 - Geographical information systems (GIS): planning and decision making

This unit entry is for students who completed this unit in 2013 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

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6 points, SCA Band 2, 0.125 EFTSL

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Level	Undergraduate
Faculty	Faculty of Arts
Organisational Unit	School of Social Science, South Africa
Offered	South Africa Second semester 2013 (Day)
Coordinator(s)	Mr Marshall Mdoka

Synopsis

The unit introduces GIS (Geographical Information Systems) and discusses basic principles, techniques and applications of GIS in the field of geography and environmental science. It examines and reviews specific applications where GIS is a useful tool. Subjects covered include basics of GIS, spatial data sources, spatial data quality, spatial data analysis and decision support systems. It also includes the basic principles of remote sensing and the use of satellite imagery. Cases studies and hands-on practices allow students to gain experience in the use of GIS.

Outcomes

At the end of the unit students should be able to:

Demonstrate the utility of digital spatial data handling for mapping and analysis from digital data, referring to themes in environmental science;
Demonstrate a clear understanding of the key concepts concerning the application of GIS to environmental problems
Explain how value can be added to the data in any information management system with geocodes, by implementing digital spatial data analysis;
Be able to assess the nature of digital spatial data, offer tests for validation and descriptions of the relative value of data sets compared with (raw) data supplied by custodians;
Demonstrate a high level of skills in the use of GIS software (Quantum GIS, Ilwis, ArcGIS) to solve environmental problems;
Develop your own environmental applications of GIS ;
Explain how digital spatial data handling is different from other digital data handling challenges, and how the theory on which it is based is central to spatial data handling for environmental science.