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.
HD/FL
One session
School of Environmental Sciences
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.
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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.