Applying geographic information systems to delineate residential suburbs and summarise data based on individual parcel attributes
CITATION: Sinske, S. A. & Jacobs, H. E. 2013. Applying geographic information systems to delineate residential suburbs and summarise data based on individual parcel attributes. South African Journal of Information Management, 15(1), Art.#538, doi:10.4102/sajim.v15i1.538.
The original publication is available at http://www.sajim.co.za
Background: Information aggregation to suburb level is of interest to engineers and urban planners. Readily available suburb boundaries do not always correspond to the suburb names recorded for individual properties in different data bases and unwanted errors are inherent. This mismatch of suburb names at different spatial scales poses a particular problem to analysts. As part of a parallel research project into the development of a robust guideline for suburb-based water demand analyses it was necessary to evaluate a large number of suburbs in terms of various attributes, one of which was the total suburb area. Objectives: Suburb boundaries were needed to assess the total suburb area. The objective of this research was to develop a novel geographic information system (GIS) application to delineate suburbs with boundaries corresponding to information contained in another data base comprising individual property records. The suburb boundaries derived in this manner may not relate to municipal boundaries, or sociopolitical boundaries, nor do they have to. The fundamentally correct suburb boundary would be the one encompassing what is perceived to be the suburb based on the suburb name in a particular data base that also contains other interesting attributes, such as water use, of individual properties. Method: The ArcGIS environment was used to delineate suburbs by means of triangulated irregular network (TIN) modelling. Boundaries for suburbs with predominantly residential land use were created that included all residential properties according to the suburb name field as recorded in the treasury system. Other vacant areas were also included so as to obtain the total suburb area. The methodology was developed to assist research in the field of potable water services, but the method presented could be applied to other services that require management of information at suburb level. Results: This article illustrates how a tedious task of suburb delineation could be automated in the GIS environment. The tool prevents subjective results that would be prone to error. The automated procedure described could effectively delineate a large number of predominantly residential suburbs in a relatively short time span and produce repeatable results. A reasonable outline could only be obtained if a sufficient number of parcels in the area contained the same suburb name. Functionality was added to the tool so that a limit could be set for this purpose. The default was that if more than 20% of the records were erroneous it was considered impractical to delineate a suburb. The derived suburb boundaries correspond to useful information in other data bases and would thus enable more effective management of the information. Conclusion: A novel procedure to delineate suburb boundaries in the GIS environment was illustrated in this article. Information at two different spatial scales, namely, individual consumers and suburbs, could be married for the purpose of further research into suburban attributes. The tool was applied as part of a parallel research project to delineate 468 suburbs in this manner, results of which were submitted for publication elsewhere.
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