2016
DOI: 10.17159/sajs.2016/20150010
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Development of census output areas with AZTool in South Africa

Abstract: The use of a single geographical unit to both collect and disseminate census data is common in many countries across the world, especially in developing countries. In South Africa this approach poses some challenges, as the design of small geographical units called enumeration areas to facilitate data collection differs considerably from the design of units that aid data analysis and interpretation. We aimed to create optimised census output areas using the Automated Zone-design Tool (AZTool) program, using th… Show more

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Cited by 8 publications
(19 citation statements)
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“…Two provinces were selected for this study; Free State and Gauteng, which were representatives of rural and urban areas, respectively (Mokhele et al, 2016). In each province, different spatial or geography levels such as district, municipality and mainplace were selected for subsequent analysis.…”
Section: Methodsmentioning
confidence: 99%
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“…Two provinces were selected for this study; Free State and Gauteng, which were representatives of rural and urban areas, respectively (Mokhele et al, 2016). In each province, different spatial or geography levels such as district, municipality and mainplace were selected for subsequent analysis.…”
Section: Methodsmentioning
confidence: 99%
“…The Automated Zone-design Tool program algorithms usually take input building blocks and iteratively aggregate them into larger output areas from an initial random aggregation, by checking the effect of swapping individual building blocks between output areas based on criteria set by the user (Openshaw, 1977;Mokhele et al, 2016). All the AZTool output areas were generated using different building blocks with a population threshold of 500 (as practised by Stats SA) and a population target of 1000 to ensure confidentiality limit (Verhoef and Grobbelaar, 2005;Mokhele et al, 2016). Confidentiality limit is minimum population that is used for the dissemination of census data in order to avoid personal information disclosure.…”
Section: Methodsmentioning
confidence: 99%
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