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Development of census output areas with AZTool in South Africa
by
Mokhele, Tholang
, Ahmed, Fethi
, Mutanga, Onisimo
in
Algorithms
/ Asthma
/ Automation
/ Boundaries
/ Census
/ Censuses
/ Colleges & universities
/ Confidentiality
/ Data collection
/ Design
/ Developing countries
/ Homogeneity
/ Households
/ Information management
/ LDCs
/ Population
/ Population research
/ Software
/ Urban areas
2016
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Development of census output areas with AZTool in South Africa
by
Mokhele, Tholang
, Ahmed, Fethi
, Mutanga, Onisimo
in
Algorithms
/ Asthma
/ Automation
/ Boundaries
/ Census
/ Censuses
/ Colleges & universities
/ Confidentiality
/ Data collection
/ Design
/ Developing countries
/ Homogeneity
/ Households
/ Information management
/ LDCs
/ Population
/ Population research
/ Software
/ Urban areas
2016
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Do you wish to request the book?
Development of census output areas with AZTool in South Africa
by
Mokhele, Tholang
, Ahmed, Fethi
, Mutanga, Onisimo
in
Algorithms
/ Asthma
/ Automation
/ Boundaries
/ Census
/ Censuses
/ Colleges & universities
/ Confidentiality
/ Data collection
/ Design
/ Developing countries
/ Homogeneity
/ Households
/ Information management
/ LDCs
/ Population
/ Population research
/ Software
/ Urban areas
2016
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Development of census output areas with AZTool in South Africa
Journal Article
Development of census output areas with AZTool in South Africa
2016
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Overview
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 the 2001 census enumeration areas as building blocks at various spatial levels, for both rural and urban settings in two South African provinces. The results were consistent and stable. The primary criterion of the confidentiality limit of 500 people was respected at all geographical levels or regions, in both urban and rural settings, for newly created optimised output areas. For the second criterion, lower intra-area correlation values at lower geographical levels for both rural and urban areas showed that higher geographical levels produced more homogeneous output areas than did lower geographical levels or regions. Our obtained intra-area correlation of 0.62 for the two provinces combined indicated that the selected homogeneity variables were good indicators of social homogeneity for creating optimised output areas in South Africa. We conclude that the AZTool software can be used to effectively and objectively create optimised output areas for South African data. Further research on the comparison of the newly created output areas with existing output areas in South Africa should be explored.
Publisher
African Online Scientific Information Systems (Pty) Ltd t/a AOSIS,Academy of Science of South Africa
Subject
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