Development of census output areas with AZTool in South Africa
Development of census output areas with AZTool in South Africa
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DOI：
10.17159/sajs.2016/20150010
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发表时间：
2016-01-01
影响因子：
2.4
通讯作者：
Ahmed, Fethi
中科院分区：
文献类型：
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作者：
Mokhele, Tholang;Mutanga, Onisimo;Ahmed, Fethi
在世界许多国家，特别是发展中国家，使用单一地理单位收集和传播普查数据的做法很常见。在南非，这一方法带来了一些挑战，因为为便利数据收集而设计的称为查点区的小地理单位与为协助数据分析和解释而设计的单位有很大不同。我们的目标是使用自动化区域设计工具（AZTool）程序创建优化的人口普查输出区域，使用2001年人口普查查点区域作为南非两个省农村和城市环境在不同空间层面的构建块。结果一致且稳定。在所有地理级别或区域，无论是城市还是农村，对于新创建的优化产出地区，500人的保密限制的主要标准都得到了遵守。就第二项标准而言，农村和城市地区在较低地理水平上的地区内相关值较低，表明较高地理水平产生的产出地区比较低地理水平或区域更同质。我们得到的两个省的区域内相关性为0.62相结合表明，所选的同质性变量是良好的社会同质性指标，在南非创建优化的输出区域。我们的结论是，AZTool软件可用于有效和客观地创建南非数据的优化输出区域。应探讨对南非新设立的产出领域与现有产出领域进行比较的进一步研究。
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.