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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLII-4-W8-85-2018</article-id>
<title-group>
<article-title>SPATIAL STATISTICAL ANALYSES TO ASSESS THE SPATIAL EXTENT AND CONCENTRATION OF MULTIDIMENSIONAL POVERTY IN GAUTENG USING THE SOUTH AFRICAN MULTIDIMENSIONAL POVERTY INDEX</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Katumba</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Gauteng City-Region Observatory (GCRO), Johannesburg, South Africa</addr-line>
</aff>
<pub-date pub-type="epub">
<day>11</day>
<month>07</month>
<year>2018</year>
</pub-date>
<volume>XLII-4/W8</volume>
<fpage>85</fpage>
<lpage>92</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2018 S. Katumba</copyright-statement>
<copyright-year>2018</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-4-W8/85/2018/isprs-archives-XLII-4-W8-85-2018.html">This article is available from https://isprs-archives.copernicus.org/articles/XLII-4-W8/85/2018/isprs-archives-XLII-4-W8-85-2018.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-4-W8/85/2018/isprs-archives-XLII-4-W8-85-2018.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-4-W8/85/2018/isprs-archives-XLII-4-W8-85-2018.pdf</self-uri>
<abstract>
<p>Assessment of poverty has generally been carried out using “money-metric” measures. But since poverty is multidimensional, these measures fall short of generating a comprehensive picture of the poor. Contrastingly, multidimensional poverty analyses are capable of generating parameters that help in providing holistic understanding of poverty in its various forms. This study compares two indexes of multidimensional poverty computed from census data collected in 2001 and 2011 in Gauteng (South Africa) by performing a spatial autocorrelation analysis. The results reveal fine-grained detailed variations in the concentration of poverty across the Gauteng province. Overall, multidimensional poverty is concentrated at the periphery of the province while affluence is concentrated in the core urban areas. Pockets of grinding poverty can also be found in core areas juxtaposed with affluence. Such an analysis will lead to the formulation of spatially targeted policy interventions geared towards poverty alleviation.</p>
</abstract>
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