Volume XLII-4/W8 | Copyright
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W8, 85-92, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W8-85-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  11 Jul 2018

11 Jul 2018

SPATIAL STATISTICAL ANALYSES TO ASSESS THE SPATIAL EXTENT AND CONCENTRATION OF MULTIDIMENSIONAL POVERTY IN GAUTENG USING THE SOUTH AFRICAN MULTIDIMENSIONAL POVERTY INDEX

S. Katumba S. Katumba
  • Gauteng City-Region Observatory (GCRO), Johannesburg, South Africa

Keywords: Multidimensional Poverty, SAMPI, Spatial Autocorrelation, Global Moran’s I, LISA

Abstract. 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.

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