Spatial statistical modeling
Since 2009, the Gauteng City-Region Observatory has bi-annually conducted Quality of Life (QoL) surveys. The five surveys (2009, 2011, 2013/14, 2015/16, 2017/18) present fascinating snapshots of the quality of life, socio-economic circumstances, attitudes to service delivery and other characteristics of the Gauteng City-Region (GCR). The fourth survey interviewed over 30 000 respondents and is one of the largest surveys of social attitudes undertaken in Gauteng. The data are geocoded at the point of interview, with ward-level representative data available for all the municipalities. The availability of individual geocoded interviews presents an opportunity for a detailed analysis at a fine-scale that is spatially-based. The GIS software utilised by GCRO, Esri Arcmap 10.3, contains a spatial statistics toolbox for analysing spatial distributions, patterns, processes, and relationships. According to Esri’s help file: “While there may be similarities between spatial and non-spatial (traditional) statistics in terms of concepts and objectives, spatial statistics are unique in that they were developed specifically for use with geographic data. Unlike traditional non-spatial statistical methods, they incorporate space (proximity, area, connectivity, and/or other spatial relationships) directly into their mathematics.”
After a variety of variables were modelled to examine (i) patterns and trends in dissatisfaction with government performance, this project has been expanded to also examine (ii) patterns and trends in racial-residential segregation, (iii) race-based inequality and related correlates, (iv) household debt and related correlates. Specific questions addressed in the above research projects are found in the respective projects pages.
Katumba, S. (2019). ‘Gauteng’s ward level racial diversity: 2018’, Map of the Month, February.
Hammann, C. & Cheruiyot, K. (2018) ‘Mapping Debt’, Map of the Month, November.
Cheruiyot, K., Katumba, S. & Wray, C. (Forthcoming). Spatial patterns and correlates of dissatisfaction with the performance of government in the Gauteng city-region. GCRO Data Brief.
Cheruiyot, K., Wray, C. & Katumba, S. (2015), ‘Satisfaction with local government performance’, Map of the month, April.
Cheruiyot, K. (2017). 'A geographical weighted regression approach to understanding dissatisfaction with government performance in the Gauteng City-Region', South Africa. 3rdBiannual Urban and Regional Science Conference, CRUISE, Department of Geography and Environmental Studies, Stellenbosch University on 5 July 2017.
Katumba, S. (2017). 'Exploring spatial change in multidimensional poverty in Gauteng: evidence of Quality of Life Survey data', South Africa. 3rd Biannual Urban and Regional Science Conference, CRUISE, Department of Geography and Environmental Studies, Stellenbosch University on 5 July 2017.
Wray, C. (2015). ‘Spatial Statistical Analysis of Dissatisfaction with the Performance of Local Government in the Gauteng City-Region, South Africa’, presented at the Geomatics Indaba 2015 Conference, in Kempton Park, South Africa on 11-13 August 2015.
Cheruiyot, K. (2015). ‘Spatial Statistical Analysis of Dissatisfaction with the Performance of Local Government in the Gauteng City-Region, South Africa’, presented at the 2nd International Conference on Applied Methods in Social Sciences: People, Goods and Regions in a Globalized World, in Poznan, Poland on 22-23 May 2015.
Cheruiyot, K. (2015). ‘Presentation and discussion on GCRO’s preliminary spatial statistical analysis of satisfaction with government’, City GCR Seminar, organised by the Gauteng City-Region Observatory (GCRO), at UJ on 6 March 2015.
Katumba, S., K. Cheruiyot, and D. Mushongera (forthcoming). ‘Spatial change in the concentration of multidimensional poverty in Gauteng, South Africa: Evidence from Quality of Life Survey data’ Submitted to Social Indicators Research journal.
Cheruiyot, K., Katumba, S. & Wray, C. (In review), Patterns and Correlates of Dissatisfaction with Government Performance in the Gauteng City-Region, South Africa: A comparison across three government spheres, The Review of Regional studies.
Katumba, S. (2018) 'Spatial statistical analyses to assess the spatial extent and concentration of multidimensional poverty in Gauteng using the South African Multidimensional Poverty Index'. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W8, 85-92, doi.org/10.5194/isprs-archives-XLII-4-W8-85-2018.
Cheruiyot, K., Wray, C. & Katumba, S. (2015). ‘Spatial Statistical Analysis of Dissatisfaction with the Performance of Local Government in the Gauteng City-Region, South Africa’ South African Journal of Geomatics, 4 (3), pp. 224 - 239.
Last updated 28 March 2019.