Photography by:
  • Amanda van der Walt

Datasets

GCRO has spent considerable time and resources building a 'data warehouse' encompassing the Gauteng City-Region. Various applications, available via the Urban Data Gallery, showcase GCRO’s data and analysis. A few of the key datasets available from GCRO are described below.

Quality of Life survey data

GCRO’s primary dataset is the biennial Quality of Life survey (QoL) which measures the quality of life, socio-economic circumstances, attitudes to service delivery, psycho-social attitudes, value-base, and other characteristics of the GCR.

Questionnaires, data, and documentation for our most recent survey (QoL 2023/24), as well as previous surveys (2009, 2011, 2013/14, 2015/16, 2017/18 & QoL 2020/21), are available for download through DataFirst: https://www.datafirst.uct.ac.za/dataportal/index.php/catalog/GCRO.

Our data is shared under a CC SA-BY 4.0 license, meaning that it is free for use. We ask that the data be cited using the citation provided on the DataFirst website and that you share a copy of the work produced with us if possible.

Data from QoL 2013/14, 2011, and 2009 can be accessed via the Quality of Life survey data viewer. QoL 2017/18, 2020/21, and 2023/24 can also be viewed on the GCRO Quality of Life survey viewer.

You are welcome to contact the GCRO if you would like to discuss any aspect of the data or its use in more detail.

GIS data

New innovative sources of spatial data have been purchased to assist in the spatial analysis and mapping of the GCR. Data licences were negotiated with the data suppliers to include access by Wits and UJ students and lecturers for academic, teaching, and research (non-financial gain) purposes. The list of data includes:

  • GCRO holds various administrative datasets such as municipal boundaries, metropolitan municipality planning regions, mesozones, ward boundaries, sub-places, schools, roads, railways, rivers, and more.
  • CSIR & SAEON: Carbon Atlas. 2018 CSIR 25m Woody Above Ground Biomass (AGB in tonnes per hectare) layer derived from ALOS 2 annual mosaic L-band SAR and seasonal Sentinel-2 Red Edge NDVI datasets.
  • European Space Agency (ESA): Land cover. At 20 m resolution, this land cover classification data of Africa was created using 180 000 Copernicus Sentinel-2A images captured between December 2015 and December 2016.
  • GeoTerraImage (GTI): Building-based land use. Point per building in Gauteng for 2001 and 2016, differentiating between 70 land use classes.
  • GTI: Land use change 1990-2000-2010-2020. A unique and standardized temporal land use dataset (aggregated to 400mx400m hexagons in Gauteng) derived from Landsat imagery that provides insight into the basic land use changes in the GCR.
  • GTI: Hexagon summaries. In addition to land use change (above), hexagon summaries include population projections, building-based land use, socio-economic risk index, neighbourhood lifestyle index, and new developments.
  • Statistics South Africa: Dwelling Frame. The Dwelling Frame is a spatially referenced framework of structures within South Africa. The primary function of the Dwelling Frame is to provide a base for statistical sampling frames required for surveys and censuses in Stats SA and other organisations.

Students and lecturers from UJ and Wits are encouraged to make use of these valuable datasets for research projects focusing on the GCR. Examples of some of these layers are available on the GCRO GIS website.

For more information, please contact Christian Hamann (christian.hamann@gcro.ac.za).

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