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.
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.
QoL 2023/24
- Questionnaires, data, and documentation DataFirst View
QoL 2020/21
- Questionnaires, data, and documentation DataFirst View
QoL 2017/18
- Questionnaires, data, and documentation DataFirst View
QoL 2015/16
- Questionnaires, data, and documentation DataFirst View
QoL 2013/14
- Questionnaires, data, and documentation DataFirst View
QoL 2011
- Questionnaires, data, and documentation DataFirst View
QoL 2009
- Questionnaires, data, and documentation DataFirst View
Gauteng Administrative Boundary data
Ward boundaries
- 2016 ward boundaries Municipal Demarcation Board View
- 2020 ward boundaries Municipal Demarcation Board View
Local municipality boundaries
- 2018 local municipality boundaries Municipal Demarcation Board View
Planning Region boundaries
- Planning region boundaries Gauteng City Metros and local district municipalities View
Enumerator Area (EA) boundaries
- 2011 EA boundaries Statistics South Africa View
Main place boundaries
- 2011 Main place boundaries Statistics South Africa View
Sub-place boundaries
- 2011 Sub-place boundaries Statistics South Africa View
Provincial boundary
- Gauteng Provincial boundary Municipal Demarcation Board View
Former Bantustan Homelands and Traditional/Tribal land boundaries
This shapefile outlines the boundaries of the Transkei, Bophuthatswana, Venda, and Ciskei (TBVC) independent homelands created by the Apartheid government (pre 1994)
- The former Bantustan Homeland boundaries Department of Land Affairs, SA (2007) View
StepSA National Mesozone boundaries
This layer is a unique spatially equal (in size) unit to enable comparison across geographies in South Africa. Some attributes include an indicator of economic production per sector and population estimates.
- The mesozone boundaries Council for Scientific and Industrial Research (CSIR) View
Health District boundaries
- The Gauteng Health District boundaries Gauteng Department of Health View
National Police Precinct boundaries
- The national police precinct boundaries South African Police Service (SAPS) View
Uber H3_7 Hexagons
Uber hexagons (H3) were developed for optimising ride pricing and dispatch and for visualising and exploring spatial datasets. This grid works well with the Spatial Economic Activity (SEAD) Data Portal (https://spatialtaxdata.org.za/)
Public infrastructure data
National Roads Line Shapefiles
- National roads line shapefiles Open Street Map (OSM) View
National Railway Line Shapefiles
- The National railway line shapefiles Open Street Map (OSM) View
National Rivers Line Shapefiles (1: 500 000)
- The national rivers line shapefiles (1: 500 000) Department of Water Affairs (DWA) View
Healthcare Facilities Point Shapefiles
- South Africa Health Facilities data Open Street Map (OSM) View
Department of Education School location Point Shapefiles
- Various school master lists Department of Basic Education, South Africa View
South Africa Land Use Land Cover and Urban Footprint data
2016 20m European Space Agency (ESA) Land Cover
This is a land cover classification data of Africa was created using 180 000 Copernicus Sentinel-2A images captured between December 2015 and December 2016.
- ESA Land Cover raster image European Space Agency View
1990, 2014, 2018, 2020 and 2022 South African National Land Cover (SANLC) Data
These are multi-year national land cover and land use raster datasets created from historic Landsat (30m for 1990 and 2014) and Sentinel-2 (20m for 2018, 2020 and 2022).
- The SANLC Raster Image for the various years Department of Forestry, Fisheries and the Environment, SA View
2019 German Aerospace Center (DLR) World Settlement Footprint (WSF) 3D
WSF 3D raster products provide detailed quantification of the average height, total volume, total area and the fraction of buildings at 90 m resolution at a global scale. These products are derived from multitemporal Sentinel-1 and Sentinel-2 imagery.
- Global WSF 3D raster datasets German Aerospace Center (DLR) View
Multi-year Global Human Settlement Layer (GHSL)
GHSL raster datasets provide some of the most accurate, detailed, consistent, and accessible geospatial datasets on human presence and settlements worldwide. Products include urban footprint coverage and other related datasets from 1990 and into the future (2030)
- Global GHSL raster datasets European Union (EU) and the Copernicus programme View
Demographics
Statistics South Africa
- Various datasets Statistics South Africa View
- Census 2022 Statistics South Africa View
- Ward-level demographic Statistics South Africa View
WorldPop
World population count estimates at 100m (country level) and 1km (global level) spatial resolutions over various years
- Global WorldPop raster datasets WorldPop View
LandScan
World population count estimates at 1km spatial resolution over various years.
- Global LandScan raster datasets Oak Ridge National Laboratory (ORNL) View
Biodiversity data
South African Protected Areas, Conservation Areas and Biosphere reserve boundary shapefiles
- Protection and conservation area boundaries Department of Forestry, Fisheries and the Environment, SA View
2025 SANBI National Biodiversity Assessment (NBA)
It is a collaborative effort to synthesise the best available science on South Africa’s biodiversity to inform policy, support decision-making across multiple sectors, and contribute to national development priorities. The raster layer includes a detailed classification map specifically linked to ecosystem groups and wetland types etc.
- Various ecosystem type tabs (raster map) South African National Biodiversity Institute (SANBI) View
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