Table 2.

Summary of data sources for each objective

Objective	Data sources
1. Mapping intraurban heat risk and exposure	Socioeconomic data (census, surveys, GCRO datasets) Geospatial data (land use, building density, OpenStreetMaps) Climate data (WRF, UrbClim models, downscaled CDS and ESGF data, IBM-PAIRS platform)
2. Creating a stratified heat–health outcome forecast model	Health data with clinical variables (eg, vital signs, heat-related illness indicators) High-resolution urban temperature hazard maps (Landsat, MODIS data with statistical models for air temperature estimation) Remote sensing data (satellite imagery, land surface temperature, soil moisture, vegetation condition) Socioeconomic and environmental data (household economic conditions, service availability, residential characteristics)
3. Establishing an early warning system	Integrated health and socioeconomic data Geospatial heat hazard maps Health outcome forecast model outputs COVID-19 incidence and mortality rates (for pandemic period adjustment) Risk profile data (demographic groups, health conditions, locations, socioeconomic statuses)

CDS, Copernicus Climate Data Store; ESGF, Earth System Grid Federation; GCRO, Gauteng City-Region Observatory; MODIS, Moderate Resolution Imaging Spectroradiometer; PAIRS, Physical Analytics Integrated Data Repository and Services; WRF, Weather Research and Forecasting.