Table 1. Description of studies.
| Author (year) | Location | Characteristics | Study duration | Exposure variable | Outcome variable |
| Song et al10 (2022) | Hong Kong, China | Daily mortality and meteorological data were analysed, using the Normalised Difference Vegetation Index (NDVI) and distance to coast as proxies for green and blue space exposure, respectively. | 2008–2017 | Green space (measured by NDVI) and blue space (proximity to coast) | Heat-related mortality |
| Chen et al11 (2014) | Melbourne, Australia | Mortality data were analysed. The study considered population by sex and by two age groups (0–75 and 75+). | 1988–2007 | Urban vegetation schemes | Heat-related mortality rate |
| Nguyen et al12 (2022) | Hanoi, Vietnam | Used hospital admission records from three national hospitals in Hanoi. Daily meteorological data and satellite images for green space measurement were used. | 2010–2014 | Green space | Heat-related respiratory hospitalisation among children under 5 years of age. |
| Kalkstein et al13 (2022) | Los Angeles, California, USA | Used historical weather data and mortality data. Mortality data were assessed to estimate excess deaths during extreme heat events. | 1985–2010 | Tree canopy and albedo modifications | Heat-related mortality reduction |
| Son et al14 (2016) | Seoul, Korea | Mortality data and NDVI data from MODIS satellite images were used to assess urban vegetation. | 2000–2009 | Urban vegetation measured by NDVI | Heat-related mortality. |
| Chaston et al15 (2022) | Sydney, Australia | Mortality records, census population data, weather observations and climate change projections. | 1997–2018 and projected data up to 2100. | Urban Heat Island effect and tree cover | Heatwave-attributable excess deaths |
| Wang et al16 (2015) | Brisbane, Melbourne and Sydney, Australia | Daily climate variables and mortality data were assessed. It focused on non-accidental and circulatory mortality. | 1988–2011 | Heatwaves are defined consistently across the cities. | Non-accidental (heart attacks and strokes) and circulatory mortality. |
| Burkart et al17 (2015) | Lisbon, Portugal | Mortality data, remotely sensed data for urban vegetation and proximity to water bodies were assessed. | 1998–2008 | Urban green (vegetation) and urban blue (proximity to water bodies) | Heat-related all-cause natural excess mortality. |
| Kusaka et al18 (2022) | Tsukuba, Ibaraki, Japan | Thermal comfort of healthy individuals was assessed under wisteria trellises and tents, compared with direct sunlight. | Specific dates in August and September 2017 | Shade provided by wisteria trellises and tents | Subjective thermal comfort and physiological responses. |
| Sinha et al19 (2021) | Baltimore, Maryland, USA | Mortality data, census population data, weather observations and climate change projections were assessed. | 2007–2017 | Urban green space coverage | Reductions in mortality attributable to extreme heat events |
| McDonald et al20 (2019) | USA (97 cities) | Analysed tree cover and developed land-cover information across 97 US cities. | 2011 National Land Cover Database | Urban green space coverage | Heat-related mortality, morbidity |
| Sadeghi et al21 (2021) | Sydney, Australia | Used weather stations across, calculating average hourly Universal Thermal Climate Index (UTCI). | 2017 | Urban greening infrastructure | Reduction in daily average UTCI and heat-attributable deaths. |
MODISModerate Resolution Imaging Spectroradiometer