Spatially-optimized urban greening for reduction of population exposure to land surface temperature extremes
European Commission · Joint Research Centre · +6 more institutions
Abstract
The population experiencing high temperatures in cities is rising due to anthropogenic climate change, settlement expansion, and population growth. Yet, efficient tools to evaluate potential intervention strategies to reduce population exposure to Land Surface Temperature (LST) extremes are still lacking. Here, we implement a spatial regression model based on remote sensing data that is able to assess the population exposure to LST extremes in urban environments across 200 cities based on surface properties like vegetation cover and distance to water bodies. We define exposure as the number of days per year where LST exceeds a given threshold multiplied by the total urban population exposed, in person ⋅ day.…
Citation impact
- FWCI
- 22.82
- Percentile
- 100%
- References
- 57
Authors
7- EMEmanuele MassaroCorresponding
European Commission, Joint Research Centre
- RSRossano Schifanella
Institute for Scientific Interchange, University of Turin
- MPMatteo Piccardo
Joint Research Centre
- LCLuca Caporaso
Joint Research Centre, National Research Council
- HTHannes Taubenböck
University of Würzburg, Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
Topics & keywords
- Vegetation (pathology)
- Greening
- Population
- Environmental science
- Climate change
- Physical geography
- Land cover
- Population growth