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As impervious surfaces have seized most areas in cities worldwide, urban heat island (UHI) has become a global concern. Urban green infrastructures (UGI) are crucial to providing microclimate regulation and thermal comfort through evapotranspiration (ET) and shading. High-spatiotemporal-resolution ET maps are required to plan and manage UGI to mitigate the UHI and droughts. We propose a method using open-access data, including hourly meteorological data and remote sensing vegetation parameters, to predict heat fluxes using a soil-vegetation-atmosphere model. The ET prediction accuracy was assessed using eddy covariance towers, showing an R2 of 0.84 for the residential-vegetated site and 0.57 for the built-up site during 2019. A greening cooling service index (GCoS), divided into evapotranspirative (ECoS) and radiative (RCoS) cooling effects were mapped for Berlin, Germany. Almost half of the population and 21% of the city area are located in low GCoS (<0.25). Based upon climate change scenarios, a rise in temperature increases the annual ET, while plant stress and droughts considerably decrease overall cooling services. Simulation of climatological scenarios and plant traits can help to define more suitable species adapted for urban environments. The presented method provides an effective decision-making tool for urban planning to reduce heat risk for urban residents.
Rocha et al. (Fri,) studied this question.