Simulating the effectiveness of greening measures for reducing the urban heat island effect: the case study of Milan

18:00 Tuesday 28 May




Nicola Colaninno (Italy) 1; Ahmed Eldesoky (Italy) 2; Eugenio Morello (Italy) 1

1 - Laboratorio di Simulazione Urbana Fausto Curti, Dipartimento di Architettura e Studi Urbani, Politecnico di Milano; 2 - PhD candidate, Università IUAV di Venezia

Climate change and global warming are among the main international concerns and major issues on the global agenda; the well-documented increase in earth’s temperature and the frequency of extreme heat waves endanger the health and wellbeing of millions of people worldwide, with serious implications on the most vulnerable populations. Currently, the wide availability of remote sensing information at high spatial resolution opens the door to promising and accurate predictions and mapping. Specifically, surface and air temperature, as well as vegetation measured by the Normalized Difference Vegetation Index (NDVI) represent fundamental information to assess effective mitigation and adaptation planning for improving cities’ resilience.

The aim of this work is to investigate the effectiveness of remote sensing as a powerful tool to support spatial analysis and planning of critical urban hotspots, with particular focus on simulating the effects of ‘urban greening’ measures and key urban morphological indicators on urban microclimate. The case study application is the City of Milan, Italy.

In particular, we have experimented the possibility of simulating the effects induced by vegetation on the urban heat island phenomenon (UHI), based on quality and spatial distribution of greenscapes in urban areas. On one hand, we have used a statistical model to predict near-surface temperature at the canopy layer by combining weather station measurements and land surface temperature from satellite data; the result is a near-surface temperature map, both daytime and night-time, according to the Landsat resolution of 30 meters per pixel. On the other hand, we have calculated the NDVI from Landsat 7 ETM+. Moreover, we have taken into account the effectiveness of green measures, such as trees, to affect urban morphology features such as the Sky View Factor (SVF), besides affecting the land cover albedo.

Using a regression model, we have assessed the correlation among near-surface air temperature, vegetation and SVF. Eventually, based on the map of potential green roofs in Milan, provided by the DECUMANUS project, we have simulated an improved NDVI and the effect of the latter upon temperatures. As shown by the results, the increase of green areas has an important impact on the microclimate, leading to a lowering of the UHI intensity of around one-Celsius degree.

The research outcomes have been carried out through two research projects, discussed with local public authorities, and are going to inform official adaptation and urban forestation strategies promoted at the local level.