EMS Annual Meeting Abstracts
Vol. 21, EMS2024-727, 2024, updated on 05 Jul 2024
https://doi.org/10.5194/ems2024-727
EMS Annual Meeting 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Wednesday, 04 Sep, 14:00–14:15 (CEST)| Lecture room 203

A geospatial approach for heat risk estimation by integrating remotely sensed and ground-based data in Milan, Italy

Matej Žgela, Alberto Vavassori, and Maria Antonia Brovelli
Matej Žgela et al.
  • Politecnico di Milano, Department of Civil and Environmental Engineering, Milano, Italy (matej.zgela@polimi.it)

The effects of climate change have never been as pronounced as they are now, however, simultaneously, urban areas are experiencing additional local-scale anthropogenic effects due to the modification of the natural environment. Consequently, urban heat islands form, amplifying the heat load in the cities and heightening the vulnerability of citizens to heat-related issues.

In the context of Europe, the fastest-warming continent in the world, significant impacts on living conditions will occur as a result of numerous climate risks. Furthermore, in a recently published European Climate Risk Assessment, heat risk is identified as one of the two main risks for which urgent action is needed. However, implementing mitigation measures in urban areas is often slow, highlighting the need to employ geospatial technologies to aid the process.

To address this issue, we identified high heat risk areas and heat-resilient zones in the city of Milan, Italy. High-resolution geospatial datasets, including remotely sensed imagery and official/crowd-sourced in-situ data, were utilised for producing a heat risk index. Main known drivers of heat risk were used as predictors, such as land surface and air temperature, vegetation fraction, surface material composition and others.

The produced heat risk maps were overlayed with population data, selecting the locations of public institutions most used by vulnerable populations - schools, retirement homes, and public health institutions. Institutions’ surroundings have been investigated based on urban geometry, considering their micro-urban morphology and at the neighbourhood scale with local climate zones. Moreover, the research examined the frequency of extreme temperatures occurring in various areas of the city over time and put it in relation to vulnerable population data.

Through detailed analysis of city-scale heat risk, the study has identified the main hotspots and cool spots within the city. The research findings are critical for vulnerable populations facing high heat risks, enabling targeted and straightforward implementation of appropriate heat mitigation measures. Finally, the utilisation of high-resolution geospatial information and multiscale datasets can aid city planners, providing them with crucial scientific insights for informed decisions.

How to cite: Žgela, M., Vavassori, A., and Brovelli, M. A.: A geospatial approach for heat risk estimation by integrating remotely sensed and ground-based data in Milan, Italy, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-727, https://doi.org/10.5194/ems2024-727, 2024.