The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-1/W2-2023
https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1589-2023
https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1589-2023
13 Dec 2023
 | 13 Dec 2023

MEASURING THE INFLUENCE OF A MOTORWAY CONSTRUCTION ON LAND SURFACE TEMPERATURE USING LANDSAT THERMAL DATA: A CASE STUDY IN THE METROPOLITAN CITY OF MILAN

A. Vavassori, M. Puche, and M. A. Brovelli

Keywords: Motorway construction, Land Surface Temperature, Landsat, Urban Heat Island, Remote Sensing

Abstract. Cities have been identified as a landmark for climate change, being among the direct targets of its negative feedbacks. The combined effect of climate change and rapidly growing urbanization is exacerbating the urban heat island phenomenon in cities worldwide. The availability of multiple geo-data sources including satellite remote sensing products is significantly empowering the investigation of its driving factors. This is a crucial step to implement ad hoc mitigation and adaptation strategies. In view of the above, the goal of this study is to measure the effect of a motorway on the Land Surface Temperature (LST) space-time patterns by leveraging Landsat 5 and 8 thermal data of the period from 2006 to 2022. The study area is around the motorway A58 and connected roads in the Metropolitan City of Milan (northern Italy). LST patterns are investigated along the motorway track and in the neighbouring areas before and after the motorway construction, in both the cold and warm seasons. Results show that the motorway significantly affects the LST distribution during summer with a median increase of 2.5 °C along the road track with respect to the surrounding area. The warming effect is also recorded in the road buffers with decreasing LST with increasing distance from the road. On the contrary, no meaningful variation in terms of LST is measured in winter. These experiments provide insightful measures of the effect of a highway on the local climate conditions in an urban area, thus representing crucial pieces of information for driving evidence-based urban planning activities.