Landsat 8 thermal data to support urban management and planning in the climate change era: a case study in Torino area, NW Italy

Abstract

Land surface temperature (LST) is an important factor in global climate change, vegetation growth, and urban heat island (UHI). LST is one of the most important environmental variables measured by satellite remote sensing. Public domain data are available from the operational Landsat-8 Thermal Infrared Sensor (TIRS). The present study focuses on determining and mapping UHI for the metropolitan city of Turin in Piedmont Italy using Landsat 8 multitemporal collection dataset from 2013 to 2018. The main purpose of this research is to give an instrument for the present urban management and future urban planning in order to increase city resistance and resilience against climate change through mitigation and adaptation. Improving green areas using urban forestry can be a way to mitigate Summer heat waves and trying to regulate the high demand of energy for cooling buildings. LST has been estimated using the Radiative Transfer Equation (RTE) while the LSE (Land Surface Emissivity) according to the NDVI Thresholds Method. In the multitemporal collection the UHI has been detected after calculating zonal statistics. Surfaces with similar thermal behave have been mapped using an Unsupervised classification (K-means). Through the considered years, the analysis has revealed how UHI are very common and persistent in the metropolitan Turin area, where vegetation and water content are lower and where there are a high number of buildings in concrete and asphalt is widespread.