A functional seasonal thermal hot-spot classification: Focus on industrial sites

Abstract

This study was focused on the metropolitan area of Florence in Tuscany (Italy) with the aim to provide a functional spatial thermal anomaly indicator obtained throughout a thermal summer and winter hot-spot detection. The hot-spot analysis was performed by applying Getis-Ord Gi* spatial statistics to Land Surface Temperature (LST) layers, obtained from Landsat 8 remote sensing data during the 2015-2019 daytime summer and winter period, to delimitate summer hot- and cool-spots, and winter warm- and cold-spots. Further, these ones were spatially combined thus obtaining a comprehensive summer-winter Thermal Hot-Spot (THS_SW) spatial indicator. Winter and summer mean daily thermal comfort profiles were provided for the study area assessing the Universal Thermal Climate Index (UTCI) by using meteorological data available from seven local weather stations, located at a maximum distance of 350 m from industrial sites. A specific focus on industrial sites was carried out by analyzing the industrial buildings characteristics and their surrounding areas (50 m buffer), through the following layers: industrial building area (BA), surface albedo of buildings (ALB), impervious area (IA), tree cover (TC), and grassland area (GA). The novel THS_SW classification applied to industrial buildings has shown that about 50% of the buildings were located in areas characterized by summer hot-spots. Increases in BA and IA revealed warming effects on industrial buildings, whereas increases in ALB, TC, and GA disclosed cooling effects. A decrease of about 10% of IA replaced by TC and GA was associated with about 2 °C decrease of LST. Very strong outdoor heat stress conditions were observed during summer daytime, whereas moderate winter outdoor cold stress conditions were recorded during nighttime until the early morning. The thermal spatial hot-spot classification in industrial areas provides a very useful source of information for thermal mitigation strategies aimed to reduce the heat-related health risk for workers.

Keywords: Getis-Ord Gi* statistic; Industrial buildings; Mitigation strategies; Thermal drivers; Thermal hot-spot.