A novel metric – the Mean Temperature Difference (MTD) – is proposed for the selection of urban-rural pairs of stations needed in the Urban Heat Island (UHI) quantification. This metric highlights the thermal pattern typical of each weather station with respect to the average one of the area of interest. Afterwards, Principal Component Analysis is adopted to cluster stations into subsets exhibiting similar thermal behaviors. The joint use of MTD and PCA allows one to classify stations objectively and without the need of preliminary assumptions about the station landscapes. An application to the metropolitan area of Turin (Italy) and a comparison with validated methods to select urban-rural pairs demonstrate that the proposed approach is easily interpretable and reliable also when the study area exhibits a non-trivial landscape categorization.
An innovative approach to select urban-rural sites for Urban Heat Island analysis: the case of Turin (Italy) / Bassani, Francesca; Garbero, Valeria; Poggi, Davide; Ridolfi, Luca; von Hardenberg, Jost; Milelli, Massimo. - In: URBAN CLIMATE. - ISSN 2212-0955. - 42:(2022), p. 101099. [10.1016/j.uclim.2022.101099]
An innovative approach to select urban-rural sites for Urban Heat Island analysis: the case of Turin (Italy)
Bassani, Francesca;Poggi, Davide;Ridolfi, Luca;von Hardenberg, Jost;
2022
Abstract
A novel metric – the Mean Temperature Difference (MTD) – is proposed for the selection of urban-rural pairs of stations needed in the Urban Heat Island (UHI) quantification. This metric highlights the thermal pattern typical of each weather station with respect to the average one of the area of interest. Afterwards, Principal Component Analysis is adopted to cluster stations into subsets exhibiting similar thermal behaviors. The joint use of MTD and PCA allows one to classify stations objectively and without the need of preliminary assumptions about the station landscapes. An application to the metropolitan area of Turin (Italy) and a comparison with validated methods to select urban-rural pairs demonstrate that the proposed approach is easily interpretable and reliable also when the study area exhibits a non-trivial landscape categorization.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2956207