Over the next 30 years, temperatures are expected to increase in hot semi-arid zones. Despite increasing studies on urban heat, cooling measures suitable for this climate zone remain poorly investigated. The proposed method is innovative because it focuses on significant landscape metrics for determining the land surface temperature (LST) and evaluating cooling measures. Recurrence of warm spells was identified analysing the daily air temperatures. Daytime and night-time LST data acquired from space were correlated with landscape metrics extracted from very high-resolution satellite imagery. Stepwise linear regression was used to identify the significant metrics that affected it. Cooling measures were selected considering implementation leeway; performance of existing measures; strengths, weaknesses, opportunities, and threats, equity analyses. Although the method was tested in Niamey, Niger, it can be applied to any city or town in hot semi-arid Global South, requiring decision-making support on cooling policies. • Landscape metrics are consistent with development standard and general requirements • Evaluation of measures to reduce land surface temperature includes experts’ advice • Equity of measures to reduce land surface temperature is considered

LST-R: A method for assessing land surface temperature reduction in urban, hot and semi-arid Global South / Tiepolo, Maurizio; Galligari, Andrea; Giulio Tonolo, Fabio; Moretto, Enrico; Stefani, Silvana. - In: METHODSX (AMSTERDAM). - ISSN 2215-0161. - ELETTRONICO. - 10:(2023), pp. 1-15. [10.1016/j.mex.2022.101977]

LST-R: A method for assessing land surface temperature reduction in urban, hot and semi-arid Global South

Tiepolo,Maurizio;Galligari,Andrea;Giulio Tonolo,Fabio;
2023

Abstract

Over the next 30 years, temperatures are expected to increase in hot semi-arid zones. Despite increasing studies on urban heat, cooling measures suitable for this climate zone remain poorly investigated. The proposed method is innovative because it focuses on significant landscape metrics for determining the land surface temperature (LST) and evaluating cooling measures. Recurrence of warm spells was identified analysing the daily air temperatures. Daytime and night-time LST data acquired from space were correlated with landscape metrics extracted from very high-resolution satellite imagery. Stepwise linear regression was used to identify the significant metrics that affected it. Cooling measures were selected considering implementation leeway; performance of existing measures; strengths, weaknesses, opportunities, and threats, equity analyses. Although the method was tested in Niamey, Niger, it can be applied to any city or town in hot semi-arid Global South, requiring decision-making support on cooling policies. • Landscape metrics are consistent with development standard and general requirements • Evaluation of measures to reduce land surface temperature includes experts’ advice • Equity of measures to reduce land surface temperature is considered
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2973937