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.

Tiepolo, M., Galligari, A., Tonolo, F., Moretto, E., Stefani, S. (2023). LST-R: A method for assessing land surface temperature reduction in urban, hot and semi-arid Global South. METHODSX (AMSTERDAM), 10 [10.1016/j.mex.2022.101977].

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

Moretto, Enrico
Co-ultimo
;
Stefani, Silvana
Co-ultimo
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.
Articolo in rivista - Articolo scientifico
ECOSTRESS; Environmental equity; Niamey; Participated SWOT; Regression analysis; School greening; Tree-lined roads; Heat; Urban planning; Warm spells
English
Tiepolo, M., Galligari, A., Tonolo, F., Moretto, E., Stefani, S. (2023). LST-R: A method for assessing land surface temperature reduction in urban, hot and semi-arid Global South. METHODSX (AMSTERDAM), 10 [10.1016/j.mex.2022.101977].
File in questo prodotto:
File Dimensione Formato  
Tiepolo-2023-Methodsx-VoR.pdf

accesso aperto

Descrizione: Article
Tipologia di allegato: Publisher’s Version (Version of Record, VoR)
Licenza: Creative Commons
Dimensione 5.57 MB
Formato Adobe PDF
5.57 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/400172
Citazioni
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
Social impact