Urban forests plays a critical role in mitigating the urban heat island (UHI) effect, yet its hourly and structure-dependent cooling performance remains insufficiently understood - particularly in morphology-constrained heritage cities. This study investigates the hourly regulation of land surface temperature (LST) by vegetation structure in Rome, a compact city with limited greening opportunities. We use multi-temporal Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) thermal imagery across 12 clear-sky summer scenes and analyse vegetation–temperature relationships with random forest (RF) models, interpreted through Shapley additive explanations (SHAP) and partial dependence plots (PDPs).
Hourly impact of urban forests on land surface temperature based on machine learning / Fan, Peiyi; Wang, Haitao; Imbroglini, Cristina. - In: RESULTS IN ENGINEERING. - ISSN 2590-1230. - (2025). [10.1016/j.rineng.2025.107584]
Hourly impact of urban forests on land surface temperature based on machine learning
Peiyi Fan
Primo
;Cristina Imbroglini
Ultimo
2025
Abstract
Urban forests plays a critical role in mitigating the urban heat island (UHI) effect, yet its hourly and structure-dependent cooling performance remains insufficiently understood - particularly in morphology-constrained heritage cities. This study investigates the hourly regulation of land surface temperature (LST) by vegetation structure in Rome, a compact city with limited greening opportunities. We use multi-temporal Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) thermal imagery across 12 clear-sky summer scenes and analyse vegetation–temperature relationships with random forest (RF) models, interpreted through Shapley additive explanations (SHAP) and partial dependence plots (PDPs).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
