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Predicting Urban Heat Island Mitigation with Random Forest Regression in Belgian Cities
Joshi, Mitali; Aliaga, Daniel G.; Teller, Jacques
2023In Urban Book Series
Peer reviewed
 

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Keywords :
Green roofs; Land surface temperature (LST); Random forest regression; Urban heat island (UHI); Geography, Planning and Development; Urban Studies
Abstract :
[en] An abundance of impervious surfaces like building roofs in densely populated cities make green roofs a suitable solution for urban heat island (UHI) mitigation. Therefore, we employ random forest (RF) regression to predict the impact of green roofs on the surface UHI (SUHI) in Liege, Belgium. While there have been several studies identifying the impact of green roofs on UHI, fewer studies utilize a remote-sensing-based approach to measure impact on Land Surface Temperatures (LST) that are used to estimate SUHI. Moreover, the RF algorithm, can provide useful insights. In this study, we use LST obtained from Landsat-8 imagery and relate it to 2D and 3D morphological parameters that influence LST and UHI effects. Additionally, we utilise parameters that influence wind (e.g., frontal area index). We simulate the green roofs by assigning suitable values of normalised difference-vegetation index and built-up index to the buildings with flat roofs. Results suggest that green roofs decrease the average LST.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Joshi, Mitali  ;  Université de Liège - ULiège > Urban and Environmental Engineering
Aliaga, Daniel G.;  Department of Computer Science, Purdue University, West Lafayette, United States
Teller, Jacques  ;  Université de Liège - ULiège > Département ArGEnCo > LEMA (Local environment management and analysis)
Language :
English
Title :
Predicting Urban Heat Island Mitigation with Random Forest Regression in Belgian Cities
Publication date :
2023
Main work title :
Urban Book Series
Publisher :
Springer Science and Business Media Deutschland GmbH
ISBN/EAN :
978-3-03-131746-0
978-3-03-131745-3
Peer reviewed :
Peer reviewed
Available on ORBi :
since 07 November 2023

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