Quantitative assessment of factors that influence heat vulnerability in residential areas using machine learning and unmanned aerial vehicle

Quantitative assessment of factors that influence heat vulnerability in residential areas using machine learning and unmanned aerial vehicle

Climate change and urbanization have intensified the urban heat island (UHI) effect, significantly impacting urban living environments. While existing studies have yielded valuable insights into macro-scale thermal environments, this study shifts the focus toward microscale residential contexts, whe...

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Bibliographic Details
Main Authors: Jawoon Gu, Dongwoo Kim, Chulmin Jun, Seungwoo Son
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:City and Environment Interactions
Subjects:
Unmanned aerial vehicle
Machine learning
Urban thermal environment
Quantitative assessment
Influencing factors
Exploratory data analysis
Online Access:http://www.sciencedirect.com/science/article/pii/S2590252025000285
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