Optimizing Urban Thermal Environments Through 2D/3D Landscape Pattern Analysis: A Machine Learning-Driven Approach for the Yangtze River Delta Urban Agglomeration

Optimizing Urban Thermal Environments Through 2D/3D Landscape Pattern Analysis: A Machine Learning-Driven Approach for the Yangtze River Delta Urban Agglomeration

To address the escalating urban heat stress driven by global warming and rapid urbanization, this study integrates multi-source remote sensing data to assess the spatiotemporal dynamics of summer thermal comfort across the Yangtze River Delta Urban Agglomeration (YRDUA) from 2000 to 2020. By combini...

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Bibliographic Details
Main Authors: Haoshan Zhou, Ruci Wang, Hao Hou, Bin Xie, Tangao Hu
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Buildings
Subjects:
thermal comfort
universal thermal climate index
landscape patterns
interpretable machine learning
Yangtze River Delta urban agglomeration
Online Access:https://www.mdpi.com/2075-5309/15/13/2261
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