March 2026

Conference Paper

Quantifying and Zoning Urban Heat Island Effects Using Unsupervised Machine Learning

By:
Chowdhury, Shovan ; Li, Fengqi ; Stubbings, Avery P; New, Joshua R
Book Title:
Proceedings of the ASME 2025 19th International Conference on Energy Sustainability
Publication Date:
March 12, 2026
Conference Name:
ASME 2025 19th International Conference on Energy Sustainability
Conference Location:
Westminster, Colorado, United States of America
Conference Sponsor:
ASME
View DOI Listing:
https://doi.org/10.1115/ES2025-156691

Abstract

This work explores the Urban Heat Island (UHI) effects in Maricopa County, Arizona, employing a simulation-based approach that combines large-scale building energy modeling with advanced spatial analysis. Utilizing the Automatic Building Energy Modeling (AutoBEM) software suite, we simulated the energy consumption for approximately 1.35 million buildings based on the Model America version 1.0 (MAv1) dataset. Our methodology incorporated spatial analysis at multiple scales, including individual buildings, clusters of zones determined by K-means clustering, and geographical level evaluation based on Zip codes. The results revealed significant variations in energy consumption and heat emissions across different building types and urban zones. High-emission hotspots identified through clustering pointed to areas most contributing to the UHI effects. Zip code-based area analysis further contextualized these findings, offering an urban context-based perspective on emission distribution and informing potential urban energy policies for mitigating UHI effects.