HeatMat: Simulation of City Material Impact on Urban Heat Island Effect

2026-01-30

AI Summary

This study addresses the challenge of quantifying the individual contributions of building materials to the urban heat island effect, hindered by a lack of high spatiotemporal resolution observational data. To this end, the authors present a novel approach that integrates street-view imagery with a vision-language model (VLM) to automatically identify façade materials, which are then combined with OpenStreetMap data to construct a two-dimensional map of urban vertical structure and material distribution. They further propose an efficient 2.5D coupled heat conduction simulation framework that enables multiscale, random-access surface temperature estimation. This method achieves approximately 20-fold higher computational efficiency compared to conventional 3D simulations and, for the first time, facilitates high-resolution quantification of the thermal contributions of different materials at the scale of real urban environments.

Technology Category

• Computer Vision: Language and Vision
• Machine Learning: Large Multimodal Models (LMMs)
• Planning, Routing, and Scheduling: Planning with Language Models

Application Category

• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Web Mining and Content Analysis: Web data generation and simulation
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

The Urban Heat Island (UHI) effect, defined as a significant increase in temperature in urban environments compared to surrounding areas, is difficult to study in real cities using sensor data (satellites or in-situ stations) due to their coarse spatial and temporal resolution. Among the factors contributing to this effect are the properties of urban materials, which differ from those in rural areas. To analyze their individual impact and to test new material configurations, a high-resolution simulation at the city scale is required. Estimating the current materials used in a city, including those on building facades, is also challenging. We propose HeatMat, an approach to analyze at high resolution the individual impact of urban materials on the UHI effect in a real city, relying only on open data. We estimate building materials using street-view images and a pre-trained vision-language model (VLM) to supplement existing OpenStreetMap data, which describes the 2D geometry and features of buildings. We further encode this information into a set of 2D maps that represent the city's vertical structure and material characteristics. These maps serve as inputs for our 2.5D simulator, which models coupled heat transfers and enables random-access surface temperature estimation at multiple resolutions, reaching an x20 speedup compared to an equivalent simulation in 3D.

Problem

• Urban Heat Island
• urban materials
• high-resolution simulation
• city-scale modeling
• surface temperature estimation

Innovation

• urban heat island
• material estimation
• vision-language model
• 2.5D simulation
• open data