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

TL;DR

HeatMat addresses urban heat island analysis by estimating city facade materials from street-view imagery and open data, encoding geometry and material properties into 2D maps that feed a 2.5D Monte Carlo heat-transfer simulator. The method couples conductive, radiative, and convective transfers to predict surface temperature $T_s$ and achieves about 20× speedups over full 3D simulations by employing GPU shaders and random-access textures. Validation against Finite Difference, Stardis, and Landsat-based observations shows consistent spatial patterns and credible absolute differences, enabling high-resolution urban-planning studies. The work enables material-change experiments and temporal evolution analyses, highlighting practical pathways for material optimization in cities while noting data limitations and suggesting avenues for aerial data integration and learning-based UHI prediction.

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.

Figures (14)

• Figure 1: From 360° Mapillary image (a.) to sliced rectified facade (b.) to cropped building facade (c.).
• Figure 2: Heatmap obtained with ground truth materials (a), and difference of absolute errors between heatmaps relative to the Ground Truth with LCZ and VLM materials (b). Positive difference means bigger error with LCZ materials, negative difference means bigger error with VLM materials.
• Figure 3: 3D geometry input of Stardis, converted into a set of 2D maps for comparison.
• Figure 4: 2.5 representation of a city using a set of maps, with a top view (roofs, ground), building facade materials (left), city geometry height map, signed distance field, and facade normals (middle). It enables procedural modeling of a facade (right) when intersecting points on a facade in the heat transfer simulator.
• Figure 4: Evolution of the FLIP value according to the number of sample per pixels equivalent in Stardis simulation.