As cities continue to grow and their infrastructure becomes more complex, the issue of urban heat islands is becoming critical. An Urban Heat Island (UHI) is a metropolitan area where temperatures are significantly higher than in the surrounding rural regions. Dense development, heavy traffic, industrial activity, and high population density turn cities into heat traps. This leads to the accumulation of excess heat, altering the microclimate and deteriorating air and water quality.
Showcasing the capabilities of 3D mapping technologies, our Swiss partner Pix4D carried out a research project at Binghamton University. Under the guidance of Thomas Pingel, Associate Professor in the Department of Geography, 3D thermal maps of the campus were created by combining data from drones, LiDAR, and thermal sensors. These models are now used both in academic programs and to support urban planners in developing strategies for greening and infrastructure renewal.
Data collection methodology
Data collection was carried out in several stages using Pix4D solutions:
- Processing RGB imagery in PIX4Dmatic — used to generate the base 3D model of the site;
- Positioning thermal data in PIX4Dmapper — integration of thermal maps with the geometric structure of objects;
- Output file structure — enabled the use of a “bootstrapping” method, where information from RGB data improves the accuracy of thermal models.
In addition, export to 3D tiles was used for streamlined workflows, along with the pyopf toolkit, which enabled the creation of high-quality NeRF visualizations and interactive flythroughs.
This combination made it possible to generate a comprehensive 3D thermal model of the campus, ready for further analysis and presentations.
3D map of a large section of the campus. Data processed in PIX4Dmatic.
Results
The project delivered the following outcomes:
- Creation of 3D thermal maps of the campus, covering diverse land cover types — from large buildings and transportation infrastructure to green spaces and natural areas;
- Integration of thermal data with LiDAR surveys, providing highly detailed and accurate 3D models;
- Use of the pyopf toolkit to merge reconstructions with NeRF models and generate interactive visualizations.
Image obtained from the final render of combined LiDAR and thermal imaging data. The white roof of the building significantly reduces the temperature, and the surrounding trees cool the soil nearby.
Conclusion
The use of PIX4Dmatic and PIX4Dmapper has proven highly effective in generating accurate 3D thermal models of urban environments. These datasets support not only academic research but also practical urban planning — from raising public awareness about the scale of urban heat islands to integrating green spaces into city renewal strategies.
