VUB research: how cities can go greener in a warming climate
VUB researcher Robbe Neyns is mapping urban tree species using satellite imagery and artificial intelligence
VUB researcher Robbe Neyns has developed artificial intelligence capable of identifying trees down to species level in satellite and aerial imagery. The technology can help cities to better map their trees and biodiversity, thereby making the urban environment as liveable as possible, particularly in the face of a warming climate. Trees fulfil important functions in our cities. They provide shade and cooling, filter the air and serve as a habitat and food source for numerous animals. Surprisingly, however, we often do not know exactly which trees are where. Existing tree inventories are not always complete or up to date, and identifying thousands of trees on the ground is labour-intensive.
Neyns therefore investigated whether artificial intelligence could take over part of this work from the air. For the Brussels-Capital Region, he combined satellite images taken at different times of the year with highly detailed aerial photographs. Deep learning is used to train the system to recognise different tree species from these images.
“Recognising a tree crown is one thing, but in a densely built-up city, crowns overlap, buildings cast shadows over the images, and you have to deal with different background materials,” says Neyns. “By combining different types of images, we provide the model with sufficient information to distinguish between tree species. After all, each tree species has its own characteristics and follows a different cycle throughout the year.” This creates a sort of digital tree expert that can help identify which tree is where on a large scale.
In search of food for wild bees
Neyns then used the technology for ecological research. In Braunschweig, Germany, he mapped willow trees for research into Andrena vaga, a wild bee that is heavily dependent on willows for its pollen. By combining the tree map with other environmental factors and observations of bee nests, it was possible to predict which areas of the city provided a suitable habitat.
In a second application, he investigated the health of the city’s trees themselves. Neyns linked information on tree species to urban heat, air pollution and urban paving. This made it possible to investigate the impact these various forms of urban stress have on the annual growth cycle of different tree species.
The research thus demonstrates how satellites, aerial photographs and AI can do much more than simply count how much greenery a city has. By also knowing which species are involved, researchers can better understand which trees thrive where, how they respond to a changing climate and what role they play for other species.
This is important information for cities wishing to plant more trees as a safeguard against increasingly hot summers. “Cities that are currently engaged in large-scale reforestation in response to climate change face a choice: not just how many trees, but which species to plant where,” says Neyns. “We hope to make that information more accessible using this technology.”
PhD title: Beyond the Canopy: Deep Learning for Urban Tree Species Classification Applications in Pollinator Ecology and Tree Phenological Responses to Urban Stressors
Robbe Neyns studied Geography at the VUB and Artificial Intelligence at KU Leuven, and began his PhD at the VUB in 2020. At the international EARSeL conference in 2024, he received the Young Scientist Award for his research.
Further information:
Robbe Neyns: robbe.neyns@vub.be+32 485 58 02 88
Frans Steenhoudt
