A researcher from the Free University of Brussels has developed artificial intelligence (AI) that can identify different tree species using satellite and aerial images. This technology can help cities create more accurate maps of their trees and biodiversity, which is especially important as the planet warms. Trees help cool urban areas, improve air quality, and support wildlife, but keeping track of them is challenging. Traditional tree inventories are often incomplete or outdated, and manually identifying thousands of trees is time-consuming. To address this, the researcher used deep learning, a type of AI that mimics the human brain's ability to recognize patterns. The system was trained using satellite images taken at different times of the year and detailed aerial photographs. This allowed the AI to learn the unique features of different tree species and how they change throughout the seasons. The researcher defended his PhD dissertation on September 9, titled "Beyond the Canopy: Deep Learning for Urban Tree Species Classification Applications in Pollinator Ecology and Tree Phenological Responses to Urban Stressors." In cities, identifying individual trees can be difficult because tree crowns often overlap, and buildings or other structures can cast shadows on images. The AI model overcomes these challenges by analyzing multiple image types and recognizing the distinct characteristics of each tree species. This creates a kind of digital "tree expert" that can identify species on a large scale. The technology has already been used in ecological research, such as mapping willow trees in Braunschweig, Germany, to study Andrena vaga, a wild bee that relies on willows for pollen. By combining the tree map with data on environmental factors and bee nest locations, researchers could predict which areas of the city were suitable habitats. In another study, the AI was used to assess the health of city trees by linking species data to factors like urban heat, air pollution, and pavement coverage. This helped scientists understand how these urban stressors affect the growth cycles of different tree species. This research shows that satellites, aerial images, and AI can do more than just measure the amount of greenery in a city. Knowing which tree species are present and how they respond to environmental changes is crucial for urban planning. As cities look to plant more trees to combat rising temperatures, the choice of species and their placement becomes increasingly important. The researcher hopes this technology will make it easier for cities to make informed decisions about urban greening and biodiversity protection.