Cyprus is tackling its climate crisis head-on with groundbreaking research that combines deep learning and high-resolution aerial imagery to create a cutting-edge tree identification system. Developed by researchers from The Cyprus Institute, the University of Copenhagen, and the Laboratory of Climate and Environmental Sciences in France, this study is a game-changer in forest management and environmental monitoring.
The study’s goal is clear: establish a reliable way to count and map trees in Cyprus, a crucial task for effective forest management. With extreme heat, drought, and forest fires becoming more frequent, understanding the true extent of tree cover is vital for reducing greenhouse gas emissions and ensuring sustainable ecosystems.
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At the heart of the research is a deep-learning neural network model, trained specifically on Cyprus’ unique data. This model was tested across diverse landscapes, including the Troodos National Forest Park, the Athalassa Forest Park, and a residential area in Aglantzia. The result? An accurate map of nearly 1 million trees over an area of 107 km², with tree crowns precisely cataloged. This gives Cyprus its first comprehensive tree inventory, crucial for estimating forest biomass, carbon absorption, and overall forest health.
This AI-powered system arrives at a critical time. Cyprus, located in the Eastern Mediterranean, faces significant climate change impacts, including forest fires and desertification. Until now, the island lacked a system to track individual trees or monitor forest health, hindering efforts to assess its carbon balance and implement effective mitigation strategies. This research fills that gap, providing the data needed for informed decision-making in forest management and reforestation.
Beyond tree counting, the system offers insights into the effects of forest fires, helps identify burned areas, and tracks endemic tree species across Cyprus’ mountains. These insights will aid foresters and government agencies in making informed decisions about conservation and restoration efforts.
As part of the Horizon Europe Edu4Climate program, this work supports the EU’s target of reducing greenhouse gas emissions by 55% by 2030, with forests playing a key role in carbon sequestration. The study could position Cyprus as a leader in forest carbon monitoring, contributing to the EU’s climate goals.
This pioneering research is particularly important for Cyprus, where tree cover is not limited to forests but extends into urban and agricultural areas. By applying machine learning models to high-resolution airborne imagery, the researchers achieved impressive accuracy—90% for estimating tree crown areas and 93% for tree counts. These results were validated by comparing them to global tree cover maps, such as those produced by Copernicus.
In Cyprus, where forest density is low and many trees are outside forested areas, traditional monitoring methods are less effective. By using deep learning to process aerial imagery, the researchers have created a scalable and accurate solution that can be applied nationwide. This lays the foundation for a much-needed national tree inventory that will have a significant impact on both local and global efforts to address the climate crisis.
This research not only provides essential data for carbon accounting but also marks a turning point in forest management for Cyprus, equipping the country with the tools to face climate change challenges. Its broader implications offer a model that could be replicated in other regions facing similar environmental threats.
This is more than just data collection—it’s about turning knowledge into action. With trees playing a pivotal role in combating climate change, this research provides a clear path for protecting and restoring Cyprus’ natural environment, ensuring its resilience in the face of a warming world.
