Arbor Geo-Frame

🌳 Why We’re Studying Street Trees

Street trees are a crucial part of healthy cities. They improve air quality, reduce heat, support biodiversity, and make our neighbourhoods more pleasant to live in. But many cities don't have detailed, up to date maps of where their trees are or what kinds of trees grow there.

At Arbor Geo-Frame, we want to help change that, using the power of Citizen Science and Artificial Intelligence (AI) through Computer Vision.

🔍 What’s the Challenge?

Training a computer to recognise different tree species from street-level images isn’t easy. Trees vary by shape, size, and season. Shadows, camera angles, and city infrastructure add to the complexity.
To create an accurate tree recognition system, we need a large dataset of real images, with each tree carefully labelled by species and location. This is where you come in!

🤝 What You’ll Be Helping Us Do

By drawing boxes around trees and selecting their species, you’re helping us:

• Build a training dataset for AI-based tree detection.
• Improve automated urban forest mapping tools.
• Support researchers, city planners, and environmental projects that rely on accurate tree data.

Your contributions will go into a system that can one day map trees across entire cities, automatically, saving time, money, and helping communities thrive.

💡 Why It Matters

🌍 Climate Action: Urban trees are a nature-based solution to urban heat and pollution
🏙️ City Planning: Accurate tree data helps cities plan green infrastructure fairly
🧠 Science & AI: Your labels make cutting-edge machine learning possible
💚 Community Impact: Your effort contributes to healthier, greener neighborhoods

📍 Where We're Studying

Arbor Geo-Frame currently focuses on urban tree species in Ireland. This regional scope helps narrow down the likely species in each image and gives volunteers a clearer sense of what to expect. All the trees in this project are either native to Ireland or commonly planted in Irish urban landscapes. As the dataset grows, future phases of the project may expand to include other regions.

🧠 How It Works

Arbor Geo-Frame created by Abdalkarim Gharbia, a researcher at the Spatial Dynamics Lab, University College Dublin (UCD) as part of ongoing research into how artificial intelligence (AI) can support environmental sustainability in cities.

The system works by combining human expertise with machine learning. Volunteers annotate trees in pictures, creating data used to train computer vision models to recognise trees by their shape and features. These models will help cities and researchers understand urban forests at scale supporting climate adaptation, biodiversity tracking, and equitable green space planning.

Your contribution is critical. With every tree you mark, you’re helping teach machines to see the natural world more clearly.