The Initiative

TreeAI is building an open, community-driven global database of annotated tree crowns, training deep learning models for forest monitoring at planetary scale.

The Annotation Gap

Petabytes of sub-meter imagery exist, yet labeled tree-crown datasets remain scarce — this is the gap TreeAI is closing.

Sub-meter imagery archives (bubble ∝ PB); national programmes such as Swisstopo and IGN represent many more. Annotation datasets (bubble ∝ labeled crowns). Click any bubble to view the source.

Team

Project Leads

Dr. Mirela Beloiu Schwenke

Dr. Mirela Beloiu Schwenke

Project Lead

ETH Zurich

Forest Resilience Remote Sensing AI for Forestry

Mirela Beloiu is a forest ecologist and remote sensing scientist working at the interface of ecology, geospatial data science, and artificial intelligence. She studies forest resilience under climate change by combining field observations, remote sensing, and deep learning, and develops AI-based approaches for tree species identification, forest health assessment, and mortality monitoring. With over 10 years of teaching experience, she actively fosters collaborations across academia and practice, translating large-scale ecological data into actionable insights for sustainable, climate-resilient forest management.

Zhongyu Xia

Zhongyu Xia

Deep Learning Lead

ETH Zurich

Tree Detection Deep Learning Data Curation

Specialises in tree detection and species identification using deep learning and high-resolution remote sensing data. Her work spans model development for accurate crown-level species mapping, large-scale dataset curation and processing, and evaluating how well detection models generalise across diverse geographic regions. She is particularly interested in how monitoring species composition can enable more effective and climate-resilient forest management at scale.

Ruoyi Chen

Ruoyi Chen

Lead Developer

ETH Zurich

Web Development Deep Learning Pipelines Dataset Infrastructure

Works at the intersection of software engineering and data science, with expertise in full-stack web development, deep learning pipeline design, and large-scale geospatial dataset infrastructure. She builds research-facing systems that turn complex remote sensing workflows into accessible, reproducible tools for scientists worldwide.

Prof. Dr. Verena Griess

Prof. Dr. Verena Griess

Co-Principal Investigator

ETH Zurich

Forest Resources Management Strategic Direction

Head of the Forest Resources Management group at ETH Zurich, where her research focuses on sustainable forest management, forest economics, and ecosystem governance. She provides scientific oversight and strategic direction for the TreeAI initiative.

Dr. Martin Mokros

Dr. Martin Mokros

Co-Principal Investigator

University College London

Close-Range Sensing 3D Forest Scanning Photogrammetry

Lecturer in Earth Observation at UCL, specialising in close-range 3D remote sensing of trees using terrestrial laser scanners, drones, and photogrammetry. He co-conceived the TreeAI initiative with Mirela and continues to guide its scientific direction.

Partners

Scientific Advisory Board

ETH Zurich

Switzerland

  • Prof. Dr. Verena Griess
  • Dr. Mirela Beloiu Schwenke
  • Zhongyu Xia

WSL Swiss Federal Institute for Forest, Snow and Landscape Research

Switzerland

  • Dr. Lars Waser
  • Dr. Natalia Rehush
  • Prof. Arthur Gessler

Wuhan University

China

  • Prof. Xinlian Liang

University College London

United Kingdom

  • Dr. Martin Mokros

Norwegian Institute of Bioeconomy Research (NIBIO)

Norway

  • Dr. Stefano Puliti

University of Freiburg

Germany

  • Prof. Teja Kattenborn

University of Leipzig

Germany

  • Clemens Mosig

University of Copenhagen

Denmark

  • Yan Cheng

Collaborate

Get in Contact

Interested in contributing but not yet ready to submit a dataset? We welcome early conversations about eligibility, data format, or collaboration.

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Community

Contributors

Research groups and individuals who have contributed annotated datasets to the initiative.

Surname First Name Institute Country Research Area