DroneNet4Beetles - A shared drone data initiative for the early detection of spruce bark beetle outbreaks
KEY POINTS- Join a growing network sharing drone-based bark beetle data!
Project overview
Participants
More related research
Short summary
Spruce bark beetle (Ips typographus) outbreaks are reshaping European forests, yet no shared, well-curated database exists to support early detection research. We are aiming to fill this gap by inviting contributions of drone imagery and field-verified infestation data to a common database.
What is DroneNet4Beetles?
DroneNet4Beetles will establish an European level network connecting researchers and create a shared library of drone imagery from spruce stands infested by bark beetles. It will provide harmonised, well-documented ground-truth data, serve as a benchmark for early detection using shared and reproducible algorithms, and offer a platform for joint research on remote-sensing-based early detection methods and operational frameworks.
Data we need
We welcome published and unpublished datasets. You do not need a “perfect” dataset – heterogeneous studies are crucial for realistic benchmarks.
We seek drone imagery over infested Norway spruce stands, preferably as time series and including at least one acquisition during the green-attack phase. Data from any sensor type (RGB, multispectral, hyperspectral, thermal or LiDAR) are suitable, provided they are accompanied by field information confirming infestation status, such as tree-level labels, timing of attack, infestation stage, and swarming or population monitoring records.
Why contribute?
Increase impact: Your drone campaigns become part of a curated reference database used by many groups.
Co-author benchmark papers: Contributors invited to multi-author studies and data description papers.
Shape standards: Help define community protocols for ground truth, pre-processing, and metrics.
Boost collaboration: Find partners for joint projects and showcase your sites and methods.
Support management: Provide robust tools for agencies responding to outbreaks.
How to get involved
Please email a brief description of your dataset(s), including location, years, sensor type and context. We will then agree what can be shared, including licensing and acknowledgements, provide templates and guidance for metadata and imagery preparation, and invite you to contribute to benchmarking activities such as designing tasks, defining metrics and co-authoring publications.
The network includes contributors from:
Langning Huo, Luiz H.E. Cosimo
Swedish University of Agricultural Sciences, Sweden
Per-Ola Olsson
Lund University, Sweden
Caroline Greiser
Stockholm University, Sweden
Eija Honkavaara, Roope Näsi
Finnish Geospatial Research Institute, Finland
Massimo Faccoli, Aurora Bozzini
University of Padua, Italy
Lucie Kupková, Salma Bijou
Charles University, Czech Republic
Jakuš Rastislav
Slovak Academy of Sciences, Slovakia
Jan Komárek, Tomáš Klouček
Czech University of Life Sciences Prague, Czech Republic
