Biogeosciences
Biogeosciences
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Articles | Volume 21, issue 11
Articles | Volume 21, issue 11
https://doi.org/10.5194/bg-21-2909-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-21-2909-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 21, issue 11
Research article
 | 
14 Jun 2024
Research article |  | 14 Jun 2024

From simple labels to semantic image segmentation: leveraging citizen science plant photographs for tree species mapping in drone imagery

Salim Soltani, Olga Ferlian, Nico Eisenhauer, Hannes Feilhauer, and Teja Kattenborn

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Short summary
In this research, we developed a novel method using citizen science data as alternative training data for computer vision models to map plant species in unoccupied aerial vehicle (UAV) images. We use citizen science plant photographs to train models and apply them to UAV images. We tested our approach on UAV images of a test site with 10 different tree species, yielding accurate results. This research shows the potential of citizen science data to advance our ability to monitor plant species.
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