Evaluating the use of automated plant identification tools in biodiversity monitoring—a case study in Switzerland
Smartphone apps and citizen science platforms have enabled large-scale public contributions to biodiversity monitoring, with image recognition readily allowing automated species identification. Yet, practical evaluations of the best use of such identification tools for nationwide plant community mon...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Ecological Informatics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1574954125003255 |
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| Summary: | Smartphone apps and citizen science platforms have enabled large-scale public contributions to biodiversity monitoring, with image recognition readily allowing automated species identification. Yet, practical evaluations of the best use of such identification tools for nationwide plant community monitoring remain limited. We conducted a stratified field survey covering diverse habitats and different growth forms at 151 sites in all biogeographic regions of Switzerland, collecting > 5000 labelled photos of different plant parts for about 20% of the Swiss Flora. We assessed the performance of leading, publicly available identification services, differing in geographic scope and taxonomic resolution. Up to 85% of species observations were correctly identified when multiple images were supplied. While all identification providers correctly identified > 90% of the species at least once, we found models with a narrower geographic scope and coarser taxonomic resolution to reach higher identification accuracy. Identifications of photographs depicting multiple plant parts were often more successful than those of images focusing on single plant parts. While manual control remains indispensable for high-quality data, involving automated identification services can boost efficiency in compiling standardised floristic data, especially when (1) several images are taken, (2) an identification provider with matching taxonomic concepts and scope is selected, and (3) auxiliary information such as environmental context is considered. |
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| ISSN: | 1574-9541 |