Pla@ntNet is a free citizen-science mobile application designed to help identify plants simply by photographing them with your smartphone or uploading images via the web. Developed by a consortium of French research institutes (including CIRAD, INRAE, INRIA, and IRD) alongside the Tela Botanica network, it functions as a global collaborative database used by scientists to monitor plant biodiversity.
The app analyzes specific parts of a plant (leaves, flowers, fruits, bark, or stems) and returns a list of candidate species ranked by probability.
Users can register and submit their observations. Once validated by the community and experts, these photos are used to train the AI and help researchers track plant species distribution worldwide.
The database is organized into geographic projects (e.g., European Flora, North American Flora) and thematic groups (e.g., useful or invasive plants) to filter results and maximize accuracy. You can also default to the World Flora.
Each identified species links to a detailed profile containing distribution maps, altitude ranges, phenology data, and crowdsourced image galleries sorted by plant organ.
The AI performs best with sharp, close-up shots of a single feature (e.g., a single leaf against a clear background or a flower) rather than a blurry photo of the entire bush.
You can attach up to 4 different photos (e.g., one of the flower, one of the leaf, and one of the bark) to a single observation to give the algorithm more data.
Allowing the app to access your location helps it narrow down candidates to local flora, instantly filtering out exotic species that do not naturally grow in your area.