Pl@ntNet is a participatory botanical observation platform. More information about Pl@ntNet project can be found at https://plantnet.org/. The observations in this resource are the ones for which the authors agree to share the associated pictures under a creative common licence and for which the species name is considered as valid.
The data in this occurrence resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 29 records.
This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.
The table below shows only published versions of the resource that are publicly accessible.
How to cite
Researchers should cite this work as follows:
AFFOUARD A, JOLY A, LOMBARDO J, CHAMP J, GOEAU H, CHOUET M, GRESSE H, BONNET P (2023): Pl@ntNet observations. v1.8. Pl@ntNet. Dataset/Occurrence. https://ipt.plantnet.org/resource?r=observations&v=1.8
Researchers should respect the following rights statement:
The publisher and rights holder of this work is Test Organization #1. This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.
This resource has been registered with GBIF, and assigned the following GBIF UUID: 9e22f566-96f6-4035-8d2d-ec737acfa29d. Test Organization #1 publishes this resource, and is itself registered in GBIF as a data publisher endorsed by GBIF Secretariat.
- Metadata Provider ●
- Programmer ●
Plant observations from Pl@ntNet network come from all around the world.
|Bounding Coordinates||South West [-90, -180], North East [90, 180]|
Pl@ntNet observations focus on plants.
PlantNet is a participatory botanical observation platform allowing to identify plants from photos (using deep learning) and share observations with the community. This resource contains illustrated observations explicitly shared by PlantNet users under a Creative Common license.
|Title||Pl@ntNet Observations Singapore|
|Funding||PlantNet is an open consortium founded by four French research organizations (CIRAD, Inria, INRAE, IRD) and supported by Agropolis Fondation. The two main funding resources are: (i) the annual contribution of the members of the consortium, (ii) donations from the end-users of PlantNet application (>10 million users).|
|Study Area Description||Entire world|
The personnel involved in the project:
- Joly, A., Goëau, H., Bonnet, P., Bakić, V., Barbe, J., Selmi, S., ... & Yahiaoui I., Carré J., Mouysset E., Molino J.-f., Boujemaa B., Barthélémy D., (2014). Interactive plant identification based on social image data. Ecological Informatics, 23, 22-34. https://doi.org/10.1016/j.ecoinf.2013.07.006
- Joly, A., Bonnet, P., Goëau, H., Barbe, J., Selmi, S., Champ, J., Dufour-Kowalski, S., Affouard, A., Carré, J., Molino, J.-f., Boujemaa, N., & Barthélémy D., (2016). A look inside the Pl@ntNet experience. Multimedia Systems, 22(6), 751-766. https://doi.org/10.1007/s00530-015-0462-9
- Goëau, H., Bonnet, P., Joly, A., 2017. Plant identification based on noisy web data: the amazing performance of deep learning (LifeCLEF 2017). CLEF: Conference and Labs of the Evaluation Forum, Sep 2017, Dublin, Ireland. ⟨hal-01629183⟩ https://hal.archives-ouvertes.fr/hal-01629183
- Affouard, A., Goëau, H., Bonnet, P., Lombardo, J. C., & Joly, A., (2017). Pl@ntNet app in the era of deep learning. ICLR: International Conference on Learning Representations, Apr 2017, Toulon, France. ⟨hal-01629195⟩ https://hal.archives-ouvertes.fr/hal-01629195