Description
Enregistrements de données
Les données de cette ressource occurrence ont été publiées sous forme dune Archive Darwin Core (Darwin Core Archive ou DwC-A), le format standard pour partager des données de biodiversité en tant quensemble dun ou plusieurs tableurs de données. Le tableur de données du cœur de standard (core) contient 13 880 enregistrements.
1 tableurs de données dextension existent également. Un enregistrement dextension fournit des informations supplémentaires sur un enregistrement du cœur de standard (core). Le nombre denregistrements dans chaque tableur de données dextension est illustré ci-dessous.
Cet IPT archive les données et sert donc de dépôt de données. Les données et métadonnées de la ressource sont disponibles pour téléchargement dans la section téléchargements. Le tableau des versions liste les autres versions de chaque ressource rendues disponibles de façon publique et permet de tracer les modifications apportées à la ressource au fil du temps.
Versions
Le tableau ci-dessous naffiche que les versions publiées de la ressource accessibles publiquement.
Comment citer
Les chercheurs doivent citer cette ressource comme suit:
D'hondt B, Steen F, Neukermans A, Adriaens T, Dalby L, Gillespie M A, Mellerup K A, Høye T T, Bonnet P, Joly A, Govaert S (2026). IAS pilot - Observations of alien plant species using a vehicle-mounted camera system in Flanders (Belgium). Version 1.1. Research Institute for Nature and Forest (INBO). Occurrence dataset. https://ipt.inbo.be/resource?r=ias-pilot-be&v=1.1
Droits
Les chercheurs doivent respecter la déclaration de droits suivante:
L’éditeur et détenteur des droits de cette ressource est Research Institute for Nature and Forest (INBO). En vertu de la loi, léditeur a abandonné ses droits par rapport à ces données et les a dédié au Domaine Public (CC0 1.0). Les utilisateurs peuvent copier, modifier, distribuer et utiliser ces travaux, incluant des utilisations commerciales, sans aucune restriction.
Enregistrement GBIF
Cette ressource a été enregistrée sur le portail GBIF, et possède lUUID GBIF suivante : 9c85f295-cc92-473c-969a-bb5d3eccfd0b. Research Institute for Nature and Forest (INBO) publie cette ressource, et est enregistré dans le GBIF comme éditeur de données avec lapprobation du Belgian Biodiversity Platform.
Mots-clé
Occurrence; CamAlien; invasive species; alien species; non-native species; IAS; plants
Contacts
- Fournisseur Des Métadonnées ●
- Créateur ●
- Personne De Contact
https://orcid.org/0000-0002-1330-1457
- Créateur
- Créateur
- Créateur
- Fournisseur Des Métadonnées ●
- Créateur
- Fournisseur Des Métadonnées ●
- Créateur
- Créateur
- Fournisseur Des Métadonnées ●
- Créateur
- Fournisseur Des Métadonnées ●
- Créateur
Couverture géographique
Flanders, Belgium
| Enveloppe géographique | Sud Ouest [50,705, 4,216], Nord Est [51,072, 4,983] |
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Couverture taxonomique
6 non-native species of vascular plants
| Genus | Reynoutria sp. |
|---|---|
| Species | Ailanthus altissima, Impatiens glandulifera, Robinia pseudoacacia, Rosa rugosa |
Couverture temporelle
| Date de début / Date de fin | 2024-07-18 / 2024-09-09 |
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Données sur le projet
Biodiversa+ monitoring pilots aim to facilitate the harmonisation of biodiversity monitoring at a transnational level, by testing common protocols and new technologies. The Biodiversa+ IAS pilot project (2023-2027) implemented the monitoring of invasive alien plants using a vehicle-mounted camera system in various countries across Europe.
| Titre | Monitoring Invasive Alien Species with image-based methods |
|---|---|
| Identifiant | IAS pilot |
| Financement | Biodiversa+, the European Biodiversity Partnership supporting excellent research on biodiversity with an impact on policy and society. Biodiversa+ was jointly developed by BiodivERsA and the European Commission as part of the EU Biodiversity Strategy 2030. |
| Description du domaine détude / de recherche | Europe |
| Description du design | During several field seasons of the project, the CamAlien camera system (AI Lab, Denmark) was mounted on vehicles to capture images of the vegetation along linear transport infrastructure. Typically, this system was mounted on a car for the monitoring of roadside vegetation. The system was also tested on other types of vehicles (e.g., boats, trains). Plant species were then identified from the images using species recognition algorithms (Pl@ntNet). The focus was specifically on invasive alien plants, in the context of large-scale surveys, rapid detection, and support of species management. This pilot study was conducted in 11 countries across Europe. |
Les personnes impliquées dans le projet:
- Auteur
Méthodes déchantillonnage
The CamAlien system essentially is a camera mounted on a moving car. The system continuously takes photos while driving, even at highway speeds. Images are anonymised for GDPR compliance and analysis is powered by the Pl@ntNet API, which returns species confidence scores. The software applies adaptive recording based on speed, and a human observer is able to tag plant sightings on the go, helping to build a better training set for the image recognition models.
| Etendue de létude | The study aimed to detect a set of predetermined invasive plant species in roadside verges on a regional scale during the field season of several consecutive years. |
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| Contrôle qualité | The species recognition algorithm (Pl@ntNet) returned a confidence value for each identification of a plant species in an image. A threshold value above which a confidence score is considered accurate was determined through expert validation and statistical modelling. Expert botanists annotated a subset of images with a range of confidence scores for presence/absence of the classified species. Presence/absence was then modelled as a binary response in a logistic GLM (General Linear Model) against confidence score. The confidence score providing a 50% probability of presence was then selected as threshold value. The images resulting from this filtering process were not all individually reviewed. |
Description des étapes de la méthode:
- Partners from the project consortium defined the set of target species (invasive alien plant species of interest), and agreed on a generic sampling plan for the coming field season.
- The CamAlien camera system was mounted on a vehicle.
- The vehicle was driven along the road infrastructure, with the CamAlien system running.
- The resulting images were shared with the lead partner (Aarhus University), for storage and first-level edits.
- The images were transferred to Pl@ntNet, which returned classifications (identifications) of the target species in each of the images.
- The returned data were processed, by filtering on the confidence level threshold, or any other step deemed necessary to increase reliability.
Citations bibliographiques
- Dyrmann M, Skovsen SK, Christiansen PH et al. (2024) High-speed camera system for efficient monitoring of invasive plant species along roadways. F1000Research 2024, 13:360. https://doi.org/10.12688/f1000research.141992.2
- Espitalier V, Lombardo JC, Goëau H, Botella C, Høye T T, Dyrmann M, Bonnet P, Joly A (2025). Adapting a global plant identification model to detect invasive alien plant species in high-resolution road side images. Ecological Informatics 89. https://doi.org/10.1016/j.ecoinf.2025.103129
Métadonnées additionnelles
| Identifiants alternatifs | 9c85f295-cc92-473c-969a-bb5d3eccfd0b |
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| https://ipt.inbo.be/resource?r=ias-pilot-be |