Descripción
Registros
Los datos en este recurso de registros biológicos han sido publicados como Archivo Darwin Core(DwC-A), el cual es un formato estándar para compartir datos de biodiversidad como un conjunto de una o más tablas de datos. La tabla de datos del core contiene 13.880 registros.
también existen 1 tablas de datos de extensiones. Un registro en una extensión provee información adicional sobre un registro en el core. El número de registros en cada tabla de datos de la extensión se ilustra a continuación.
Este IPT archiva los datos y, por lo tanto, sirve como repositorio de datos. Los datos y los metadatos del recurso están disponibles para su descarga en la sección descargas. La tabla versiones enumera otras versiones del recurso que se han puesto a disposición del público y permite seguir los cambios realizados en el recurso a lo largo del tiempo.
Versiones
La siguiente tabla muestra sólo las versiones publicadas del recurso que son de acceso público.
¿Cómo referenciar?
Los usuarios deben citar este trabajo de la siguiente manera:
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
Derechos
Los usuarios deben respetar los siguientes derechos de uso:
El publicador y propietario de los derechos de este trabajo es Research Institute for Nature and Forest (INBO). En la medida de lo posible según la ley, el publicador ha renunciado a todos los derechos sobre estos datos y los ha dedicado al Dominio público (CC0 1.0). Los usuarios pueden copiar, modificar, distribuir y utilizar la obra, incluso con fines comerciales, sin restricciones.
Registro GBIF
Este recurso ha sido registrado en GBIF con el siguiente UUID: 9c85f295-cc92-473c-969a-bb5d3eccfd0b. Research Institute for Nature and Forest (INBO) publica este recurso y está registrado en GBIF como un publicador de datos avalado por Belgian Biodiversity Platform.
Palabras clave
Occurrence; CamAlien; invasive species; alien species; non-native species; IAS; plants
Contactos
- Proveedor De Los Metadatos ●
- Originador ●
- Punto De Contacto
https://orcid.org/0000-0002-1330-1457
- Originador
- Originador
- Originador
- Proveedor De Los Metadatos ●
- Originador
- Proveedor De Los Metadatos ●
- Originador
- Originador
- Proveedor De Los Metadatos ●
- Originador
- Proveedor De Los Metadatos ●
- Originador
Cobertura geográfica
Flanders, Belgium
| Coordenadas límite | Latitud Mínima Longitud Mínima [50,705, 4,216], Latitud Máxima Longitud Máxima [51,072, 4,983] |
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Cobertura taxonómica
6 non-native species of vascular plants
| Género | Reynoutria sp. |
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| Especie | Ailanthus altissima, Impatiens glandulifera, Robinia pseudoacacia, Rosa rugosa |
Cobertura temporal
| Fecha Inicial / Fecha Final | 2024-07-18 / 2024-09-09 |
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Datos del proyecto
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.
| Título | Monitoring Invasive Alien Species with image-based methods |
|---|---|
| Identificador | IAS pilot |
| Fuentes de Financiación | 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. |
| Descripción del área de estudio | Europe |
| Descripción del diseño | 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. |
Personas asociadas al proyecto:
- Autor
Métodos de muestreo
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.
| Área de Estudio | 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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| Control de Calidad | 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. |
Descripción de la metodología paso a paso:
- 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.
Referencias bibliográficas
- 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
Metadatos adicionales
| Identificadores alternativos | 9c85f295-cc92-473c-969a-bb5d3eccfd0b |
|---|---|
| https://ipt.inbo.be/resource?r=ias-pilot-be |