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Data for Early Detection of an Invasive Alien Plant (Phragmites australis) Using Unoccupied Aerial Vehicles and Artificial Intelligence
| Description: | This dataset contains UAV RGB imagery and georeferenced common reed point annotations in Parc national des Îles-de-Boucherville, Quebec, Canada. It also includes an area of interest layer for each zone mapped, and a grid layer used to export data for the classification model. |
| Authors: | Caron-Guay, Antoine; University of Montreal; Institut de recherche en biologie végétale;  0009-0000-6197-8625Laliberté, Etienne; University of Montreal; Institut de recherche en biologie végétale; 0000-0002-3167-2622Germain, Mickaël; Université de Sherbrooke; 0000-0003-1867-7530 |
| Keywords: | common reed drones invasive alien plant species Phragmites remote sensing unoccupied aerial vehicles UAV RGB imagery RGB orthomosaic point annotations classification model |
| Field of Research: | Biological sciences > Ecological applications > Invasive species ecology
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| Publication Date: | 2024-08-21 |
| Publisher: | Federated Research Data Repository / dépôt fédéré de données de recherche |
| Funder: | Canada First Research Excellence Fund; PRF-2021-02 Natural Sciences and Engineering Research Council; Discovery grant; RGPIN-2019-04537 Canada Research Chairs; 950-231858 |
| URI: | https://doi.org/10.20383/103.0954 |
| Related Identifiers: |
This dataset is cited by
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| Geographic Coverage: | Place Name Parc national des Îles-de-Boucherville City Boucherville Province / Province / Territory Quebec Territory Country Canada |
| Geographic Point: | Latitude 45.587222 Longitude -73.482778 |
| Appears in Collections: | LEFO |
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Access to this dataset is subject to the following terms:
Creative Commons Public Domain Dedication (CC0 1.0) https://creativecommons.org/publicdomain/zero/1.0/
Citation
Caron-Guay, A., Laliberté, E., Germain, M. (2024). Data for Early Detection of an Invasive Alien Plant (Phragmites australis) Using Unoccupied Aerial Vehicles and Artificial Intelligence. Federated Research Data Repository. https://doi.org/10.20383/103.0954
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