Robotic monitoring of forests: a dataset from the EU habitat 9210* in the Tuscan Apennines (central Italy).
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
01 12 2023
01 12 2023
Historique:
received:
08
03
2023
accepted:
17
11
2023
medline:
4
12
2023
pubmed:
2
12
2023
entrez:
1
12
2023
Statut:
epublish
Résumé
Effective monitoring of habitats is crucial for their preservation. As the impact of anthropic activities on natural habitats increases, accurate and up-to-date information on the state of ecosystems has become imperative. This paper presents a new dataset collected from the forests located in the Tuscan Apennines (Italy) using the ANYmal robot. The dataset provides information regarding the structure and composition of the EU priority habitat 9210*. The dataset, which is publicly available through a Zenodo repository, includes photos, videos, and point clouds of the environment. This dataset is a valuable resource for the scientific community working in the field of forest ecology and conservation and has the potential to inform future research and conservation efforts on habitat 9210*. The collaboration between robotic engineers and plant scientists provides a unique perspective on the forest ecosystem and underscores the potential for interdisciplinary work in this field. This dataset constitutes an important contribution to the ongoing effort to monitor and conserve habitats globally, particularly in light of the challenges posed by global changes.
Identifiants
pubmed: 38040693
doi: 10.1038/s41597-023-02763-2
pii: 10.1038/s41597-023-02763-2
pmc: PMC10692077
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
845Subventions
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 101016970
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 101016970
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 101016970
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 101016970
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 101016970
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 101016970
Informations de copyright
© 2023. The Author(s).
Références
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pubmed: 38040693