Robotic monitoring of Alpine screes: a dataset from the EU Natura2000 habitat 8110 in the Italian Alps.


Journal

Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192

Informations de publication

Date de publication:
01 12 2023
Historique:
received: 11 07 2023
accepted: 17 11 2023
medline: 4 12 2023
pubmed: 2 12 2023
entrez: 1 12 2023
Statut: epublish

Résumé

The surveying of European Union (EU) Annex I habitat "8110 - Siliceous scree of the montane to snow levels (Androsacetalia alpinae and Galeopsietalia ladani)" is generally executed by humans. However, robots could increase human monitoring capabilities. To this end, we collected information on this habitat employing the quadrupedal robot ANYmal C. These data include videos of eight different typical or early warning species. Additionally, data on four relevés are provided. These consist, for instance, of the robot state, and videos and pictures collected to evaluate the habitat conservation status. The aim of this dataset is to help researchers in a variety of fields. For instance, information on plant species collected by the robot can be utilized to develop new procedures and new metrics to assess the habitat conservation status or to train neural networks for plant classification. On the other hand, engineers can use robot state information to validate their algorithms. This database is publicly available in the provided Zenodo repository.

Identifiants

pubmed: 38040689
doi: 10.1038/s41597-023-02764-1
pii: 10.1038/s41597-023-02764-1
pmc: PMC10692210
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

855

Subventions

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

Sci Rep. 2019 Nov 6;9(1):16087
pubmed: 31695108
Sci Data. 2023 Jun 27;10(1):418
pubmed: 37369670
Sci Data. 2023 Dec 1;10(1):855
pubmed: 38040689

Auteurs

Franco Angelini (F)

Centro di Ricerca ''Enrico Piaggio", and Dipartimento di Ingegneria dell'Informazione, Università di Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy. frncangelini@gmail.com.

Mathew J Pollayil (MJ)

Centro di Ricerca ''Enrico Piaggio", and Dipartimento di Ingegneria dell'Informazione, Università di Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy.

Barbara Valle (B)

Università degli Studi di Milano, Department of Biosciences, Via Celoria 26, 20133, Milano, Italy.
Department of Life Sciences, Università degli Studi di Siena, Via A. Moro 2, 53100, Siena, Italy.
NBFC, National Biodiversity Future Center, Palermo, Italy.

Marina Serena Borgatti (MS)

Università degli Studi di Milano, Department of Biosciences, Via Celoria 26, 20133, Milano, Italy.

Marco Caccianiga (M)

Università degli Studi di Milano, Department of Biosciences, Via Celoria 26, 20133, Milano, Italy.

Manolo Garabini (M)

Centro di Ricerca ''Enrico Piaggio", and Dipartimento di Ingegneria dell'Informazione, Università di Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy.

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Classifications MeSH