Robotic monitoring of grasslands: a dataset from the EU Natura2000 habitat 6210* in the central Apennines (Italy).


Journal

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

Informations de publication

Date de publication:
27 06 2023
Historique:
received: 05 12 2022
accepted: 14 06 2023
medline: 29 6 2023
pubmed: 28 6 2023
entrez: 27 6 2023
Statut: epublish

Résumé

Despite the remarkable growth of the global market for robotics, robotic monitoring of habitats is still an understudied topic. This is true, among others, for the species-rich EU Annex I habitat "6210 - Semi-natural grasslands and scrubland facies on calcareous substrates". This habitat is typically surveyed by human operators. In this work, we present a dataset concerning relevés performed through the quadrupedal robot ANYmal C. The dataset contains information from three plots, which include the robot state, videos, and images acquired to assess the habitat conservation status. Additionally, a collection of videos and pictures about two typical and one early warning species of habitat 6210 is also presented. This database is publicly available in the provided Zenodo repository and will aid researchers in several fields. Robot state information can be used by engineers to validate their algorithms, while data gathered by the robot can be used to design new methodologies and new metrics to assess the habitat conservation status or train/test classifiers (e.g. neural networks) for plant classification.

Identifiants

pubmed: 37369670
doi: 10.1038/s41597-023-02312-x
pii: 10.1038/s41597-023-02312-x
pmc: PMC10300093
doi:

Types de publication

Dataset Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

418

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

Conserv Biol. 2018 Feb;32(1):109-115
pubmed: 28755447
Sci Rep. 2019 Nov 6;9(1):16087
pubmed: 31695108
Sci Data. 2023 Jun 27;10(1):418
pubmed: 37369670

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.

Federica Bonini (F)

Department of Agricultural, Food and Environmental Sciences, University of Perugia, Borgo XX giugno 74, I-06121, Perugia, Italy.

Daniela Gigante (D)

Department of Agricultural, Food and Environmental Sciences, University of Perugia, Borgo XX giugno 74, I-06121, Perugia, 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.

Classifications MeSH