Robotic monitoring of European habitats: a labeled dataset for plant detection in Annex I habitats of Italy

The present data descriptor presents a dataset designed for the detection of plant species in various habitats of the European Union. This dataset is based on images captured using multiple different hardware including quadrupedal robot ANYmal C, referring to ecologically important species to assess the presence and conservation status in Annex I habitats 2110, 2120, 6210*, 8110, 8120, and 9210*. Plant scientists and robotic engineers gathered the data in key Italian protected areas and labeled it using YOLOtxt format. Researchers in vegetation science, habitat monitoring, robotics, machine learning, and biodiversity conservation can access the dataset through Zenodo. The ultimate goal of this collaborative effort was to create a dataset that can be used to train artificial intelligence models to assess parameters that enable robotic habitat monitoring. The availability of this dataset may enhance future studies and conservation initiatives for Annex I habitats inside and outside the Natura 2000 network. The dataset and the methods used to obtain it are fully described, highlighting the significance of interdisciplinary cooperation in habitat monitoring.

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Publication Details

Journal
Scientific Data
Published
2025-05-20
DOI
https://doi.org/10.1038/s41597-025-05182-7
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.75

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article

Robotic monitoring of European habitats: a labeled dataset for plant detection in Annex I habitats of Italy

Marina Serena Borgatti, Maria Carmela Caria, Daniela Gigante, Manolo Garabini et al.
1 citations
Scientific Data
Smart Agriculture and AI
1.75
article

Robotic monitoring of European habitats: a labeled dataset for plant detection in Annex I habitats of Italy

Marina Serena Borgatti, Maria Carmela Caria, Daniela Gigante, Manolo Garabini, Franco Angelini, Simonetta Bagella, Emanuele Fanfarillo, Michele Pierallini, Tiberio Fiaschi, Leopoldo de Simone, Giovanni Rivieccio, Anna Grassi, Marco Caccianiga, Barbara Valle, Federica Bonini, Simona Maccherini, Claudia Angiolini, Simone Tolomei, Davide De Benedittis, Giovanni Di Lorenzo, Agnese Denaro
article en
1 citations

Abstract

The present data descriptor presents a dataset designed for the detection of plant species in various habitats of the European Union. This dataset is based on images captured using multiple different hardware including quadrupedal robot ANYmal C, referring to ecologically important species to assess the presence and conservation status in Annex I habitats 2110, 2120, 6210*, 8110, 8120, and 9210*. Plant scientists and robotic engineers gathered the data in key Italian protected areas and labeled it using YOLOtxt format. Researchers in vegetation science, habitat monitoring, robotics, machine learning, and biodiversity conservation can access the dataset through Zenodo. The ultimate goal of this collaborative effort was to create a dataset that can be used to train artificial intelligence models to assess parameters that enable robotic habitat monitoring. The availability of this dataset may enhance future studies and conservation initiatives for Annex I habitats inside and outside the Natura 2000 network. The dataset and the methods used to obtain it are fully described, highlighting the significance of interdisciplinary cooperation in habitat monitoring.

Scientific DataVol. 12(1)
University of Siena (IT), Piaggio (Italy) (IT), University of Sassari (IT), University of Milan (IT), University of Perugia (IT), University of Palermo (IT)
Dipartimenti di Eccellenza, European Commission, Ministero dell’Istruzione, dell’Università e della Ricerca
Life in Land
Openalex Percentile: Top 15%
Smart Agriculture and AI
1.75
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