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

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          Abstract

          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.

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          Plant species richness: the world records

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            Building the European Union’s Natura 2000 network

            In the second half of the 20th Century there was a growing awareness of environmental problems, including the loss of species and habitats, resulting in many national and international initiatives, including the creation of organisations, such as the IUCN, treaties and conventions, such as Ramsar and the Berne Convention, and the establishment of networks of protected areas. Natura 2000 is a network of sites in the European for selected species and habitats listed in the 1979 Birds Directive and the 1992 Habitats Directive. Under the Habitats Directive a series of seminars and other meetings have been held with agreed criteria to ensure a coherent network. Despite both scientific and political difficulties the network is now nearing completion.
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              Plot sizes used for phytosociological sampling of European vegetation

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                Author and article information

                Contributors
                frncangelini@gmail.com
                Journal
                Sci Data
                Sci Data
                Scientific Data
                Nature Publishing Group UK (London )
                2052-4463
                27 June 2023
                27 June 2023
                2023
                : 10
                : 418
                Affiliations
                [1 ]GRID grid.5395.a, ISNI 0000 0004 1757 3729, Centro di Ricerca “Enrico Piaggio”, and Dipartimento di Ingegneria dell’Informazione, , Università di Pisa, ; Largo Lucio Lazzarino 1, 56122 Pisa, Italy
                [2 ]GRID grid.9027.c, ISNI 0000 0004 1757 3630, Department of Agricultural, Food and Environmental Sciences, , University of Perugia, ; Borgo XX giugno 74, I-06121 Perugia, Italy
                Author information
                http://orcid.org/0000-0003-2559-9569
                http://orcid.org/0000-0001-9526-0662
                http://orcid.org/0000-0001-9757-3697
                http://orcid.org/0000-0003-1787-5164
                http://orcid.org/0000-0002-5873-3173
                Article
                2312
                10.1038/s41597-023-02312-x
                10300093
                37369670
                91c6ffbc-98cf-4a24-9ef9-f7bf883577ae
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 5 December 2022
                : 14 June 2023
                Funding
                Funded by: Ministry of University and Research (MUR) as part of the PON 2014-2021 “Research and Innovation” resources – Green Action - DM MUR 1062/2021
                Funded by: FundRef https://doi.org/10.13039/100010661, EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020);
                Award ID: 101016970
                Award ID: 101016970
                Award ID: 101016970
                Award ID: 101016970
                Award Recipient :
                Categories
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                © Springer Nature Limited 2023

                electrical and electronic engineering,grassland ecology,biodiversity

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