Evidence map›Paper›PMID 38040693›Full record

ArticleScientific data2023

Robotic monitoring of forests: a dataset from the EU habitat 9210* in the Tuscan Apennines (central Italy).

Mathew J Pollayil, Franco Angelini, Leopoldo de Simone, Emanuele Fanfarillo, Tiberio Fiaschi, Simona Maccherini, Claudia Angiolini, Manolo Garabini

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Mathew J PollayilCentro di Ricerca "Enrico Piaggio", and Dipartimento di Ingegneria dell'Informazione, Universitá di Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy.ORCID 0000-0001-9526-0662
Franco AngeliniCentro di Ricerca "Enrico Piaggio", and Dipartimento di Ingegneria dell'Informazione, Universitá di Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy. frncangelini@gmail.com.ORCID 0000-0003-2559-9569
Leopoldo de SimoneDepartment of Life Sciences, University of Siena, Via Mattioli, 4, 53100, Siena, Italy.ORCID 0000-0002-3055-136X
Emanuele FanfarilloDepartment of Life Sciences, University of Siena, Via Mattioli, 4, 53100, Siena, Italy.ORCID 0000-0001-5742-737X
Tiberio FiaschiDepartment of Life Sciences, University of Siena, Via Mattioli, 4, 53100, Siena, Italy.ORCID 0000-0003-0403-2387
Simona MaccheriniDepartment of Life Sciences, University of Siena, Via Mattioli, 4, 53100, Siena, Italy.ORCID 0000-0002-2025-7546
Claudia AngioliniDepartment of Life Sciences, University of Siena, Via Mattioli, 4, 53100, Siena, Italy.ORCID 0000-0002-9125-764X
Manolo GarabiniCentro di Ricerca "Enrico Piaggio", and Dipartimento di Ingegneria dell'Informazione, Universitá di Pisa, Largo Lucio Lazzarino 1, 56122, Pisa, Italy.ORCID 0000-0002-5873-3173

Funding

EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 101016970
6 · The paper itself

Abstract

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.

Indexed as

ForestsRoboticsConservation of Natural ResourcesEcosystemItaly

Identifiers

PMID38040693
PMCPMC10692077

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.