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A dataset of acoustic measurements from soundscapes collected worldwide during the COVID-19 pandemic

  • Silent Cities project consortium
  • Université Toulouse Jean Jaurès
  • CNRS
  • University of Stirling
  • Sorbonne Université
  • University of Bristol
  • Aix-Marseille Université
  • Oregon State University
  • UMR6613 LAUM (Laboratoire d’Acoustique de l’Université du Mans)
  • University of Lisbon
  • University of Washington
  • Newcastle University
  • The University of the West Indies
  • Fauna & Flora International
  • Université du Québec à Trois-Rivières
  • Communauté de communes de Serre-Ponçon
  • Groupe Chiroptéres Languedoc-Roussillon
  • University of Alcalá
  • Vall d’Aro
  • Pôle Aves Natagora
  • Swiss Federal Institute of Technology Zurich
  • University of Toronto
  • Wildlife Acoustics Inc.
  • Brown University
  • University of East London
  • Universidad Javeriana
  • Field Museum of Natural History
  • Western Washington University
  • Universidad Autónoma de Madrid
  • Cornell University
  • Université Paris Nanterre
  • UNEP-WCMC (UN Environment Programme World Conservation Monitoring Centre)
  • École Supérieure d’Art d’Aix-en-Provence
  • University of Évora
  • Universidad Nacional Autónoma de México
  • Parks Canada
  • University of Freiburg
  • University of Porto
  • Universidade de Lisboa, Portugal
  • University of Natural Resources and Life Sciences, Vienna
  • Purdue University
  • Deakin University

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)
37 Downloads (Pure)

Abstract

Political responses to the COVID-19 pandemic led to changes in city soundscapes around the globe. From March to October 2020, a consortium of 261 contributors from 35 countries brought together by the Silent Cities project built a unique soundscape recordings collection to report on local acoustic changes in urban areas. We present this collection here, along with metadata including observational descriptions of the local areas from the contributors, open-source environmental data, open-source confinement levels and calculation of acoustic descriptors. We performed a technical validation of the dataset using statistical models run on a subset of manually annotated soundscapes. Results confirmed the large-scale usability of ecoacoustic indices and automatic sound event recognition in the Silent Cities soundscape collection. We expect this dataset to be useful for research in the multidisciplinary field of environmental sciences.
Original languageEnglish
Article number928
Number of pages16
JournalScientific Data
Volume11
Issue number1
DOIs
Publication statusPublished - Dec 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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