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BioAcoustic Index Tool: long-term biodiversity monitoring using on-sensor acoustic index calculations
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). IT Univ Copenhagen, Digital Design, Copenhagen, Denmark.ORCID iD: 0000-0003-3573-2917
IT Univ Copenhagen, Comp Sci, Copenhagen, Denmark.
2022 (English)In: Bioacoustics, ISSN 0952-4622, E-ISSN 2165-0586, Vol. 31, no 3, p. 348-378Article in journal (Refereed) Published
Abstract [en]

Acoustic indices are valuable tools for measuring and tracking changes in biodiversity. However, the method used to collect acoustic index data can be made more effective by recent developments in electronics. The current process requires recording high-quality audio in the field and computing acoustic indices in the lab. This produces vast quantities of raw audio data, which limits the time that sensors can spend in the field and complicates data processing and analysis. Additionally, most field audio recorders are unable to log the full range of contextual environmental data that would help explain short-term variations. In this paper, we present the BioAcoustic Index Tool, a smart acoustic index and environmental sensor. The BioAcoustic Index Tool computes acoustic indices as audio is captured, storing only the index information, and logs temperature, humidity, and light levels. The sensor was able to operate completely autonomously for the entire five-month duration of the field study. In that time, it recorded over 4000 measurements of acoustic complexity and diversity all while producing the same amount of data that would be used to record 3 minutes of raw audio. These factors make the BioAcoustic Index Tool well-suited for large-scale, long-term acoustic biodiversity monitoring.

Place, publisher, year, edition, pages
Taylor & Francis, 2022. Vol. 31, no 3, p. 348-378
Keywords [en]
Acoustic index, soundscape ecology, biodiversity, sensor, field recorder, open source
National Category
Physical Geography
Identifiers
URN: urn:nbn:se:mau:diva-45837DOI: 10.1080/09524622.2021.1939786ISI: 000685333400001OAI: oai:DiVA.org:mau-45837DiVA, id: diva2:1593933
Available from: 2021-09-14 Created: 2021-09-14 Last updated: 2022-12-07Bibliographically approved

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Kadish, David

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