Looking for the -scape in the sound: Discriminating soundscapes categories in the Sonoran Desert using indices and clustering
Soundscapes are increasingly used as innovative entry doors in environmental studies. Facing huge libraries of sound files which cannot be processed manually, acoustic indices provide an overview to the information contained in them, as well as to allow for automatic processing. Studies dealing with...
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/04323e06b5be4ea98ba599f112a9c0c9 |
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| Sumario: | Soundscapes are increasingly used as innovative entry doors in environmental studies. Facing huge libraries of sound files which cannot be processed manually, acoustic indices provide an overview to the information contained in them, as well as to allow for automatic processing. Studies dealing with such indices have, however, focused more on specific topics or indices than on the overall characteristics of the soundscapes they were analyzing. The aim of this paper is to propose a holistic approach to soundscapes. Our hypothesis is that sufficient number and variety of indices can help frame the characteristics of sound environments and that the use of clustering algorithms allows us to group them in families and study the distribution of those across space and time, revealing a geography that will not necessarily coincide with the obvious landscape/visual geography. To demonstrate this point, we have run indices analysis and classification on a soundscapes database recorded in the Sonoran Desert region (Southeastern Arizona, USA). The results show that sound indices reveal temporal variations and patterns of soundscapes and point out to sometimes surprising similarities between otherwise different environments. As sound indices capture a wealth of information which characterizes the environment at a given place and time, they could be used as proxies to continuous monitoring without having to store extreme amounts of data. |
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