Abstract
Information extracted from environmental sounds has been of great importance to the analysis of ecological complexity in natural ecosystems. However, the study of these sounds does not have a universal protocol for the sampling and reduction of large quantities of data that it produces. This paper proposes to use a neural network to optimize the sampling of soundscapes of three Colombian ecosystems. The neural network is trained to identify meaningful temporal windows for audio recording from previously gathered data. This method simplifies the acoustic complexity analysis.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Farina, A.: Soundscape Ecology: Principles, Patterns, Methods and Applications. Springer Science & Business Media, New York (2013)
Van Parijs, S.M., Clark, C.W., Sousa-Lima, R.S., Parks, S.E., Rankin, S., Risch, D., van Opzeeland, I.: Management and research applications of real-time and archival passive acoustic sensors over varying temporal and spatial scales. Mar. Ecol. Prog. Ser. 395, 21–36 (2009)
Aide, T.M., Corrada-Bravo, C., Campos-Cerqueira, M., Milan, C., Vega, G., Alvarez, R.: Real-time bioacoustics monitoring and automated species identification. PeerJ 1, e103 (2013)
Farina, A., Pieretti, N., Morganti, N.: Acoustic patterns of an invasive species: the red-billed leiothrix (leiothrix lutea scopoli 1786) in a Mediterranean shrubland. Bioacoustics 22(3), 175–194 (2013)
Farina, A., Pieretti, N.: Sonic environment and vegetation structure: a methodological approach for a soundscape analysis of a Mediterranean maqui. Ecol. Inform. 21, 120–132 (2014)
Sueur, J., Pavoine, S., Hamerlynck, O., Duvail, S.: Rapid acoustic survey for biodiversity appraisal. PloS one 3(12), e4065 (2008)
Joo, W., Gage, S.H., Kasten, E.P.: Analysis and interpretation of variability in soundscapes along an urban-rural gradient. Landscape Urban Plann. 103(3), 259–276 (2011)
Pieretti, N., Duarte, M., Sous-Lima, R., Rodrigues, M., Young, R., Farina, A.: Determining temporal sampling schemes for passive acoustic studies in different tropical ecosystems. Trop. Conserv. Sci. 8(1), 215–234 (2015)
Farina, A., Pieretti, N., Piccioli, L.: The soundscape methodology for long-term bird monitoring: a Mediterranean Europe case-study. Ecol. Inform. 6(6), 354–363 (2011)
Acknowledgment
Authors would like to acknowledge the cooperation of all partners within the Center of Excellence and Appropriation on the Internet of Things (Centro de Excelencia y Apropiación en Internet de las Cosas, CEA-IoT). Authors would also like to thank all institutions that supported this work: the Colombian Ministry for the Information and Communication Technologies (Ministerio de Tecnologías de la Información y las Comunicaciones - MinTIC), and the Colombian Administrative Department of Science, Technology and Innovation (Departamento Administrativo de Ciencia, Tecnología e Innovación - Colciencias) through the National Trust for Funding Science, Technology and Innovation Francisco José de Caldas (Fondo Nacional de Financiamiento para la Ciencia, la Tecnología y la Innovación Francisco José de Caldas), under project ID: FP44842-502-2015.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Quiroz, L., Gómez, J., Agudelo, O., Tobón, L. (2017). Intelligent Sampling for Colombian Soundscapes Using an Artificial Neural Network. In: Figueroa-García, J., López-Santana, E., Villa-Ramírez, J., Ferro-Escobar, R. (eds) Applied Computer Sciences in Engineering. WEA 2017. Communications in Computer and Information Science, vol 742. Springer, Cham. https://doi.org/10.1007/978-3-319-66963-2_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-66963-2_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66962-5
Online ISBN: 978-3-319-66963-2
eBook Packages: Computer ScienceComputer Science (R0)