Auto-correlations and long time memory of environment sound: The case of an Urban Park in the city of Milan (Italy)
We investigate the possible presence of ‘long time’ memory in the auto-correlations of biophonic activity of environment sound. The study is based on recordings taken at two sites located in the Parco Nord of Milan (Italy), characterized by a wooded land, rich in biodiversity and exposed to differen...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-01-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X21011572 |
| _version_ | 1819175881399074816 |
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| author | Roberto Benocci H. Eduardo Roman Alessandro Bisceglie Fabio Angelini Giovanni Brambilla Giovanni Zambon |
| author_facet | Roberto Benocci H. Eduardo Roman Alessandro Bisceglie Fabio Angelini Giovanni Brambilla Giovanni Zambon |
| author_sort | Roberto Benocci |
| collection | DOAJ |
| description | We investigate the possible presence of ‘long time’ memory in the auto-correlations of biophonic activity of environment sound. The study is based on recordings taken at two sites located in the Parco Nord of Milan (Italy), characterized by a wooded land, rich in biodiversity and exposed to different sources and degrees of anthropogenic disturbances. The audio files correspond to a three-day recording campaign (1-min recording followed by 5-min pause), from (17:00) April 30 to (17:00) May 3, 2019, which have been transformed into ecoacoustic indices time series. The following eight indices have been computed: Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI), Bio-acoustic Index (BI), Acoustic Entropy Index (H), Acoustic Richness index (AR), Normalized Difference Soundscape Index (NSDI) and Dynamic Spectral Centroid (DSC). We have grouped the indices carrying similar sound information by performing a principal component analysis (PCA). This allows us to reduce the number of variables from eight to three by retaining a large (≳80%) variance of the original variables. The time series corresponding to the reduced set of new variables have been analyzed, and both seasonal and possible long term trend components have been extracted. We find that no trends are present, i.e. the resulting time series are stationary, and the auto-correlations of the three selected PCA dimensions and associated residuals (obtained after extracting the seasonal components) can be determined. The calculations reveal the presence of a “memory” of few (≲5) hours long in the environment sound, for the two sites considered, which is quantified by the Hurst exponent, H. For Site1, we find an overall effective Hurst exponent, Hdim≃0.88, for all three dimensions, and Hres≃0.75 for the residuals. For Site2, the exponents are slightly smaller, amounting to 0.80 and 0.60, respectively. We attempt to correlate the Hurst exponents with a quality index obtained from an aural survey, aimed at determining the sound components, such as biophonies, technophonies and geophonies, at the two sites. We conclude that the higher the Hurst exponents, the higher are the periodic-structured sounds, corresponding to stronger long-term biophonic activity. We find that Site1 has a more structured environment sound than Site2, also consistent with the major presence of tall trees surrounding the location of the acoustic sensor at the former. |
| first_indexed | 2024-12-22T21:01:55Z |
| format | Article |
| id | doaj.art-74488ebb4a6443fa80fd7ce47ebb8e52 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-12-22T21:01:55Z |
| publishDate | 2022-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-74488ebb4a6443fa80fd7ce47ebb8e522022-12-21T18:12:49ZengElsevierEcological Indicators1470-160X2022-01-01134108492Auto-correlations and long time memory of environment sound: The case of an Urban Park in the city of Milan (Italy)Roberto Benocci0H. Eduardo Roman1Alessandro Bisceglie2Fabio Angelini3Giovanni Brambilla4Giovanni Zambon5Department of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy; Corresponding author.Department of Physics, University of Milano-Bicocca, Piazza delle Scienze3, 20126 Milan, ItalyDepartment of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, ItalyDepartment of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, ItalyCNR-INM, Department of Acoustics and Sensors “O.M. Corbino”, Via del Fosso del Cavaliere 100, 00133 Rome, ItalyDepartment of Earth and Environmental Sciences (DISAT), University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, ItalyWe investigate the possible presence of ‘long time’ memory in the auto-correlations of biophonic activity of environment sound. The study is based on recordings taken at two sites located in the Parco Nord of Milan (Italy), characterized by a wooded land, rich in biodiversity and exposed to different sources and degrees of anthropogenic disturbances. The audio files correspond to a three-day recording campaign (1-min recording followed by 5-min pause), from (17:00) April 30 to (17:00) May 3, 2019, which have been transformed into ecoacoustic indices time series. The following eight indices have been computed: Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI), Bio-acoustic Index (BI), Acoustic Entropy Index (H), Acoustic Richness index (AR), Normalized Difference Soundscape Index (NSDI) and Dynamic Spectral Centroid (DSC). We have grouped the indices carrying similar sound information by performing a principal component analysis (PCA). This allows us to reduce the number of variables from eight to three by retaining a large (≳80%) variance of the original variables. The time series corresponding to the reduced set of new variables have been analyzed, and both seasonal and possible long term trend components have been extracted. We find that no trends are present, i.e. the resulting time series are stationary, and the auto-correlations of the three selected PCA dimensions and associated residuals (obtained after extracting the seasonal components) can be determined. The calculations reveal the presence of a “memory” of few (≲5) hours long in the environment sound, for the two sites considered, which is quantified by the Hurst exponent, H. For Site1, we find an overall effective Hurst exponent, Hdim≃0.88, for all three dimensions, and Hres≃0.75 for the residuals. For Site2, the exponents are slightly smaller, amounting to 0.80 and 0.60, respectively. We attempt to correlate the Hurst exponents with a quality index obtained from an aural survey, aimed at determining the sound components, such as biophonies, technophonies and geophonies, at the two sites. We conclude that the higher the Hurst exponents, the higher are the periodic-structured sounds, corresponding to stronger long-term biophonic activity. We find that Site1 has a more structured environment sound than Site2, also consistent with the major presence of tall trees surrounding the location of the acoustic sensor at the former.http://www.sciencedirect.com/science/article/pii/S1470160X21011572Eco-acoustic indicesLong time memoryHurst exponentEnvironment sound in urban parks |
| spellingShingle | Roberto Benocci H. Eduardo Roman Alessandro Bisceglie Fabio Angelini Giovanni Brambilla Giovanni Zambon Auto-correlations and long time memory of environment sound: The case of an Urban Park in the city of Milan (Italy) Ecological Indicators Eco-acoustic indices Long time memory Hurst exponent Environment sound in urban parks |
| title | Auto-correlations and long time memory of environment sound: The case of an Urban Park in the city of Milan (Italy) |
| title_full | Auto-correlations and long time memory of environment sound: The case of an Urban Park in the city of Milan (Italy) |
| title_fullStr | Auto-correlations and long time memory of environment sound: The case of an Urban Park in the city of Milan (Italy) |
| title_full_unstemmed | Auto-correlations and long time memory of environment sound: The case of an Urban Park in the city of Milan (Italy) |
| title_short | Auto-correlations and long time memory of environment sound: The case of an Urban Park in the city of Milan (Italy) |
| title_sort | auto correlations and long time memory of environment sound the case of an urban park in the city of milan italy |
| topic | Eco-acoustic indices Long time memory Hurst exponent Environment sound in urban parks |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X21011572 |
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