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生态声学分析中的偏差：一种使音频记录器均衡的方案。

Biases in Ecoacoustics Analysis: A Protocol to Equalize Audio Recorders.

作者信息

Potenza Andrea, Zaffaroni-Caorsi Valentina, Benocci Roberto, Guagliumi Giorgia, Fouani Jalal M, Bisceglie Alessandro, Zambon Giovanni

机构信息

Department of Earth and Environmental Sciences, University of Milano-Bicocca, 20126 Milan, Italy.

Independent Researcher, 40132 Bologna, Italy.

出版信息

Sensors (Basel). 2024 Jul 17;24(14):4642. doi: 10.3390/s24144642.

DOI:10.3390/s24144642
PMID:39066040
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11280489/
Abstract

Eco-acoustic indices allow us to rapidly evaluate habitats and ecosystems and derive information about anthropophonic impacts. However, it is proven that indices' values and trends are not comparable between studies. These incongruences may be caused by the availability on the market of recorders with different characteristics and costs. Thus, there is a need to reduce these biases and incongruences to ensure an accurate analysis and comparison between soundscape ecology studies and habitat assessments. In this study, we propose and validate an audio recording equalization protocol to reduce eco-acoustic indices' biases, by testing three soundscape recorder models: Song Meter Micro, Soundscape Explorer Terrestrial and Audiomoth. The equalization process aligns the signal amplitude and frequency response of the soundscape recorders to those of a type 1 level meter. The adjustment was made in MATLAB R2023a using a filter curve generated comparing a reference signal (white noise); the measurements were performed in an anechoic chamber using 11 audio sensors and a type 1 sound level meter (able to produce a .WAV file). The statistical validation of the procedure was performed on recordings obtained in an urban and Regional Park (Italy) assessing a significant reduction in indices' biases on the Song Meter Micro and Audiomoth.

摘要

生态声学指标使我们能够快速评估栖息地和生态系统，并获取有关人为影响的信息。然而，事实证明，不同研究之间指标的数值和趋势无法进行比较。这些不一致可能是由市场上具有不同特性和成本的录音机的可用性导致的。因此，有必要减少这些偏差和不一致，以确保在声景生态学研究和栖息地评估之间进行准确的分析和比较。在本研究中，我们通过测试三种声景录音机型号：Song Meter Micro、Soundscape Explorer Terrestrial和Audiomoth，提出并验证了一种音频记录均衡协议，以减少生态声学指标的偏差。均衡过程将声景录音机的信号幅度和频率响应与1型声级计的信号幅度和频率响应对齐。使用通过比较参考信号（白噪声）生成的滤波器曲线，在MATLAB R2023a中进行调整；测量在消声室中使用11个音频传感器和1型声级计（能够生成.WAV文件）进行。该程序的统计验证是在意大利一个城市和区域公园获得的录音上进行的，评估结果表明Song Meter Micro和Audiomoth的指标偏差显著降低。

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本文引用的文献

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3
Limits to the accurate and generalizable use of soundscapes to monitor biodiversity.声音景观在监测生物多样性方面的准确和可推广使用存在限制。
Nat Ecol Evol. 2023 Sep;7(9):1373-1378. doi: 10.1038/s41559-023-02148-z. Epub 2023 Jul 31.
4
Analysis and Acoustic Event Classification of Environmental Data Collected in a Citizen Science Project.在公民科学项目中收集的环境数据的分析和声学事件分类。
Int J Environ Res Public Health. 2023 Feb 19;20(4):3683. doi: 10.3390/ijerph20043683.
5
Acoustic indices as proxies for biodiversity: a meta-analysis.声学生物指标作为生物多样性的代理指标：一项荟萃分析。
Biol Rev Camb Philos Soc. 2022 Dec;97(6):2209-2236. doi: 10.1111/brv.12890. Epub 2022 Aug 17.
6
Mapping of the Acoustic Environment at an Urban Park in the City Area of Milan, Italy, Using Very Low-Cost Sensors.使用极低成本传感器对意大利米兰市区城市公园的声环境进行测绘。
Sensors (Basel). 2022 May 6;22(9):3528. doi: 10.3390/s22093528.
7
Multilabel Acoustic Event Classification Using Real-World Urban Data and Physical Redundancy of Sensors.利用真实世界城市数据和传感器物理冗余进行多标签声学事件分类。
Sensors (Basel). 2021 Nov 10;21(22):7470. doi: 10.3390/s21227470.
8
Assimilation of mobile phone measurements for noise mapping of a neighborhood.用于邻里噪声地图绘制的手机测量数据同化
J Acoust Soc Am. 2018 Sep;144(3):1279. doi: 10.1121/1.5052173.
9
T test as a parametric statistic.T检验作为一种参数统计方法。
Korean J Anesthesiol. 2015 Dec;68(6):540-6. doi: 10.4097/kjae.2015.68.6.540. Epub 2015 Nov 25.
10
Measuring acoustic habitats.测量声学栖息地。
Methods Ecol Evol. 2015 Mar;6(3):257-265. doi: 10.1111/2041-210X.12330. Epub 2015 Jan 27.