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Seismic signal analysis for the characterisation of elephant movements in a forest environment
Ecological Informatics ( IF 5.8 ) Pub Date : 2021-05-31 , DOI: 10.1016/j.ecoinf.2021.101329
D.S. Parihar , Ripul Ghosh , Aparna Akula , Satish Kumar , H.K. Sardana

Monitoring of pachyderm movements in the neighbourhood of a forest is an important area of research for mitigation of human-wildlife conflict issues. This paper reports the feasibility study for the detection of elephants using seismic sensors inside a forest environment and further characterisation of the seismic signals. Seismic signals generated during elephant locomotion are analysed for various distances. Frequency analysis of these signals shows an average dominant frequency of 15.80 Hz (±1.03 s.d.) and 16.52 Hz (±1.20 s.d.) in the range of 0 m to ~20 m and 20 m to ~40 m respectively. Based on frequency information of the seismic signal, different filter bands were incorporated and the highest accuracy of detection was achieved corresponding to the filter band of 10–20 Hz. The paper also illustrates the statistical analysis of three signal detection algorithms; short and long time averaging (STA/LTA), amplitude spectrum of Fourier transform (ASFT) and continuous wavelet transform (CWT) as a function of the distance from the sensor and elephant group size. Comparative analysis of the preliminary dataset was carried out where CWT based detection approach shows F1-score improvement of ~28% and ~14% in comparison with STA/LTA and ASFT respectively for a radial distance 0– 20 m whereas, ~2% for a radial distance 20– 40 m from the sensor. Furthermore, CWT outperforms with a detection accuracy of ~90% on the preliminary dataset.



中文翻译:

用于表征森林环境中大象运动的地震信号分析

监测森林附近的厚皮动物运动是缓解人类与野生动物冲突问题的重要研究领域。本文报告了在森林环境中使用地震传感器检测大象的可行性研究,并进一步表征地震信号。大象运动过程中产生的地震信号被分析为不同的距离。这些信号的频率分析显示,在 0 m 到 ~20 m 和 20 m 到 ~40 m 范围内的平均主频率分别为 15.80 Hz (±1.03 sd) 和 16.52 Hz (±1.20 sd)。根据地震信号的频率信息,结合不同的滤波带,在10-20Hz的滤波带对应的检测精度达到最高。论文还举例说明了三种信号检测算法的统计分析;短期和长期平均 (STA/LTA)、傅立叶变换 (ASFT) 和连续小波变换 (CWT) 的幅度谱作为与传感器距离和大象群大小的函数。对初步数据集进行了比较分析,其中基于 CWT 的检测方法显示,与 STA/LTA ​​和 ASFT 相比,径向距离 0-20 m 的 F1 分数分别提高了约 28% 和约 14%,而对于径向距离为约 2%距离传感器 20-40 m 的径向距离。此外,在初步数据集上,CWT 的检测准确度优于 90%。傅里叶变换 (ASFT) 和连续小波变换 (CWT) 的幅度谱作为与传感器距离和大象群大小的函数。对初步数据集进行了比较分析,其中基于 CWT 的检测方法显示,与 STA/LTA ​​和 ASFT 相比,径向距离 0-20 m 的 F1 分数分别提高了约 28% 和约 14%,而对于径向距离为约 2%距离传感器 20-40 m 的径向距离。此外,在初步数据集上,CWT 的检测准确度优于 90%。傅里叶变换 (ASFT) 和连续小波变换 (CWT) 的幅度谱作为与传感器距离和大象群大小的函数。对初步数据集进行了比较分析,其中基于 CWT 的检测方法显示,与 STA/LTA ​​和 ASFT 相比,径向距离 0-20 m 的 F1 分数分别提高了约 28% 和约 14%,而对于径向距离为约 2%距离传感器 20-40 m 的径向距离。此外,在初步数据集上,CWT 的检测准确度优于 90%。

更新日期:2021-06-11
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