Acoustic Monitoring Techniques for Avian Detection and Classification

Conference Paper

Title: Acoustic Monitoring Techniques for Avian Detection and Classification
Publication Date:
November 04, 2012
Pages: 1835-1838
Publisher: IEEE
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Document Access

Website: External Link

Citation

Mirzaei, G.; Majid, M.; Ross, J.; Jamali, M.; Gorsevski, P.; Frizado, J.; Bingman, V.; Bastas, S. (2012). Acoustic Monitoring Techniques for Avian Detection and Classification.
Abstract: 

There are many reports of bird and bat mortality in vicinity of wind turbines [1]. It is important to quantify numbers and species of birds and bats in a given area which is targeted for wind farm development. It is also necessary to assess the behavior of birds and bats in wind farm areas. Acoustic monitoring techniques have been developed in this work for monitoring of birds and bats. Spectrogram-based Image Frequency Statistics (SIFS) is used for feature extraction and Evolutionary Neural Network (ENN) is used for classification purposes. Data was collected near Lake Erie in Ohio during 2011 spring and fall migration periods. Data analysis was performed in accordance to needs of wildlife biologists.

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