Automatic data selection for validation: A method to determine cetacean occurrence in large acoustic data sets
Katie A Kowarski1, Julien J-Y Delarue1, Briand J Gaudet1
1JASCO Applied Sciences, 32 Troop Avenue, Suite 202, Dartmouth, Nova Scotia B3B 1Z1, Canada katie.kowarski@jasco.com, julien.delarue@jasco.com, briand.gaudet@jasco.com, bruce.martin@jasco.com.
Abstract:
Passive acoustic monitoring (PAM) can inform wildlife management by providing information on the distribution of cetaceans. This paper presents an automatic data selection for validation (ADSV) method to effectively identify all species acoustically present in large PAM data sets. The ADSV method involves the application of automated detectors, the automated selection of a portion of data for manual review, and the evaluation/optimization of automated detectors. Using an exemplar data set, results from the ADSV method were compared to a more intensive systematic manual review method. The two methods were found to have similar species occurrence results (hourly occurrence matching 73%-100%).
