[MARMAM] New publication: A review of big data analysis methods for baleen whale passive acoustic monitoring

Katie Kowarski katiekowarski at gmail.com
Mon Nov 9 06:51:52 PST 2020


We are pleased to announce our recent publication available online!

Kowarski, KA, Moors‐Murphy, H. A review of big data analysis methods for
baleen whale passive acoustic monitoring. *Mar Mam Sci*. 2020; 1– 22.
https://doi.org/10.1111/mms.12758

Abstract

Many organizations collect large passive acoustic monitoring (PAM) data
sets that need to be efficiently and reliably analyzed. To determine
appropriate methods for effective analysis of big PAM data sets, we
undertook a literature review of baleen whale PAM analysis methods.
Methodologies from 166 studies (published between 2000–2019) were
summarized, and a detailed review was performed on the 94 studies that
recorded more than 1,000 hr of acoustic data (“big data”). Analysis
techniques for extracting baleen whale information from PAM data sets
varied depending on the research observed. A spectrum of methodologies was
used and ranged from manual analysis of all acoustic data by human experts
to completely automated techniques with no manual validation. Based on this
assessment, recommendations are provided to encourage robust research
methods that are comparable across studies and sectors, achievable across
research groups, and consistent with previous work. These include using
automated techniques when possible to increase efficiency and
repeatability, supplementing automation with manual review to calculate
automated detector performance, and increasing consistency in terminology
and presentation of results. This work can be used to facilitate discussion
for minimum standards and best practices to be implemented in the field of
marine mammal PAM.
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