The Clustering of Acoustic Indices derived from Long-duration Recordings of the Environment

Publication Type:Report
Year of Publication:2017
Alkuperäinen tekijä:Phillips
Avainsanat:acoustic environment, acoustic indices, hierarchical clustering, k-means clustering
Abstract:

This paper outlines the recording dataset and methods used to choose a clustering algorithm for a large twenty-six month acoustic dataset. The recordings were of the natural environment and consist of thirteen months of recording from each of two sites in two national parks 160 km north of Brisbane, Queensland. This paper also explains the calculation and use of the intra-three-day-distance (I3DD) error measure used to determine the optimum clustering result. Site maps and photos are provided at the end of this document.

URL:https://eprints.qut.edu.au/110659/
BioAcoustica ID: 
Non biological: 
Scratchpads developed and conceived by (alphabetical): Ed Baker, Katherine Bouton Alice Heaton Dimitris Koureas, Laurence Livermore, Dave Roberts, Simon Rycroft, Ben Scott, Vince Smith