03307nas a2200313 4500008004100000245010000041210006900141260004000210520226600250653002102516653001802537653001702555653001302572653001202585653001502597653001902612653003302631653001702664653002602681653001302707653004402720653002702764653003402791653002302825653003902848653001802887100002102905856006702926 2018 eng d00aANALYSIS AND VISUALISATION OF VERY-LONG-DURATION ACOUSTIC RECORDINGS OF THE NATURAL ENVIRONMENT0 aANALYSIS AND VISUALISATION OF VERYLONGDURATION ACOUSTIC RECORDIN bQueensland University of Technology3 a

Advances in technology and reduction in data storage costs enable the autonomous collection of large quantities of continuous audio recordings. While the collection of very long environmental recordings has become easier, the analysis of these recordings remains challenging. A very-long-duration audio recording is defined as one with a minimum length of one day, but may have durations of weeks, months, or years. This thesis provides methods for data reduction and visualisation that enable the ecological interpretation and navigation of very-long-duration audio recordings.
The major theme of data reduction commenced after the establishment of protocols and the collection of two thirteen-month continuous audio recordings from two separate Southeast Queensland forest ecosystems. The acoustic indices calculated on one-minute audio segments were used to develop two new techniques to visualise the contents of very- long-duration recordings. An acoustic index is a mathematical expression used to measure a particular aspect of the energy distribution in audio recordings. Microphone failure in one channel was noticed shortly after the recording commenced. A method was established to detect microphone problems in long recordings.
A novel error measure was developed to detect seasonal and site differences and enable optimisation of the clustering based on seasonal and site differences in the data. Cluster interpretation on very-long-duration audio recordings is problematic because listening to large amounts of audio is time-consuming and therefore impractical. To overcome this, a series of five methods were developed to build on the interpretations made through listening. These methods enabled the allocation of an acoustic label to each cluster, resulting in a labelled acoustic sequence. This acoustic sequence was used to develop three additional visualisation techniques.
The culmination of the methods developed in this thesis was the six case studies. These extended the ecological interpretation of the acoustic sequence beyond those that were made through the visualisations. The case studies demonstrated that clustering can facilitate ecological interpretation of very-long-duration audio recordings.

10aacoustic indices10aAnthropophony10abioacoustics10abiophony10aCicadas10aClustering10aData reduction10aDiel plots; Dot-matrix plots10aecoacoustics10aEcological Monitoring10aGeophony10aLong-duration false-colour spectrograms10aMicrophone malfunction10aPrincipal Components Analysis10aSoundscape ecology10aVery-long-duration audio recording10aVisualisation1 aPhillips, Yvonne uhttps://eprints.qut.edu.au/123020/1/Yvonne_Phillips_Thesis.pdf