The primary goal of this thesis is to utilize acoustical radiation from the Arctic ice cover to infer the response of sea ice to environmental forcing, and to sense remotely the mechanical properties of the ice. The work makes use of two experiments in the Canadian arctic undertaken by the Ocean Acoustics Group of the Institute of Ocean Sciences, which resulted in an extensive body of acoustical and related environmental data. Cracking sounds originating from both first and multi-year ice fracturing processes are analyzed. Data used in this thesis also include sound made by artificial sources. The survey of in situ ice conditions by air photography and synthetic radar imaging, and a crack distribution map based on observations made with a 3-D hydrophone array, reveal, for the first time, a close correlation between thermal cracking events and ice type. It is shown that most of the thermal cracks occur in irregular multi-year ice where there are exposed, snow-free surfaces. The study shows that acoustical radiation from some cracks implies a slip-stick seismic movement over the faults, and some cracks tend to radiate more high frequency sound downwards rather than sideways. This phenomenon is most clearly apparent in sounds made by artificial sources. Another interesting finding from this study is that the sound of cracking ice does not always exhibit a vertical dipole radiation pattern, and some cracks due to thermal tension on smooth first year ice radiate more energy horizontally. The observations have motivated the development of various analytical models. These models allow the observed acoustical features to be related to the length and depth of a crack, the thickness of the ice cover and its Young's modulus. The models also show that maximum sound radiation from a crack is in the direction of external forcing. Finally, it is found that noise due to rubbing between ice floes exhibits a narrow band spectrum. This phenomenon is investigated and a linear model derived shows that the observed peak frequency is that of the first mode horizontal shear wave triggered by frictional effects at the ice floe edge. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

Climate modelling and high-latitude marine navigation require improved information on sea-ice floe extents and dynamics. New satellite sensors provide raw data of this nature but the volume of information makes human analysis impractical. To address this problem, a software system for automatic tracking of sea-ice floes in satellite imagery has been designed and evaluated. Using a recurrent neural network model, experiments were conducted to discover suitable design parameters. Simulated imagery time-sequences of increasing complexity were produced to train successive models. The networks produced were evaluated based on performance and reliability. A small-scale working system, able to map multiple input features in image sequences to Cartesian coordinates, was produced. Results show that a recurrent neural network is suitable for the tracking task and has advantages in robustness and speed over other approaches. Recurrency (feedback) was found to be crucial in achieving good performance.

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