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Applying spatial mutual information to AIS data

Published online by Cambridge University Press:  01 October 2021

Bruce A. McArthur  and
Anthony W. Isenor Open the ORCID record for Anthony W. Isenor [Opens in a new window]
Bruce A. McArthur
Affiliation:
Defence R&D Canada – Atlantic Research Centre, Dartmouth, Canada
Anthony W. Isenor*
Affiliation:
Defence R&D Canada – Atlantic Research Centre, Dartmouth, Canada
*
*Corresponding author. E-mail: anthony.isenor@forces.gc.ca
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Abstract

This paper examines a new interpretation for spatial mutual information based on the mutual information between an attribute value and a spatial random variable. This new interpretation permits the measurement of variations in spatial mutual information over the domain, not only answering the question of whether a spatial dependency exists and the strength of that dependency, but also allowing the identification of where such dependencies exist. Using simulated and real vessel reporting data, the properties of this new interpretation of spatial mutual information are explored. The utility of the technique in detecting spatial boundaries between regions of data having different statistical properties is examined. The technique is shown to successfully identify vessel traffic boundaries, crossing points between traffic lanes, and transitions between regions having differing vessel movement patterns.

Keywords

entropymutual informationautomatic identification systemtraffic pattern
Type
Research Article
Information
The Journal of Navigation , Volume 75 , Issue 1 , January 2022 , pp. 95 - 105
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Copyright
Copyright © Crown Copyright, 2021. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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