Abstract
In order to identify a model that best predicts spatial patterns it is necessary to first explore the spatial properties of the data that will be included in a predictive model. Exploratory analyses help determine whether or not important statistical assumptions are met, and potentially lead to the definition of spatial patterns that might exist in the data. Here, we present results from exploratory analyses based on data describing illegal oil spills detected by the National Aerial Surveillance Program (NASP) in Canada’s Pacific Region, and marine vessel traffic, the possible source of these oil discharges. We identify and describe spatial properties of the oil spills, surveillance flights and marine traffic, to ultimately identify the most suitable predictive model to map areas where these events are more likely to occur.
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Serra-Sogas, N., O’Hara, P., Canessa, R., Bertazzon, S., Gavrilova, M. (2009). Exploratory Spatial Analysis of Illegal Oil Discharges Detected off Canada’s Pacific Coast. In: Gavrilova, M.L., Tan, C.J.K. (eds) Transactions on Computational Science VI. Lecture Notes in Computer Science, vol 5730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10649-1_13
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DOI: https://doi.org/10.1007/978-3-642-10649-1_13
Publisher Name: Springer, Berlin, Heidelberg
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