Geospatial data analysis for global maritime risk assessment using the discrete global grid system.

Abstract

The effective management of the safety of navigation by coastguards is challenged by the complexity in quantifying and describing the relative risk of accidents occurrence. The discovery of patterns in observation data is reliant on the collection and analysis of significant volumes of relevant heterogenous spatial datasets. Conventional approaches of risk mapping which aggregate vessel traffic and incident data into Cartesian grids can result in misrepresentation due to inherent inadequacies in this spatial data format. In this paper, we explore how the Discrete Global Grid System (DGGS) overcomes these limitations through the development of global maps of incident rates at multiple resolutions. The results demonstrate hot spots of relative high risk across different regions and clearly show that DGGS is more suited to global analysis than conventional grids. This work contributes to a greater understanding of both the disposition of maritime risk and the advantages of adopting DGGS in supporting big data analysis.