A Tessellation-Based Methodology for an Interactive Analysis of the Arctic Ice Dynamic Phenomenon with Spatial Online Analytical Processing

Abstract

A tessellation-based methodology for interactively analyzing the spatio-temporal evolution of a dynamic phenomenon – ice coverage and its characteristics – using a spatial online analytical processing (OLAP) approach is proposed. The feasibility of the method was tested through a prototype developed in the context of the CanICE project using Canadian Ice Service data and the Egg Code, an international standard for characterizing sea and lake ice. By transforming the standard spatial OLAP vector-based point of view – aggregating data from instances of evolving features – into a tessellation-based point of view – aggregating data from constant spaces with evolving properties – the proposed solution makes it possible to meet the criteria of interactive multidimensional analysis for dynamic phenomena. The second innovative aspect of the methodology relates to the management of data quality with a spatial OLAP approach.