Towards a framework for mining and analysing spatio-temporal datasets

High-resolution spatio-temporal datasets are being collected every day to record the behaviour of several natural phenomena. However, data-mining techniques are needed to extract relevant patterns from very large repositories and reveal spatial and temporal patterns in the behaviour of these phenomena. To this aim, we propose a system for mining data with spatial and temporal characteristics, and for visualizing and interpreting the results. Within this system, we have developed two complementary 3D visualization environments, one based on Google Earth and one relying on a Java3D graphical user interface. In this paper, we illustrate the main features of the system we have developed, and report on the main results we have obtained by analysing the Hurricane Isabel dataset.