Uncovering spatio-temporal patterns in environmental data

The integration of data mining and geographic visualization techniques facilitates the identification and the interpretation of spatio-temporal patterns - a process recognized as knowledge construction. Knowledge construction is a dynamic process of manipulating 'data' to find, relate, and interpret interesting patterns in large environmental data sets. Toward this end, an overview of the main methods associated with the expanding fields of Knowledge Discovery in Databases (KDD) and Geographic Visualization (GeoVis) is provided. The paper explains how different methods can be combined in order to design a knowledge construction process for the identification and interpretation of the space-time variability of both composition and structure of a pattern. Case studies, tools and prototype implementations are described for illustrating how both KDD and GeoVis methods can be applied to uncovering spatio-temporal patterns. Finally, the specific underlying research issues are described, with particular emphasis on how these relate to the environmental sciences domain.