Mining spatiotemporal associations using queries

In this paper, we present our approach for mining spatiotemporal knowledge. The proposed method is based on the computation of neighborhood relationships between geographical objects during a time interval. This kind of information is non-explicitly stored in spatio-temporal database and is extracted by the means of special mining queries enriched by time management parameters. The general aim of our approach is to develop a method that utilizes the inherent structure of spatiotemporal information as well as its rich semantics to derive spatio-temporal association rules in order to improve the decision making process about land changes and resulting prohibited risks.