Including Spatial Relations and Scales within Sequential Pattern Extraction

Georeferenced databases contain a huge volume of temporal and spatial data. They are notably used in environmental analysis. Several works address the problem of mining those data, but none are able to take into account the richness of the data and especially their spatial and temporal dimensions. In this paper, we focus on the extraction of a new kind of spatio-temporal pattern, considering the relationship between spatial objects and geographical scales. We propose an algorithm, STR PrefixGrowth, which can be applied to a huge amount of data. The proposed method is evaluated on hydrological data collected on the Saône watershed during the last 19 years. Our experiments emphasize the contribution of our approach toward the existing methods.