Spatial and spatio-temporal data mining

ABSTRACT

The recent advances in technologies for collecting spatial and spatio-temporal data (e.g. Cellular Phones, GPS devices) has facilitated the collection of data referenced in space and time. These huge collections of data often hide interesting information which conventional systems are unable to discover. Spatial and spatio-temporal data require complex data preprocessing, transformation, data mining, and post-processing techniques to extract novel, useful, and understandable patterns. The importance of spatial data mining is growing with the increasing incidence and importance of large geo-spatial datasets such as maps, repositories of remote-sensing images, trajectories of moving objects generated by mobile devices, etc. Applications include Mobile-commerce industry (location-based services), climatological effects of El Nino, land-use classification and global change using satellite imagery, finding crime hot spots, and local instability in traffic. The main goal of this tutorial is to disseminate this research field in Brazil, giving an overview of the current state of the art and the main methodologies and algorithms for spatial and spatiotemporal data mining.

Index Terms

• Information systems

  • Information systems applications

    • Data mining

    • Spatial-temporal systems