Definition
Spatial data mining [1,2,3] is the process of discovering nontrivial, interesting, and useful patterns in large spatial datasets. The most common spatial pattern families are co-locations, spatial hotspots, spatial outliers, and location predictions.
Figure 1 gives an example of a spatial hotspot pattern (in the green circle) detected by SaTScan [4] from 250 cholera cases (shown by red points) that occurred near Broad Street in London, 1854. Notice that discovering spatial hotspots here is a nontrivial process due to the irregular size and special shape of the pattern. In addition, not all incidents contribute to the hotspot (e.g., red points outside the circles). Discovery of this pattern is very useful and interesting to detect outbreak of disease for public...
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Shekhar, S., Jiang, Z., Kang, J., Gandhi, V. (2017). Spatial Data Mining. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_357-2
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DOI: https://doi.org/10.1007/978-1-4899-7993-3_357-2
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