We have applied clustering techniques to the terracing of potential field data. We found out how [Formula: see text]-means clustering or a simple reclassification of the field values based on the minimum Euclidean distance from a set of cluster centers can produce a nicely terraced potential field map, with the degree of simplification of the original map controlled by the number of clusters. We developed a method to automatically define the number and the center value of these clusters. The gravity or magnetic maps terraced by clustering techniques are transformed and present no smooth transitions, and each terrace has a constant field value. Such a terraced map is thus suitable for computing an apparent physical property distribution. To obtain even better results, it is possible to combine clustering techniques with edge-preserving filters. We tested our method on simple and complex synthetic fields and finally applied it to the real gravity data of a mining region in Canada, finding good correspondence between the resulting apparent density distribution and a simplified geologic map.
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