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PAKDD
2009
ACM

Change Analysis in Spatial Data by Combining Contouring Algorithms with Supervised Density Functions.

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Change Analysis in Spatial Data by Combining Contouring Algorithms with Supervised Density Functions.
Detecting changes in spatial datasets is important for many fields. In this paper, we introduce a methodology for change analysis in spatial datasets that combines contouring algorithms with supervised density estimation techniques. The methodology allows users to define their own criteria for features of interest and to identify changes in those features between two datasets. Change analysis is performed by comparing interesting regions that have been derived using contour clustering. A novel clustering algorithm called DCONTOUR is introduced for this purpose that computes contour polygons that describe the boundary of a supervised density function at a given density threshold. Relationships between old and new data are analyzed relying on polygon operations. We evaluate our methodology in case studies that analyze changes in earthquake patterns.
Christoph F. Eick, Chun-Sheng Chen, Michael D. Twa
Added 07 Mar 2010
Updated 07 Mar 2010
Type Conference
Year 2009
Where PAKDD
Authors Christoph F. Eick, Chun-Sheng Chen, Michael D. Twa, Vadeerat Rinsurongkawong
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