Creating Polygon Models for Spatial Clusters
نویسندگان
چکیده
This paper proposes a novel methodology for creating efficient polygon models for spatial datasets. A comprehensive analysis framework is proposed that takes a spatial cluster as an input and generates a polygon model for the cluster as an output. The framework creates a visually appealing, simple, and smooth polygon for the cluster by minimizing a fitness function. We propose a novel polygon fitness function for this task. Moreover, a novel emptiness measure is introduced for quantifying the presence of empty spaces inside polygons.
منابع مشابه
Polygon-Based Spatial Clustering
Clustering geographic data using traditional methods often result in clusters that look dispersed over the geographic space and poorly reflect any underlying spatial structure. We propose a polygon-based spatial clustering approach, which models a spatial object as a polygon with three groups of attributes: general attributes, boundary attributes, and spatial events. We have developed a general...
متن کاملProceedings of the 1 st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics ( DMG ) 2010 offered under the auspices of the 18 th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Polygons can serve an important role in the analysis of georeferenced data as they provide a natural representation for particular types of spatial objects and in that they can be used as models for spatial clusters. This paper claims that polygon analysis is particularly useful for mining related, spatial datasets. A novel methodology for clustering polygons that have been extracted from diffe...
متن کاملProceedings of the 1 st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics
Polygons can serve an important role in the analysis of georeferenced data as they provide a natural representation for particular types of spatial objects and in that they can be used as models for spatial clusters. This paper claims that polygon analysis is particularly useful for mining related, spatial datasets. A novel methodology for clustering polygons that have been extracted from diffe...
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