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Proceedings Paper

A novel spatial clustering algorithm based on Delaunay triangulation
Author(s): Xiankun Yang; Weihong Cui
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Paper Abstract

Exploratory data analysis is increasingly more necessary as larger spatial data is managed in electro-magnetic media. Spatial clustering is one of the very important spatial data mining techniques. So far, a lot of spatial clustering algorithms have been proposed. In this paper we propose a robust spatial clustering algorithm named SCABDT (Spatial Clustering Algorithm Based on Delaunay Triangulation). SCABDT demonstrates important advantages over the previous works. First, it discovers even arbitrary shape of cluster distribution. Second, in order to execute SCABDT, we do not need to know any priori nature of distribution. Third, like DBSCAN, Experiments show that SCABDT does not require so much CPU processing time. Finally it handles efficiently outliers.

Paper Details

Date Published: 29 December 2008
PDF: 9 pages
Proc. SPIE 7285, International Conference on Earth Observation Data Processing and Analysis (ICEODPA), 728530 (29 December 2008); doi: 10.1117/12.813354
Show Author Affiliations
Xiankun Yang, Institute of Remote Sensing Applications (China)
Graduate Univ. of the Chinese Academy of Sciences (China)
Weihong Cui, Institute of Remote Sensing Applications (China)

Published in SPIE Proceedings Vol. 7285:
International Conference on Earth Observation Data Processing and Analysis (ICEODPA)
Deren Li; Jianya Gong; Huayi Wu, Editor(s)

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