An Adaptive Sweep-Circle Spatial Clustering Algorithm Based on Gestalt

An adaptive spatial clustering (ASC) algorithm is proposed in this present study, which employs sweep-circle techniques and a dynamic threshold setting based on the Gestalt theory to detect spatial clusters. The proposed algorithm can automatically discover clusters in one pass, rather than through...

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Veröffentlicht in:ISPRS international journal of geo-information Jg. 6; H. 9; S. 272
Hauptverfasser: Zhan, Qingming, Deng, Shuguang, Zheng, Zhihua
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.09.2017
Schlagworte:
Adaptive algorithms
Algorithms
Clustering
Clusters
Data
data collection
data stream
Data transmission
Delaunay triangulation
Dynamic characteristics
Economic models
Gestalt theory
Mathematical models
spatial clustering
Spatial data
sweep-circle
trees
Voronoi graphs
ISSN:2220-9964, 2220-9964
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Zusammenfassung:An adaptive spatial clustering (ASC) algorithm is proposed in this present study, which employs sweep-circle techniques and a dynamic threshold setting based on the Gestalt theory to detect spatial clusters. The proposed algorithm can automatically discover clusters in one pass, rather than through the modification of the initial model (for example, a minimal spanning tree, Delaunay triangulation, or Voronoi diagram). It can quickly identify arbitrarily-shaped clusters while adapting efficiently to non-homogeneous density characteristics of spatial data, without the need for prior knowledge or parameters. The proposed algorithm is also ideal for use in data streaming technology with dynamic characteristics flowing in the form of spatial clustering in large data sets.
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ISSN:2220-9964
2220-9964
DOI:10.3390/ijgi6090272