Preprint Article Version 2 This version is not peer-reviewed

An Adaptive Sweep-Circle Spatial Clustering Algorithm Based on Gestalt

Version 1 : Received: 10 August 2017 / Approved: 10 August 2017 / Online: 10 August 2017 (10:14:33 CEST)
Version 2 : Received: 24 August 2017 / Approved: 24 August 2017 / Online: 24 August 2017 (10:53:05 CEST)

A peer-reviewed article of this Preprint also exists.

Zhan, Q.; Deng, S.; Zheng, Z. An Adaptive Sweep-Circle Spatial Clustering Algorithm Based on Gestalt. ISPRS Int. J. Geo-Inf. 2017, 6, 272. Zhan, Q.; Deng, S.; Zheng, Z. An Adaptive Sweep-Circle Spatial Clustering Algorithm Based on Gestalt. ISPRS Int. J. Geo-Inf. 2017, 6, 272.

Journal reference: ISPRS Int. J. Geo-Inf. 2017, 6, 272
DOI: 10.3390/ijgi6090272

Abstract

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 of 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.

Subject Areas

spatial clustering; sweep-circle; Gestalt theory; data stream

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