Adaptive spatial clustering in the presence of obstacles and facilitators

An intersection-and-combination strategy for clustering spatial point data in the presence of obstacles (e.g. mountain) and facilitators (e.g. highway) is proposed in this paper, and an adaptive spatial clustering algorithm, called ASCDT+, is also developed. The ASCDT+ algorithm can take both obstac...

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Bibliographic Details
Published in:Computers & geosciences Vol. 56; pp. 104 - 118
Main Authors: Liu, Qiliang, Deng, Min, Shi, Yan
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.07.2013
Subjects:
Adaptive
algorithms
computers
data collection
Delaunay triangulation
Facilitator
Obstacle
Spatial clustering
Facilitator
Delaunay triangulation
Spatial clustering
Obstacle
Adaptive
ISSN:0098-3004, 1873-7803
Online Access:Get full text
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Summary:An intersection-and-combination strategy for clustering spatial point data in the presence of obstacles (e.g. mountain) and facilitators (e.g. highway) is proposed in this paper, and an adaptive spatial clustering algorithm, called ASCDT+, is also developed. The ASCDT+ algorithm can take both obstacles and facilitators into account without additional preprocessing, and automatically detects spatial clusters adjacent to each other with arbitrary shapes and/or different densities. In addition, the ASCDT+ algorithm has the ability to find clustering patterns at both global and local levels so that users can make a more complete interpretation of the clustering results. Several simulated and real-world datasets are utilized to evaluate the effectiveness of the ASCDT+ algorithm. Comparison with two related algorithms, AUTOCLUST+ and DBRS+, demonstrates the advantages of the ASCDT+ algorithm. •The ASCDT+ algorithm can consider both obstacles (e.g. mountain) and facilitators (e.g. highway).•The ASCDT+ algorithm can detect clusters with different shapes and densities at both global and local levels.•The ASCDT+ algorithm is easy to implement with no need of user-specified parameters.
Bibliography:http://dx.doi.org/10.1016/j.cageo.2013.03.002
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ISSN:0098-3004
1873-7803
DOI:10.1016/j.cageo.2013.03.002