Map segmentation for geospatial data mining through generalized higher-order Voronoi diagrams with sequential scan algorithms
Journal Publication ResearchOnline@JCULee, Ickjai;Torpelund-Bruin, Christopher;Lee, Kyungmi
Abstract
Segmentation is one popular method for geospatial data mining. We propose efficient and effective sequential-scan algorithms for higher-order Voronoi diagram districting. We extend the distance transform algorithm to include complex primitives (point, line, and area), Minkowski metrics, different weights and obstacles for higher-order Voronoi diagrams. The algorithm implementation is explained along with efficiencies and error. Finally, a case study based on trade area modeling is described to demonstrate the advantages of our proposed algorithms.
Journal
Expert Systems with Applications
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Volume
39
ISBN/ISSN
0957-4174
Edition
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Issue
12
Pages Count
15
Location
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Publisher
Elsevier
Publisher Url
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Publisher Location
N/A
Publish Date
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Url
N/A
Date
N/A
EISSN
N/A
DOI
10.1016/j.eswa.2012.03.042