Map segmentation for geospatial data mining through generalized higher-order Voronoi diagrams with sequential scan algorithms

Authors:
Ickjai Lee;Christopher Torpelund-Bruin;Kyungmi Lee
Affiliations:
School of Business (IT), James Cook University, Cairns, QLD 4870, Australia;School of Business (IT), James Cook University, Cairns, QLD 4870, Australia;School of Business (IT), James Cook University, Cairns, QLD 4870, Australia
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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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.