Map segmentation for geospatial data mining through generalized higher-order Voronoi diagrams with sequential scan algorithms |
| |
Authors: | Ickjai Lee Christopher Torpelund-Bruin Kyungmi Lee |
| |
Affiliation: | 1. Faculty of Management, University of Tehran, Tehran, Iran;2. University of Tehran, Tehran, Iran;3. Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran |
| |
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. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|