Abstract
Clustering geographically referenced data is an important issue in Geographic Information Science. Although the standard SOM can be used in many of these problems, it is useful to have a clustering tool that takes into account the special importance that geographic location has in these problems. In this paper, such a tool, named GEO-SOM, is presented. The differences between the training and mapping algorithms of the standard SOM and GEO-SOM are pointed out, and some simple examples of applications are given. Another important issue in the analysis of geo-referenced data is visualization of results, and integration with well established Geographic Information Systems (GIS). It is shown that GEO-SOM can easily be integrated in such systems, and examples of relevant visualization tools are presented. The fundamental assumption of the GEO-SOM is that some variables (in this case geographical coordinates) are more important, in the sense that they condition any subsequent clustering.
Original language | English |
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Title of host publication | WSOM 2005 - 5th Workshop on Self-Organizing Maps |
Pages | 505-512 |
Number of pages | 8 |
Publication status | Published - 2005 |
Event | 5th Workshop on Self-Organizing Maps, WSOM 2005 - Paris, France Duration: 5 Sept 2005 → 8 Sept 2005 |
Conference
Conference | 5th Workshop on Self-Organizing Maps, WSOM 2005 |
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Country/Territory | France |
City | Paris |
Period | 5/09/05 → 8/09/05 |
Keywords
- Geo-referenced data
- Geography
- SOM variants
- Spatial data