Title :
Spatial Clustering with SOM and GeoSOM: Case Study of Lisbon´s Metropolitan Area
Author :
Henriques, Roberto ; Bacao, Fernando ; Lobo, Victor
Author_Institution :
Inst. Super. de Estatistica e Gestao de Informacao, Lisbon, Portugal
Abstract :
Clustering constitutes one of the most popular and important tasks in data analysis. The size and dimensionality of the existing geospatial databases stress the need for efficient and robust spatial clustering algorithms. In this paper we present the GeoSOM suite as a spatial clustering tool. GeoSOM suite implements the GeoSOM algorithm, which allows to perform clustering using both spatial and aspatial components from geospatial datasets. Finally, a case study is presented, based on census data from Lisbon, exploring the GeoSOM suite features and exemplifying its use in the context of exploratory data analysis.
Keywords :
data analysis; pattern clustering; self-organising feature maps; visual databases; GeoSOM algorithm; SOM algorithm; aspatial component; data analysis; geospatial databases; geospatial datasets; self-organizing maps; spatial clustering; spatial component; Clustering algorithms; Data analysis; Data mining; Floods; Geographic Information Systems; Robustness; Self organizing feature maps; Spatial databases; Stress; Urban areas; Exploratory data analysis; GeoSOM; Spatial clustering;
Conference_Titel :
Advanced Geographic Information Systems, Applications, and Services (GEOPROCESSING), 2010 Second International Conference on
Conference_Location :
St. Maarten
Print_ISBN :
978-1-4244-5809-7
DOI :
10.1109/GEOProcessing.2010.30
