PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Zanda A., Koerner C., Giannotti F., Schulz D., May M. Clustering of German municipalities based on mobility characteristics. In: ACM GIS 2008 - 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (Irvine, CA, USA, 5-7 novembre 2008). Proceedings, pp. 479 - 482. ACM New York, 2008.
 
 
Abstract
(English)
This paper presents a clustering approach which groups German municipalities according to mobility characteristics. As the number of measurements for nationwide mobility studies is usually restricted, this clustering provides a means to infer mobility information for locations without measurements based on values of their respective cluster representatives. Our approach considers local and global information, i.e. characteristics of municipalities as well as relationships between municipalities. We realize previous findings in urban geography by using techniques from graph theory and computer vision. Our clustering consists of a two-step model, which rst extracts and condenses single mobility characteristics and subsequently combines the various features. We apply our model to all German municipalities between 10,000 and 50,000 inhabitants. The clustering has been successfully applied in practice for the inference of traffic frequencies.
URL: http://portal.acm.org/toc.cfm?id=1463434&type=proceeding&coll=GUIDE&dl=GUIDE&CFID=20366713&CFTOKEN=14353793
DOI: 10.1145/1463434.1463514
Subject Spatial data mining
Clustering
Mobility
H.2.8 Database Management. Database Applications. Data mining
H.2.8 Database Management. Database Applications. Spatial databases and GIS
G.2.2 Discrete Mathemat- ics. Graph Theory
G.2.2 Discrete Mathemat- ics. Graph algorithms
I.5.3 Pattern Recognition. Clustering


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