Clustering of German municipalities based on mobility characteristics
Zanda A., Koerner C., Giannotti F., Schulz D., May M.
Spatial data mining Mobility Clustering
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.
Source: 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 479–482, Irvine, CA, US, 5-7 novembre 2008
Publisher: ACM Press, New York, USA
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@inproceedings{oai:it.cnr:prodotti:91832,
title = {Clustering of German municipalities based on mobility characteristics},
author = {Zanda A. and Koerner C. and Giannotti F. and Schulz D. and May M.},
publisher = {ACM Press, New York, USA},
doi = {10.1145/1463434.1463514},
booktitle = {16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 479–482, Irvine, CA, US, 5-7 novembre 2008},
year = {2008}
}
0000-0003-3099-3835