Name
Title | ||
|---|---|---|
Spatio-Temporal Clustering of Time-Dependent Origin-Destination Electronic Trace Data. |
Abstract | ||
|---|---|---|
In this study we identify spatial regions based on an empirical data set consisting of time-dependent origin-destination (OD) pairs. This OD data consists of electronic traces collected from smart phone data by Google in the Amsterdam metropolitan region and is aggregated by the volume of trips per hour at neighborhood level. In this study we cluster the pairs by space and time to gain insight in both aspects regarding travel characteristics. We show that spatially connected clusters appear when we use a performance metric called modularity on the OD data when directionality is incorporated. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.procs.2018.04.053 | Procedia Computer Science |
Keywords | Field | DocType |
Screen-lines,OD-matrices,Clustering,Modularity optimization,GPS traces,Travel behavior | Travel behavior,Data mining,Cluster (physics),Computer science,Spacetime,Performance metric,Cluster analysis,TRIPS architecture,Metropolitan area,Modularity | Conference |
Volume | ISSN | Citations |
130 | 1877-0509 | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daphne van Leeuwen | 1 | 0 | 1.35 |
| J. W. Bosman | 2 | 16 | 5.17 |
| Elenna Dugundji | 3 | 0 | 1.35 |