Gennady Andrienko, Natalia Andrienko Fraunhofer IAIS, Germany Topic: “Spatio-temporal analysis of flows in CDC 2013 data”

1. © Fraunhofer-Institut für Intelligente
Analyse- und Informationssysteme IAIS
Spatio-temporal analysis of flows
in CDC 2013 data
Gennady Andrienko
Natalia Andrienko
http://geoanalytics.net

2. © Fraunhofer-Institut für Intelligente
Analyse- und Informationssysteme IAIS
Data processing procedures
1. Initial processing in Database
• Eliminating duplicates (same ID and time stamp)
• Eliminating stationary points (speed<2km/h)
• Dividing into days (by 3AM)
• Further dividing by 30min stops and 1km gaps
• Eliminating trajectories consisting of less than 5 points, shorter than 5
minutes, within 100m bounding rectangle
2. Further processing attempts in main memory
• Removing segments with speed > 75km/h
• Removing segments with high tortuosity (>2 over 1min), sinuosity (>5
over 1min) or being within 100m radius over 10-15 minutes
3. Still, the data are far from being perfect
• Wrong hardware / software / settings?

3. © Fraunhofer-Institut für Intelligente
Analyse- und Informationssysteme IAIS
Data quality
• Jumping around stops;
• Systematically wrong positions

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Analyse- und Informationssysteme IAIS
Summarization and aggregation of trajectories
• Density-driven Voronoi polygons, r=100m: 14,033 polygons country-wide
• Correctly reflect the street network

5. © Fraunhofer-Institut für Intelligente
Analyse- und Informationssysteme IAIS
Flows between adjacent polygons
• 14,033 polygons => 26,094 directed connections
• 5,723 used by at least 5 different trajectories
• Attribute “N different trajectories” compensates for “hairball” structures @stops

6. © Fraunhofer-Institut für Intelligente
Analyse- und Informationssysteme IAIS
Hourly time series of flows: transformation and clustering
• Only connections used by
at least 5 trajectories
1. Hourly time series
2. Smoothing by 3 hours
windows
3. Mean-normalization of
each time series
4. Clustering by k-Means
with different K

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Analyse- und Informationssysteme IAIS
Major clusters

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Analyse- und Informationssysteme IAIS
Cluster 5

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Analyse- und Informationssysteme IAIS
Cluster 3

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Analyse- und Informationssysteme IAIS
Cluster 1

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Analyse- und Informationssysteme IAIS
Cluster 2

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Analyse- und Informationssysteme IAIS
Cluster 4

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Analyse- und Informationssysteme IAIS
Conclusions
• Different roads have different temporal signatures
• Especially bridges
• Too few trajectories per person / per road segment for more sophisticated
analysis
• Data quality issues

14. © Fraunhofer-Institut für Intelligente
Analyse- und Informationssysteme IAIS
What we can do:
• Analysis of flows and their temporal dynamics
Times
Locations
Movers
Spatial events
Spatial event data Spatial time series
Movement data Local time series
Spatial distributions
Trajectories
Details:
Visual Analytics of Movement: an Overview of
Methods, Tools, and Procedures
Information Visualization, 12(1), pp.3-24, 2013
and
Visual Analytics of Movement
Springer-Verlag 2013
ISBN 978-3-642-37582-8
Due: July 5, 2013