Lecture 2 - Mobility Data
13 Feb 2023
Mozhgan Pourmoradnasseri, Ph.D.
Human mobility impacts the lives of individuals and environmental conditions.
Ford Mode T (1908)
Railway 1830
Spatial, Temporal, and Social Aspects.
Different levels of aggregation, from individual GPS traces to aggregated patterns.
Dodge, Somayeh, et al. "Analysis of movement data." International Journal of Geographical Information Science 30.5 (2016): 825-834.
Temporally ordered sequence of spatiotemporal position records during the whole lifespan of the object.
\((x,y)\)
\((x,y,t)\)
A trajectory is part of the movement of an object that is delimited by a given time interval \([t_{Begin}, t_{End}]\).
It is a continuous function from the time interval \([t_{Begin}, t_{End}]\) to Space. The spatiotemporal position of the object at \(t_{Begin}\) (resp. \(t_{End}\)) is called the Begin (resp. End) of the trajectory.
GPS
GSM
Real-world applications usually consider objects that are restricted from moving within a given spatial network that is represented as a graph.
The huge amounts of data raise storage, transmission, computation, and display challenges.
Gole:
Reducing the size of the data set,
without deviating from the original one, with reducing computational complexity.
8:24
12:39
18:16
& 17:48
Stay locations?
8:24
12:39
8:26
17:48
Move episodes/trips?
In 2 minutes?
Schneider, C. M., Belik, V., Couronné, T., Smoreda, Z., & González, M. C. (2013). Unravelling daily human mobility motifs. Journal of The Royal Society Interface, 10(84), 20130246.
Only 17 unique patterns are present in daily mobility and they follow simple rules. These patterns are sufficient to capture up to 90% of the population.
Decomposition of the mobility profile over 10 days into daily mobility patterns for two anonymous mobile phone users.
Daily human mobility patterns are stable over several months. The values show how more or less likely a motif is found during the observation period of six months under the condition that the individual has a given motif on another day. Positive values indicate that these motifs are more likely than expected and negative values that these motifs are suppressed.
Ebrahimpour, Zeinab, et al. "Analyzing social-geographic human mobility patterns using large-scale social media data." ISPRS International Journal of Geo-Information 9.2 (2020): 125.
Weibo (Chinese version of Twitter) data are used to analyze social-geographic human mobility in the CBD area of Shanghai.
325,713 posts during 2014-2015.
Hourly check-in distribution in different districts.
Coming soon :)
Tartu Smart Bike Data
Daily Mobility Patterns of Tartu