Mobility Modelling
Lecture 2 - Mobility Data
13 Feb 2023
Mozhgan Pourmoradnasseri, Ph.D.
- Climate change
- Inhospitable landscapes
- Conflict and food scarcity
- Socio-economic factors such as wage imbalance
- Differences in welfare and living conditions
- Globalization
- Social and leisure activities.
Human mobility impacts the lives of individuals and environmental conditions.
in modern times
Ford Mode T (1908)
Revolution in commuting
Railway 1830
Your Experience with spatial data
- The research question?
- Data and its attributes?
- What attributes were used, and what not?
- What other data/info could enhance your results?
Application areas
- History
- Global Changes
- Social Equity
- Local Developments
- Spread of Biological Viruses
- Utility Management
- Traffic Forecasting
- Location-based Services
- Business
Spatial, Temporal, and Social Aspects.
- which urban areas could provide people with essentially everything they needed to survive—all within walking distance of their homes. study emergency or disaster responses to events like the big freeze in Texas, rising gas prices, hurricane or earthquake relief, power outages, traffic bottlenecks, and more.
What questions can be answered with mobility data?
Big Data and Paradime Shift in mobility analysis
- Enable researchers to answer new questions by giving access to a higher spatial, temporal, and thematic resolution than before.
-
Different levels of aggregation, from individual GPS traces to aggregated patterns.
- But requires novel techniques (e.g., parallelization) to handle the size of these data.
Dodge, Somayeh, et al. "Analysis of movement data." International Journal of Geographical Information Science 30.5 (2016): 825-834.- Top-down approach
- Theory-driven modeling
- Knowledge is used for prediction and reconstruction
When, Where, How, and Why?
- Bottom-up approach
- Data-driven analytics
- Data analytics for knowledge discovery
Temporally ordered sequence of spatiotemporal position records during the whole lifespan of the object.
- Each record (instant, point, features) contains the instant of the capture, the 2D or 3D point of the object, and possibly other features (e.g., the instantaneous speed, acceleration, direction, and rotation).
- There are no two records with the same instant value.
Movement track
(x,y)
(x,y,t)
Tourists Application Scenario
A trajectory is part of the movement of an object that is delimited by a given time interval [tBegin,tEnd].
It is a continuous function from the time interval [tBegin,tEnd] to Space. The spatiotemporal position of the object at tBegin (resp. tEnd) is called the Begin (resp. End) of the trajectory.
Trajectory Definition
Different data types
- Census Data
- Travel Surveys
- Bank Notes
- Traffic Sensors
- Transit Smart Cards
- Social Networks (Twitter, Flicker, ...)
- GPS Trajectories
- Cellular Network Data
Data Attributes
Knowledge discovery process
Some technologies
GPS
GSM
Handling Trajectory data; Data Cleaning
- Systematic errors: filtering method that filters noisy positions by taking advantage of the maximum allowed speed of a moving object.
- Random errors: small distortions from the true values. Smoothing techniques such as Gaussion kernels and Kalman filter.
Handling Trajectory data; Map Matching
Real-world applications usually consider objects that are restricted from moving within a given spatial network that is represented as a graph.
- Geometric methods based on min distance.
- Hidden Markov Model for finding the most likely route.
Handling Trajectory data; Data Compression
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.
Trajectory reconstruction; Semantics
- Building trajectory episodes
- Annotating trajectory with regions
- Annotating trajectory with lines
- Annotating trajectory with points
Extracting Trajectories; toy example
8:24
12:39
18:16
& 17:48
Stay locations?
8:24
12:39
8:26
17:48
Move episodes/trips?
In 2 minutes?
Extracting Trajectories; toy example
EXAMPLE: DAILY MOBILITY PATTERNS
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.
SOCIAL-GEOGRAPHIC HUMAN MOBILITY PATTERNS
Hourly check-in distribution in different districts.
WHY DO PEOPLE MOVE TO OTHER DISTRICTS?
Different data types; Lagrangian vs Eulerian
- Census Data
- Travel Surveys
- Bank Notes
- Traffic Sensors
- Transit Smart Cards
- Social Networks (Twitter, Flicker, ...)
- GPS Trajectories of Prob Vehicles
- Cellular Network Data
Coming soon :)
Project Ideas
Tartu Smart Bike Data
- Is the usage pattern different in men & women?
- Where & When do women avoid to bike?
- Discovering activities.
Daily Mobility Patterns of Tartu
- Effect of weather conditions on modal shift.