From land use
to human mobility:
Inferring intra-city human mobility using individual daily life
pattern and land use map
Minjin Lee & Petter Holme
Sungkyunkwan University
arXiv:1505.07372
- Standing in for the main author … and this is really her
project.
- Heard about this talk today:
‣ Naoki Masuda: “Sorry I can’t see you talk today.”
‣ Me: “What are you talk about? I’ll only talk tomorrow.”
- New to the subject.
- No slides prepared.
- I think this talk will be too short, but:
“nobody has been killed for giving a too short talk”.
Apologies and excuses:
Questions:
Predicting human intra-city mobility (statistics of
human travel)
What can land-use maps tell us?
Data:
Chicago origin-destination study
http://www.cmap.illinois.gov/data/transportation/travel-tracker-survey
25,845 listed their trajectories (name, and rough coordinates of source and
destination) & trip-purposes during a day or two
Google Maps API
Land-use map
https://datahub.cmap.illinois.gov/dataset/land-use-inventory-for-northeast-illinois-2005
49 categories, both relating to the activity (e.g. entertainment) or physical
composition (e.g. river)
Trip purpose
Landuse
1 2 3 4 5 6 7 8 9 10 11 12 13 14
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Frequency
The fraction of destination
land-use type per trip purpose:
Strong correlation between
land use and trip purpose
Land use transition probability matrix:
lots of structure →
could increase predictability of mobility
Model relating land use and mobility:
The flux from location i to j is proportional to:
- The population at i, pi.
- The transition matrix entry ij (the mean flux between
land-use types i to j).
- The the distance dependence from the gravity model.
Tij pi~
Lij
dij
S
and the population is given by the steady state of this
process…