Presentation is loading. Please wait.

Presentation is loading. Please wait.

2013.10.24Y. Yuan and M. Raubal1 Investigating the distribution of human activity space from mobile phone usage Yihong Yuan 1,2 and Martin Raubal 1 1 Institute.

Published byColin Hampton Modified over 9 years ago

Similar presentations

Presentation on theme: "2013.10.24Y. Yuan and M. Raubal1 Investigating the distribution of human activity space from mobile phone usage Yihong Yuan 1,2 and Martin Raubal 1 1 Institute."— Presentation transcript:

1 2013.10.24Y. Yuan and M. Raubal1 Investigating the distribution of human activity space from mobile phone usage Yihong Yuan 1,2 and Martin Raubal 1 1 Institute of Cartography and Geoinformation, ETH Zurich 2 Department of Geography, University of California, Santa Barbara yyuan@ethz.ch, mraubal@ethz.ch

2 2013.10.24Y. Yuan and M. Raubal2 Background Information and communication technologies (ICTs) –Greater mobility flexibility –A wide range of Spatio-temporal data sources Modeling the activity pattern of phone users –Call Detailed Records (CDRs) –Low resolution / precision –Uncertainty?

3 2013.10.24Y. Yuan and M. Raubal3 Background Activity space of human beings –“the local areas within which people travel during their daily activities” –How to measure an activity space Size Shape Regularly visited places (e.g., home, work) ……

4 2013.10.24Y. Yuan and M. Raubal4 Objective & Motivation Explore the distribution of activity space of phone users based on (CDRs) Why is this important? –Large scale, urban oriented research –Model fitting Abstract and generalized indicators Provide reference for various fields A neat fitted distribution can facilitate comparison between cities/countries/cultures, etc…

5 2013.10.24Y. Yuan and M. Raubal5 Methodology Three measures of Activity space –Radius -> Scale –Eccentricity -> Shape Shape Index: 1- Eccentricity –Entropy->Regularity Transformation of Trajectories (Gonzalez et al. 2008).

6 2013.10.24Y. Yuan and M. Raubal6 Example dataset Mobile Phone Connections in 10 cities in Northeast China –3 large, 5 median, 2 small –Time, duration, and locations of mobile phone connections over 9 days

7 2013.10.24Y. Yuan and M. Raubal7

8 2013.10.24Y. Yuan and M. Raubal8 Descriptive plots (Probability density functions) Radius (b)

9 2013.10.24Y. Yuan and M. Raubal9 Probability distribution functions Shape Index

10 2013.10.24Y. Yuan and M. Raubal10 Probability distribution functions Entropy

11 2013.10.24Y. Yuan and M. Raubal11 Model Fitting Various models –Why model fitting is needed sometimes –Exponential… –Skewed normal… Cross-variable comparison –One flexible model for all three variables –Weibull distribution For exploratory analysis Both cross-city and cross-variable comparison

12 2013.10.24Y. Yuan and M. Raubal12 Weibull distribution An effective model in various applications such as industrial engineering –where k > 0 is the shape parameter and λ > 0 is the scale parameter of the distribution. –With k=1, the Weibull distribution turns into an exponential distribution The combination of simplicity and flexibility in the shape of the Weibull distribution ( )

13 2013.10.24Y. Yuan and M. Raubal13 Weibull Distribution (Cont.) Scale parameter lamda –How much the curve stretches out –When k stays the same, The larger lamda is,, the distribution gets stretched out to the right and its height decreases, while maintaining its shape and location.

14 2013.10.24Y. Yuan and M. Raubal14 Weibull distribution fitting

15 2013.10.24Y. Yuan and M. Raubal15 Discussion The distribution of radius is close to an exponential distribution (k 2 ≈1) The decay of Shape Index is faster than exponential (k 3 <1). It also shows that the distribution of Entropy is similar to a skewed normal distribution (k 1 ≈2).

16 2013.10.24Y. Yuan and M. Raubal16 Application We have also constructed a regression model showing that –k 2 is significantly correlated with the size of the cities, indicating that bigger cities have a faster decay trend for individual activity radii. –city size is not significantly correlated with either entropy or SI.

17 2013.10.24Y. Yuan and M. Raubal17 Summary Weibull distribution –Fit into three variables The distribution of radius is close to an exponential distribution

18 2013.10.24Y. Yuan and M. Raubal18 Future Work Further examine other potential factors Test the robust of the method –Apply to other data Applications

19 2013.10.24Y. Yuan and M. Raubal19 Acknowledgement This research is funded by: –Swiss National Science Foundation, Grant No. 141284

20 2013.10.24Y. Yuan and M. Raubal20

Download ppt "2013.10.24Y. Yuan and M. Raubal1 Investigating the distribution of human activity space from mobile phone usage Yihong Yuan 1,2 and Martin Raubal 1 1 Institute."

Similar presentations

Yinyin Yuan and Chang-Tsun Li Computer Science Department

Yinyin Yuan and Chang-Tsun Li Computer Science Department
+ Failure rates. + outline Failure rates as continuous distributions Weibull distribution – an example of an exponential distribution with the failure.

+ Failure rates. + outline Failure rates as continuous distributions Weibull distribution – an example of an exponential distribution with the failure.
Evidence synthesis of competing interventions when there is inconsistency in how effectiveness outcomes are measured across studies Nicola Cooper Centre.

Evidence synthesis of competing interventions when there is inconsistency in how effectiveness outcomes are measured across studies Nicola Cooper Centre.
The Normal Distribution

The Normal Distribution
By Venkata Sai Pulluri ( ) Narendra Muppavarapu ( )

By Venkata Sai Pulluri ( ) Narendra Muppavarapu ( )
Mech4740 Numerical Methods, Hong Kong University of Science and Technology. 1 Part Five Curve Fitting.

Mech4740 Numerical Methods, Hong Kong University of Science and Technology. 1 Part Five Curve Fitting.
Descriptive statistics. Statistics Many studies generate large numbers of data points, and to make sense of all that data, researchers use statistics.

Descriptive statistics. Statistics Many studies generate large numbers of data points, and to make sense of all that data, researchers use statistics.
Funding Networks Abdullah Sevincer University of Nevada, Reno Department of Computer Science & Engineering.

Funding Networks Abdullah Sevincer University of Nevada, Reno Department of Computer Science & Engineering.
The role of cartographic visualizations to improve spatial cognition in geography fieldwork Xiaoling Wang, Efiom Ekpenyong, Corné P.J.M. van Elzakker,

The role of cartographic visualizations to improve spatial cognition in geography fieldwork Xiaoling Wang, Efiom Ekpenyong, Corné P.J.M. van Elzakker,
Integration of Software Cost Estimates Across COCOMO, SEER- SEM, and PRICE-S models Tom Harwick, Engineering Specialist Northrop Grumman Corporation Integrated.

Integration of Software Cost Estimates Across COCOMO, SEER- SEM, and PRICE-S models Tom Harwick, Engineering Specialist Northrop Grumman Corporation Integrated.
Continuous Random Variables Chap. 12. COMP 5340/6340 Continuous Random Variables2 Preamble Continuous probability distribution are not related to specific.

Continuous Random Variables Chap. 12. COMP 5340/6340 Continuous Random Variables2 Preamble Continuous probability distribution are not related to specific.
Ch. 6 The Normal Distribution

Ch. 6 The Normal Distribution
Analysis of Simulation Input.. Simulation Machine n Simulation can be considered as an Engine with input and output as follows: Simulation Engine Input.

Analysis of Simulation Input.. Simulation Machine n Simulation can be considered as an Engine with input and output as follows: Simulation Engine Input.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 6-1 Chapter 6 The Normal Distribution and Other Continuous Distributions.

Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 6-1 Chapter 6 The Normal Distribution and Other Continuous Distributions.
Modeling and Prediction of Abdominal Tumor Motion Haobing Wang Department of Computer Science May 9 th, 2003.

Modeling and Prediction of Abdominal Tumor Motion Haobing Wang Department of Computer Science May 9 th, 2003.
Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc. Chap 6-1 Chapter 6 The Normal Distribution Business Statistics: A First Course 5 th.

Business Statistics: A First Course, 5e © 2009 Prentice-Hall, Inc. Chap 6-1 Chapter 6 The Normal Distribution Business Statistics: A First Course 5 th.
Chapter 13, Part 1 STA 200 Summer I 2011. At this point… we have a couple of methods for graphing a data set (histogram, stem-and-leaf plot) we have a.

Chapter 13, Part 1 STA 200 Summer I At this point… we have a couple of methods for graphing a data set (histogram, stem-and-leaf plot) we have a.
Geographic Profiling in Australia – An examination of the predictive potential of serial armed robberies in the Australian Environment By Peter Branca.

Geographic Profiling in Australia – An examination of the predictive potential of serial armed robberies in the Australian Environment By Peter Branca.
6 am 11 am 5 pm Fig. 5: Population density estimates using the aggregated Markov chains. Colour scale represents people per km. Population Activity Estimation.

6 am 11 am 5 pm Fig. 5: Population density estimates using the aggregated Markov chains. Colour scale represents people per km. Population Activity Estimation.
1 Statistical Analysis - Graphical Techniques Dr. Jerrell T. Stracener, SAE Fellow Leadership in Engineering EMIS 7370/5370 STAT 5340 : PROBABILITY AND.

1 Statistical Analysis - Graphical Techniques Dr. Jerrell T. Stracener, SAE Fellow Leadership in Engineering EMIS 7370/5370 STAT 5340 : PROBABILITY AND.

Similar presentations

Ads by Google