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Measures of Human Mobility Using Mobile Phone Records Enhanced with GIS Data.

Williams NE, Thomas TA, Dunbar M, Eagle N, Dobra A - PLoS ONE (2015)

Bottom Line: There is already a significant body of literature that has made key inroads into understanding human mobility using this exciting new data source, and there have been several different measures of mobility used.However, existing mobile phone based mobility measures are inconsistent, inaccurate, and confounded with social characteristics of local context.We also contribute a discussion of the variety of uses for these new measures in developing a better understanding of how human mobility influences micro-level human behaviors and well-being, and macro-level social organization and change.

View Article: PubMed Central - PubMed

Affiliation: Jackson School of International Studies and Department of Sociology, University of Washington, Seattle, Washington, United States of America.

ABSTRACT
In the past decade, large scale mobile phone data have become available for the study of human movement patterns. These data hold an immense promise for understanding human behavior on a vast scale, and with a precision and accuracy never before possible with censuses, surveys or other existing data collection techniques. There is already a significant body of literature that has made key inroads into understanding human mobility using this exciting new data source, and there have been several different measures of mobility used. However, existing mobile phone based mobility measures are inconsistent, inaccurate, and confounded with social characteristics of local context. New measures would best be developed immediately as they will influence future studies of mobility using mobile phone data. In this article, we do exactly this. We discuss problems with existing mobile phone based measures of mobility and describe new methods for measuring mobility that address these concerns. Our measures of mobility, which incorporate both mobile phone records and detailed GIS data, are designed to address the spatial nature of human mobility, to remain independent of social characteristics of context, and to be comparable across geographic regions and time. We also contribute a discussion of the variety of uses for these new measures in developing a better understanding of how human mobility influences micro-level human behaviors and well-being, and macro-level social organization and change.

No MeSH data available.


Map of the monthly spatiotemporal trajectory of the caller with the largest monthly RoG.This caller which we refer to as 𝓟 made two calls in October 2005: the first one from a cellular tower located in the grid cell labeled “Site 1976” and the second one from a cellular tower located in the grid cell labeled “Site 360.” There are 2040 5km x 5km grid cells indexed from 1 (the cell in the lower left corner) to 2040 (the cell in the upper right corner). A site is a grid cell that contains at least one cellular tower. The map shows the location of the straight path between sites 1976 and 360, and also the location of the quickest road route—the road route with the smallest estimated travel time—between the two sites. The straight path between the two towers used by 𝓟 is 236.8 km long, while the straight line path between the centroids of sites 1976 and 360 is 237.2 km long. The quickest road route between the centroids of sites 1976 and 360 is 432.1 km long. The estimated travel time along this route is 6 hours and 4 minutes. The map also shows the center of mass required for the calculation of RoG which is located in the middle of the straight path, as well as Rwanda’s borders, Rwanda’s road network structure with trunk, primary, secondary and tertiary roads, and the locations of the all the 239 cellular towers references in the Rwandan CDRs. We note that only 78 of these towers were active (i.e., handled at least one communication) in October 2005. The grid cells that contain at least one active tower in October 2005 are referred to as sites for that month. The visited sites associated with the spatiotemporal trajectory of 𝓟 are the sites which are intersected by the quickest road route between sites 1976 and 360. There are 19 visited sites which are shown in blue. All the grid cells intersected by this route are called visited cells. The visited cells that are not visited sites are shown in green. The inset shows the capital Kigali and its surrounding area. This is the region with the highest cellular tower density in Rwanda. The Rwandan road network is publicly available data under the Open Database License, and comes from OpenStreetMap (openstreetmap.org), a global open-source mapping project.
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pone.0133630.g001: Map of the monthly spatiotemporal trajectory of the caller with the largest monthly RoG.This caller which we refer to as 𝓟 made two calls in October 2005: the first one from a cellular tower located in the grid cell labeled “Site 1976” and the second one from a cellular tower located in the grid cell labeled “Site 360.” There are 2040 5km x 5km grid cells indexed from 1 (the cell in the lower left corner) to 2040 (the cell in the upper right corner). A site is a grid cell that contains at least one cellular tower. The map shows the location of the straight path between sites 1976 and 360, and also the location of the quickest road route—the road route with the smallest estimated travel time—between the two sites. The straight path between the two towers used by 𝓟 is 236.8 km long, while the straight line path between the centroids of sites 1976 and 360 is 237.2 km long. The quickest road route between the centroids of sites 1976 and 360 is 432.1 km long. The estimated travel time along this route is 6 hours and 4 minutes. The map also shows the center of mass required for the calculation of RoG which is located in the middle of the straight path, as well as Rwanda’s borders, Rwanda’s road network structure with trunk, primary, secondary and tertiary roads, and the locations of the all the 239 cellular towers references in the Rwandan CDRs. We note that only 78 of these towers were active (i.e., handled at least one communication) in October 2005. The grid cells that contain at least one active tower in October 2005 are referred to as sites for that month. The visited sites associated with the spatiotemporal trajectory of 𝓟 are the sites which are intersected by the quickest road route between sites 1976 and 360. There are 19 visited sites which are shown in blue. All the grid cells intersected by this route are called visited cells. The visited cells that are not visited sites are shown in green. The inset shows the capital Kigali and its surrounding area. This is the region with the highest cellular tower density in Rwanda. The Rwandan road network is publicly available data under the Open Database License, and comes from OpenStreetMap (openstreetmap.org), a global open-source mapping project.

Mentions: We exemplify the evaluation of these four measures with the spatiotemporal trajectory of the caller, 𝓟, who had the largest RoG from all 20 million trajectories in the Rwandan data—see Fig 1. During October 2005, 𝓟 made only two calls in this provider’s network: the first call from a location near the northern border with Uganda and the second call from a location near the western border with Democratic Republic of Congo. The NTU measure for this person is equal to 2 (10th percentile). The DT-SL and the MDT measures are both 236.8 km (78th and 100th percentile, respectively). The RoG of 𝓟 is 118.6 km.


Measures of Human Mobility Using Mobile Phone Records Enhanced with GIS Data.

Williams NE, Thomas TA, Dunbar M, Eagle N, Dobra A - PLoS ONE (2015)

Map of the monthly spatiotemporal trajectory of the caller with the largest monthly RoG.This caller which we refer to as 𝓟 made two calls in October 2005: the first one from a cellular tower located in the grid cell labeled “Site 1976” and the second one from a cellular tower located in the grid cell labeled “Site 360.” There are 2040 5km x 5km grid cells indexed from 1 (the cell in the lower left corner) to 2040 (the cell in the upper right corner). A site is a grid cell that contains at least one cellular tower. The map shows the location of the straight path between sites 1976 and 360, and also the location of the quickest road route—the road route with the smallest estimated travel time—between the two sites. The straight path between the two towers used by 𝓟 is 236.8 km long, while the straight line path between the centroids of sites 1976 and 360 is 237.2 km long. The quickest road route between the centroids of sites 1976 and 360 is 432.1 km long. The estimated travel time along this route is 6 hours and 4 minutes. The map also shows the center of mass required for the calculation of RoG which is located in the middle of the straight path, as well as Rwanda’s borders, Rwanda’s road network structure with trunk, primary, secondary and tertiary roads, and the locations of the all the 239 cellular towers references in the Rwandan CDRs. We note that only 78 of these towers were active (i.e., handled at least one communication) in October 2005. The grid cells that contain at least one active tower in October 2005 are referred to as sites for that month. The visited sites associated with the spatiotemporal trajectory of 𝓟 are the sites which are intersected by the quickest road route between sites 1976 and 360. There are 19 visited sites which are shown in blue. All the grid cells intersected by this route are called visited cells. The visited cells that are not visited sites are shown in green. The inset shows the capital Kigali and its surrounding area. This is the region with the highest cellular tower density in Rwanda. The Rwandan road network is publicly available data under the Open Database License, and comes from OpenStreetMap (openstreetmap.org), a global open-source mapping project.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4507852&req=5

pone.0133630.g001: Map of the monthly spatiotemporal trajectory of the caller with the largest monthly RoG.This caller which we refer to as 𝓟 made two calls in October 2005: the first one from a cellular tower located in the grid cell labeled “Site 1976” and the second one from a cellular tower located in the grid cell labeled “Site 360.” There are 2040 5km x 5km grid cells indexed from 1 (the cell in the lower left corner) to 2040 (the cell in the upper right corner). A site is a grid cell that contains at least one cellular tower. The map shows the location of the straight path between sites 1976 and 360, and also the location of the quickest road route—the road route with the smallest estimated travel time—between the two sites. The straight path between the two towers used by 𝓟 is 236.8 km long, while the straight line path between the centroids of sites 1976 and 360 is 237.2 km long. The quickest road route between the centroids of sites 1976 and 360 is 432.1 km long. The estimated travel time along this route is 6 hours and 4 minutes. The map also shows the center of mass required for the calculation of RoG which is located in the middle of the straight path, as well as Rwanda’s borders, Rwanda’s road network structure with trunk, primary, secondary and tertiary roads, and the locations of the all the 239 cellular towers references in the Rwandan CDRs. We note that only 78 of these towers were active (i.e., handled at least one communication) in October 2005. The grid cells that contain at least one active tower in October 2005 are referred to as sites for that month. The visited sites associated with the spatiotemporal trajectory of 𝓟 are the sites which are intersected by the quickest road route between sites 1976 and 360. There are 19 visited sites which are shown in blue. All the grid cells intersected by this route are called visited cells. The visited cells that are not visited sites are shown in green. The inset shows the capital Kigali and its surrounding area. This is the region with the highest cellular tower density in Rwanda. The Rwandan road network is publicly available data under the Open Database License, and comes from OpenStreetMap (openstreetmap.org), a global open-source mapping project.
Mentions: We exemplify the evaluation of these four measures with the spatiotemporal trajectory of the caller, 𝓟, who had the largest RoG from all 20 million trajectories in the Rwandan data—see Fig 1. During October 2005, 𝓟 made only two calls in this provider’s network: the first call from a location near the northern border with Uganda and the second call from a location near the western border with Democratic Republic of Congo. The NTU measure for this person is equal to 2 (10th percentile). The DT-SL and the MDT measures are both 236.8 km (78th and 100th percentile, respectively). The RoG of 𝓟 is 118.6 km.

Bottom Line: There is already a significant body of literature that has made key inroads into understanding human mobility using this exciting new data source, and there have been several different measures of mobility used.However, existing mobile phone based mobility measures are inconsistent, inaccurate, and confounded with social characteristics of local context.We also contribute a discussion of the variety of uses for these new measures in developing a better understanding of how human mobility influences micro-level human behaviors and well-being, and macro-level social organization and change.

View Article: PubMed Central - PubMed

Affiliation: Jackson School of International Studies and Department of Sociology, University of Washington, Seattle, Washington, United States of America.

ABSTRACT
In the past decade, large scale mobile phone data have become available for the study of human movement patterns. These data hold an immense promise for understanding human behavior on a vast scale, and with a precision and accuracy never before possible with censuses, surveys or other existing data collection techniques. There is already a significant body of literature that has made key inroads into understanding human mobility using this exciting new data source, and there have been several different measures of mobility used. However, existing mobile phone based mobility measures are inconsistent, inaccurate, and confounded with social characteristics of local context. New measures would best be developed immediately as they will influence future studies of mobility using mobile phone data. In this article, we do exactly this. We discuss problems with existing mobile phone based measures of mobility and describe new methods for measuring mobility that address these concerns. Our measures of mobility, which incorporate both mobile phone records and detailed GIS data, are designed to address the spatial nature of human mobility, to remain independent of social characteristics of context, and to be comparable across geographic regions and time. We also contribute a discussion of the variety of uses for these new measures in developing a better understanding of how human mobility influences micro-level human behaviors and well-being, and macro-level social organization and change.

No MeSH data available.