On the regularity of human mobility
Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London,...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Mucelli Rezende Oliveira, Eduardo [verfasserIn] |
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| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016transfer abstract |
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| Schlagwörter: |
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| Umfang: |
18 |
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| Übergeordnetes Werk: |
Enthalten in: BIG-OH: BInarization of gradient orientation histograms - Baber, Junaid ELSEVIER, 2014transfer abstract, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:33 ; year:2016 ; pages:73-90 ; extent:18 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.pmcj.2016.04.005 |
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ELV04002668X |
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| 520 | |a Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. | ||
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10.1016/j.pmcj.2016.04.005 doi GBV00000000000110A.pica (DE-627)ELV04002668X (ELSEVIER)S1574-1192(16)30028-1 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ Mucelli Rezende Oliveira, Eduardo verfasserin aut On the regularity of human mobility 2016transfer abstract 18 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. Dataset Elsevier Analysis Elsevier Mobility Elsevier Human mobility Elsevier Carneiro Viana, Aline oth Sarraute, Carlos oth Brea, Jorge oth Alvarez-Hamelin, Ignacio oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:33 year:2016 pages:73-90 extent:18 https://doi.org/10.1016/j.pmcj.2016.04.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 33 2016 73-90 18 045F 004 |
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10.1016/j.pmcj.2016.04.005 doi GBV00000000000110A.pica (DE-627)ELV04002668X (ELSEVIER)S1574-1192(16)30028-1 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ Mucelli Rezende Oliveira, Eduardo verfasserin aut On the regularity of human mobility 2016transfer abstract 18 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. Dataset Elsevier Analysis Elsevier Mobility Elsevier Human mobility Elsevier Carneiro Viana, Aline oth Sarraute, Carlos oth Brea, Jorge oth Alvarez-Hamelin, Ignacio oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:33 year:2016 pages:73-90 extent:18 https://doi.org/10.1016/j.pmcj.2016.04.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 33 2016 73-90 18 045F 004 |
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10.1016/j.pmcj.2016.04.005 doi GBV00000000000110A.pica (DE-627)ELV04002668X (ELSEVIER)S1574-1192(16)30028-1 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ Mucelli Rezende Oliveira, Eduardo verfasserin aut On the regularity of human mobility 2016transfer abstract 18 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. Dataset Elsevier Analysis Elsevier Mobility Elsevier Human mobility Elsevier Carneiro Viana, Aline oth Sarraute, Carlos oth Brea, Jorge oth Alvarez-Hamelin, Ignacio oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:33 year:2016 pages:73-90 extent:18 https://doi.org/10.1016/j.pmcj.2016.04.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 33 2016 73-90 18 045F 004 |
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10.1016/j.pmcj.2016.04.005 doi GBV00000000000110A.pica (DE-627)ELV04002668X (ELSEVIER)S1574-1192(16)30028-1 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ Mucelli Rezende Oliveira, Eduardo verfasserin aut On the regularity of human mobility 2016transfer abstract 18 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. Dataset Elsevier Analysis Elsevier Mobility Elsevier Human mobility Elsevier Carneiro Viana, Aline oth Sarraute, Carlos oth Brea, Jorge oth Alvarez-Hamelin, Ignacio oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:33 year:2016 pages:73-90 extent:18 https://doi.org/10.1016/j.pmcj.2016.04.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 33 2016 73-90 18 045F 004 |
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10.1016/j.pmcj.2016.04.005 doi GBV00000000000110A.pica (DE-627)ELV04002668X (ELSEVIER)S1574-1192(16)30028-1 DE-627 ger DE-627 rakwb eng 004 004 DE-600 004 VZ Mucelli Rezende Oliveira, Eduardo verfasserin aut On the regularity of human mobility 2016transfer abstract 18 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. Dataset Elsevier Analysis Elsevier Mobility Elsevier Human mobility Elsevier Carneiro Viana, Aline oth Sarraute, Carlos oth Brea, Jorge oth Alvarez-Hamelin, Ignacio oth Enthalten in Elsevier Baber, Junaid ELSEVIER BIG-OH: BInarization of gradient orientation histograms 2014transfer abstract Amsterdam [u.a.] (DE-627)ELV02262399X volume:33 year:2016 pages:73-90 extent:18 https://doi.org/10.1016/j.pmcj.2016.04.005 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_78 GBV_ILN_100 GBV_ILN_130 GBV_ILN_300 AR 33 2016 73-90 18 045F 004 |
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Mucelli Rezende Oliveira, Eduardo |
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On the regularity of human mobility |
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On the regularity of human mobility |
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10.1016/j.pmcj.2016.04.005 |
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on the regularity of human mobility |
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On the regularity of human mobility |
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Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. |
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Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. |
| abstract_unstemmed |
Understanding human mobility patterns is crucial to fields such as urban mobility and mobile network planning. For this purpose, we make use of large-scale datasets recording individuals spatio-temporal locations, from eight major world cities: Beijing, Tokyo, New York, Paris, San Francisco, London, Moscow and Mexico City. Our contributions are two-fold: first, we show significant similarities in people’s mobility habits regardless of the city and nature of the dataset. Second, we unveil three persistent traits present in an individual’s urban mobility: repetitiveness, preference for shortest-paths, and confinement. These characteristics uncover people’s tendency to revisit few favorite venues using the shortest-path available. |
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On the regularity of human mobility |
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Carneiro Viana, Aline Sarraute, Carlos Brea, Jorge Alvarez-Hamelin, Ignacio |
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