Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China

Abstract The spatial pattern and mechanism of human flow are of great significance for urban planning, economic development, transportation planning and so on. In this study, we used cell phone location data to represent the human flow network in Guangdong Province, China, using the 21 cities in Gua...
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Autor*in:	Zhuo, Li [verfasserIn] Chen, Zhuo Wu, Chengzhuo Shi, Qingli Gu, Zhihui Tao, Haiyan Li, Qiuping

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Cell phone location data Network analysis Human flow Human mobility

Anmerkung:	© The Author(s) 2022

Übergeordnetes Werk:	Enthalten in: Computational urban science - [Singapore] : Springer Singapore, 2021, 2(2022), 1 vom: 21. Jan.
Übergeordnetes Werk:	volume:2 ; year:2022 ; number:1 ; day:21 ; month:01

Links:	Volltext

DOI / URN:	10.1007/s43762-022-00033-2

Katalog-ID:	SPR046033343

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520			\|a Abstract The spatial pattern and mechanism of human flow are of great significance for urban planning, economic development, transportation planning and so on. In this study, we used cell phone location data to represent the human flow network in Guangdong Province, China, using the 21 cities in Guangdong as “nodes” and the human flow intensity among them as “edges”. Then we explored macro and micro features of the human flow network, by using the index of degree distribution, alter-based centrality and alter-based power, respectively. Finally, we proposed a human flow estimation model which integrates individual urban characteristics, intercity links, and differences to further analyze the affecting factors of human flow. We found that the human flow network in this region is significantly scale-free, with Guangzhou, Shenzhen, Foshan, and Dongguan being the most important cities. We also found that the newly proposed model can explain the human flow in the study area, with an R2 of 0.914. Analysis results show that the factors of employment in tertiary sector, intercity internet attention, intercity differences in the number of tertiary workers, differences in population size, and distance have significant impacts on the human flow. This study may provide insights into human activity mechanisms that can contribute to urban planning and management.
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allfields	10.1007/s43762-022-00033-2 doi (DE-627)SPR046033343 (SPR)s43762-022-00033-2-e DE-627 ger DE-627 rakwb eng Zhuo, Li verfasserin aut Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract The spatial pattern and mechanism of human flow are of great significance for urban planning, economic development, transportation planning and so on. In this study, we used cell phone location data to represent the human flow network in Guangdong Province, China, using the 21 cities in Guangdong as “nodes” and the human flow intensity among them as “edges”. Then we explored macro and micro features of the human flow network, by using the index of degree distribution, alter-based centrality and alter-based power, respectively. Finally, we proposed a human flow estimation model which integrates individual urban characteristics, intercity links, and differences to further analyze the affecting factors of human flow. We found that the human flow network in this region is significantly scale-free, with Guangzhou, Shenzhen, Foshan, and Dongguan being the most important cities. We also found that the newly proposed model can explain the human flow in the study area, with an R2 of 0.914. Analysis results show that the factors of employment in tertiary sector, intercity internet attention, intercity differences in the number of tertiary workers, differences in population size, and distance have significant impacts on the human flow. This study may provide insights into human activity mechanisms that can contribute to urban planning and management. Cell phone location data (dpeaa)DE-He213 Network analysis (dpeaa)DE-He213 Human flow (dpeaa)DE-He213 Human mobility (dpeaa)DE-He213 Chen, Zhuo aut Wu, Chengzhuo aut Shi, Qingli aut Gu, Zhihui aut Tao, Haiyan aut Li, Qiuping aut Enthalten in Computational urban science [Singapore] : Springer Singapore, 2021 2(2022), 1 vom: 21. Jan. (DE-627)1755847114 (DE-600)3061590-2 2730-6852 nnns volume:2 year:2022 number:1 day:21 month:01 https://dx.doi.org/10.1007/s43762-022-00033-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2 2022 1 21 01
spelling	10.1007/s43762-022-00033-2 doi (DE-627)SPR046033343 (SPR)s43762-022-00033-2-e DE-627 ger DE-627 rakwb eng Zhuo, Li verfasserin aut Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract The spatial pattern and mechanism of human flow are of great significance for urban planning, economic development, transportation planning and so on. In this study, we used cell phone location data to represent the human flow network in Guangdong Province, China, using the 21 cities in Guangdong as “nodes” and the human flow intensity among them as “edges”. Then we explored macro and micro features of the human flow network, by using the index of degree distribution, alter-based centrality and alter-based power, respectively. Finally, we proposed a human flow estimation model which integrates individual urban characteristics, intercity links, and differences to further analyze the affecting factors of human flow. We found that the human flow network in this region is significantly scale-free, with Guangzhou, Shenzhen, Foshan, and Dongguan being the most important cities. We also found that the newly proposed model can explain the human flow in the study area, with an R2 of 0.914. Analysis results show that the factors of employment in tertiary sector, intercity internet attention, intercity differences in the number of tertiary workers, differences in population size, and distance have significant impacts on the human flow. This study may provide insights into human activity mechanisms that can contribute to urban planning and management. Cell phone location data (dpeaa)DE-He213 Network analysis (dpeaa)DE-He213 Human flow (dpeaa)DE-He213 Human mobility (dpeaa)DE-He213 Chen, Zhuo aut Wu, Chengzhuo aut Shi, Qingli aut Gu, Zhihui aut Tao, Haiyan aut Li, Qiuping aut Enthalten in Computational urban science [Singapore] : Springer Singapore, 2021 2(2022), 1 vom: 21. Jan. (DE-627)1755847114 (DE-600)3061590-2 2730-6852 nnns volume:2 year:2022 number:1 day:21 month:01 https://dx.doi.org/10.1007/s43762-022-00033-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2 2022 1 21 01
allfields_unstemmed	10.1007/s43762-022-00033-2 doi (DE-627)SPR046033343 (SPR)s43762-022-00033-2-e DE-627 ger DE-627 rakwb eng Zhuo, Li verfasserin aut Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract The spatial pattern and mechanism of human flow are of great significance for urban planning, economic development, transportation planning and so on. In this study, we used cell phone location data to represent the human flow network in Guangdong Province, China, using the 21 cities in Guangdong as “nodes” and the human flow intensity among them as “edges”. Then we explored macro and micro features of the human flow network, by using the index of degree distribution, alter-based centrality and alter-based power, respectively. Finally, we proposed a human flow estimation model which integrates individual urban characteristics, intercity links, and differences to further analyze the affecting factors of human flow. We found that the human flow network in this region is significantly scale-free, with Guangzhou, Shenzhen, Foshan, and Dongguan being the most important cities. We also found that the newly proposed model can explain the human flow in the study area, with an R2 of 0.914. Analysis results show that the factors of employment in tertiary sector, intercity internet attention, intercity differences in the number of tertiary workers, differences in population size, and distance have significant impacts on the human flow. This study may provide insights into human activity mechanisms that can contribute to urban planning and management. Cell phone location data (dpeaa)DE-He213 Network analysis (dpeaa)DE-He213 Human flow (dpeaa)DE-He213 Human mobility (dpeaa)DE-He213 Chen, Zhuo aut Wu, Chengzhuo aut Shi, Qingli aut Gu, Zhihui aut Tao, Haiyan aut Li, Qiuping aut Enthalten in Computational urban science [Singapore] : Springer Singapore, 2021 2(2022), 1 vom: 21. Jan. (DE-627)1755847114 (DE-600)3061590-2 2730-6852 nnns volume:2 year:2022 number:1 day:21 month:01 https://dx.doi.org/10.1007/s43762-022-00033-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2 2022 1 21 01
allfieldsGer	10.1007/s43762-022-00033-2 doi (DE-627)SPR046033343 (SPR)s43762-022-00033-2-e DE-627 ger DE-627 rakwb eng Zhuo, Li verfasserin aut Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract The spatial pattern and mechanism of human flow are of great significance for urban planning, economic development, transportation planning and so on. In this study, we used cell phone location data to represent the human flow network in Guangdong Province, China, using the 21 cities in Guangdong as “nodes” and the human flow intensity among them as “edges”. Then we explored macro and micro features of the human flow network, by using the index of degree distribution, alter-based centrality and alter-based power, respectively. Finally, we proposed a human flow estimation model which integrates individual urban characteristics, intercity links, and differences to further analyze the affecting factors of human flow. We found that the human flow network in this region is significantly scale-free, with Guangzhou, Shenzhen, Foshan, and Dongguan being the most important cities. We also found that the newly proposed model can explain the human flow in the study area, with an R2 of 0.914. Analysis results show that the factors of employment in tertiary sector, intercity internet attention, intercity differences in the number of tertiary workers, differences in population size, and distance have significant impacts on the human flow. This study may provide insights into human activity mechanisms that can contribute to urban planning and management. Cell phone location data (dpeaa)DE-He213 Network analysis (dpeaa)DE-He213 Human flow (dpeaa)DE-He213 Human mobility (dpeaa)DE-He213 Chen, Zhuo aut Wu, Chengzhuo aut Shi, Qingli aut Gu, Zhihui aut Tao, Haiyan aut Li, Qiuping aut Enthalten in Computational urban science [Singapore] : Springer Singapore, 2021 2(2022), 1 vom: 21. Jan. (DE-627)1755847114 (DE-600)3061590-2 2730-6852 nnns volume:2 year:2022 number:1 day:21 month:01 https://dx.doi.org/10.1007/s43762-022-00033-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2 2022 1 21 01
allfieldsSound	10.1007/s43762-022-00033-2 doi (DE-627)SPR046033343 (SPR)s43762-022-00033-2-e DE-627 ger DE-627 rakwb eng Zhuo, Li verfasserin aut Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract The spatial pattern and mechanism of human flow are of great significance for urban planning, economic development, transportation planning and so on. In this study, we used cell phone location data to represent the human flow network in Guangdong Province, China, using the 21 cities in Guangdong as “nodes” and the human flow intensity among them as “edges”. Then we explored macro and micro features of the human flow network, by using the index of degree distribution, alter-based centrality and alter-based power, respectively. Finally, we proposed a human flow estimation model which integrates individual urban characteristics, intercity links, and differences to further analyze the affecting factors of human flow. We found that the human flow network in this region is significantly scale-free, with Guangzhou, Shenzhen, Foshan, and Dongguan being the most important cities. We also found that the newly proposed model can explain the human flow in the study area, with an R2 of 0.914. Analysis results show that the factors of employment in tertiary sector, intercity internet attention, intercity differences in the number of tertiary workers, differences in population size, and distance have significant impacts on the human flow. This study may provide insights into human activity mechanisms that can contribute to urban planning and management. Cell phone location data (dpeaa)DE-He213 Network analysis (dpeaa)DE-He213 Human flow (dpeaa)DE-He213 Human mobility (dpeaa)DE-He213 Chen, Zhuo aut Wu, Chengzhuo aut Shi, Qingli aut Gu, Zhihui aut Tao, Haiyan aut Li, Qiuping aut Enthalten in Computational urban science [Singapore] : Springer Singapore, 2021 2(2022), 1 vom: 21. Jan. (DE-627)1755847114 (DE-600)3061590-2 2730-6852 nnns volume:2 year:2022 number:1 day:21 month:01 https://dx.doi.org/10.1007/s43762-022-00033-2 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_138 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_187 GBV_ILN_213 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_647 GBV_ILN_702 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 2 2022 1 21 01
language	English
source	Enthalten in Computational urban science 2(2022), 1 vom: 21. Jan. volume:2 year:2022 number:1 day:21 month:01
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institution	findex.gbv.de
topic_facet	Cell phone location data Network analysis Human flow Human mobility
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container_title	Computational urban science
authorswithroles_txt_mv	Zhuo, Li @@aut@@ Chen, Zhuo @@aut@@ Wu, Chengzhuo @@aut@@ Shi, Qingli @@aut@@ Gu, Zhihui @@aut@@ Tao, Haiyan @@aut@@ Li, Qiuping @@aut@@
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author	Zhuo, Li
spellingShingle	Zhuo, Li misc Cell phone location data misc Network analysis misc Human flow misc Human mobility Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China
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topic_title	Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China Cell phone location data (dpeaa)DE-He213 Network analysis (dpeaa)DE-He213 Human flow (dpeaa)DE-He213 Human mobility (dpeaa)DE-He213
topic	misc Cell phone location data misc Network analysis misc Human flow misc Human mobility
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title	Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China
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title_full	Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China
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author_browse	Zhuo, Li Chen, Zhuo Wu, Chengzhuo Shi, Qingli Gu, Zhihui Tao, Haiyan Li, Qiuping
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title_sort	deriving intercity human flow pattern and mechanism based on cell phone location data: case study of guangdong province, china
title_auth	Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China
abstract	Abstract The spatial pattern and mechanism of human flow are of great significance for urban planning, economic development, transportation planning and so on. In this study, we used cell phone location data to represent the human flow network in Guangdong Province, China, using the 21 cities in Guangdong as “nodes” and the human flow intensity among them as “edges”. Then we explored macro and micro features of the human flow network, by using the index of degree distribution, alter-based centrality and alter-based power, respectively. Finally, we proposed a human flow estimation model which integrates individual urban characteristics, intercity links, and differences to further analyze the affecting factors of human flow. We found that the human flow network in this region is significantly scale-free, with Guangzhou, Shenzhen, Foshan, and Dongguan being the most important cities. We also found that the newly proposed model can explain the human flow in the study area, with an R2 of 0.914. Analysis results show that the factors of employment in tertiary sector, intercity internet attention, intercity differences in the number of tertiary workers, differences in population size, and distance have significant impacts on the human flow. This study may provide insights into human activity mechanisms that can contribute to urban planning and management. © The Author(s) 2022
abstractGer	Abstract The spatial pattern and mechanism of human flow are of great significance for urban planning, economic development, transportation planning and so on. In this study, we used cell phone location data to represent the human flow network in Guangdong Province, China, using the 21 cities in Guangdong as “nodes” and the human flow intensity among them as “edges”. Then we explored macro and micro features of the human flow network, by using the index of degree distribution, alter-based centrality and alter-based power, respectively. Finally, we proposed a human flow estimation model which integrates individual urban characteristics, intercity links, and differences to further analyze the affecting factors of human flow. We found that the human flow network in this region is significantly scale-free, with Guangzhou, Shenzhen, Foshan, and Dongguan being the most important cities. We also found that the newly proposed model can explain the human flow in the study area, with an R2 of 0.914. Analysis results show that the factors of employment in tertiary sector, intercity internet attention, intercity differences in the number of tertiary workers, differences in population size, and distance have significant impacts on the human flow. This study may provide insights into human activity mechanisms that can contribute to urban planning and management. © The Author(s) 2022
abstract_unstemmed	Abstract The spatial pattern and mechanism of human flow are of great significance for urban planning, economic development, transportation planning and so on. In this study, we used cell phone location data to represent the human flow network in Guangdong Province, China, using the 21 cities in Guangdong as “nodes” and the human flow intensity among them as “edges”. Then we explored macro and micro features of the human flow network, by using the index of degree distribution, alter-based centrality and alter-based power, respectively. Finally, we proposed a human flow estimation model which integrates individual urban characteristics, intercity links, and differences to further analyze the affecting factors of human flow. We found that the human flow network in this region is significantly scale-free, with Guangzhou, Shenzhen, Foshan, and Dongguan being the most important cities. We also found that the newly proposed model can explain the human flow in the study area, with an R2 of 0.914. Analysis results show that the factors of employment in tertiary sector, intercity internet attention, intercity differences in the number of tertiary workers, differences in population size, and distance have significant impacts on the human flow. This study may provide insights into human activity mechanisms that can contribute to urban planning and management. © The Author(s) 2022
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title_short	Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China
url	https://dx.doi.org/10.1007/s43762-022-00033-2
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author2	Chen, Zhuo Wu, Chengzhuo Shi, Qingli Gu, Zhihui Tao, Haiyan Li, Qiuping
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Deriving intercity human flow pattern and mechanism based on cell phone location data: case study of Guangdong Province, China

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