The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’
The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to me...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
He, Qingsong [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018transfer abstract |
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| Schlagwörter: |
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| Umfang: |
13 |
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| Übergeordnetes Werk: |
Enthalten in: Land use policy - Son, Yang-Ju ELSEVIER, 2021, the international journal covering all aspects of land use, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:78 ; year:2018 ; pages:726-738 ; extent:13 |
| Links: |
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| DOI / URN: |
10.1016/j.landusepol.2018.07.020 |
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ELV044523181 |
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| 245 | 1 | 4 | |a The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’ |
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| 520 | |a The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. | ||
| 520 | |a The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. | ||
| 650 | 7 | |a Association rules analysis |2 Elsevier | |
| 650 | 7 | |a Urban growth patterns |2 Elsevier | |
| 650 | 7 | |a Urban vitality |2 Elsevier | |
| 650 | 7 | |a Geographical big data |2 Elsevier | |
| 700 | 1 | |a He, Weishan |4 oth | |
| 700 | 1 | |a Song, Yan |4 oth | |
| 700 | 1 | |a Wu, Jiayu |4 oth | |
| 700 | 1 | |a Yin, Chaohui |4 oth | |
| 700 | 1 | |a Mou, Yanchuan |4 oth | |
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10.1016/j.landusepol.2018.07.020 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001216.pica (DE-627)ELV044523181 (ELSEVIER)S0264-8377(18)30693-8 DE-627 ger DE-627 rakwb eng 630 640 610 VZ He, Qingsong verfasserin aut The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’ 2018transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. Association rules analysis Elsevier Urban growth patterns Elsevier Urban vitality Elsevier Geographical big data Elsevier He, Weishan oth Song, Yan oth Wu, Jiayu oth Yin, Chaohui oth Mou, Yanchuan oth Enthalten in Elsevier Science Son, Yang-Ju ELSEVIER Land use policy 2021 the international journal covering all aspects of land use Amsterdam [u.a.] (DE-627)ELV006296785 volume:78 year:2018 pages:726-738 extent:13 https://doi.org/10.1016/j.landusepol.2018.07.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 78 2018 726-738 13 |
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10.1016/j.landusepol.2018.07.020 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001216.pica (DE-627)ELV044523181 (ELSEVIER)S0264-8377(18)30693-8 DE-627 ger DE-627 rakwb eng 630 640 610 VZ He, Qingsong verfasserin aut The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’ 2018transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. Association rules analysis Elsevier Urban growth patterns Elsevier Urban vitality Elsevier Geographical big data Elsevier He, Weishan oth Song, Yan oth Wu, Jiayu oth Yin, Chaohui oth Mou, Yanchuan oth Enthalten in Elsevier Science Son, Yang-Ju ELSEVIER Land use policy 2021 the international journal covering all aspects of land use Amsterdam [u.a.] (DE-627)ELV006296785 volume:78 year:2018 pages:726-738 extent:13 https://doi.org/10.1016/j.landusepol.2018.07.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 78 2018 726-738 13 |
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10.1016/j.landusepol.2018.07.020 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001216.pica (DE-627)ELV044523181 (ELSEVIER)S0264-8377(18)30693-8 DE-627 ger DE-627 rakwb eng 630 640 610 VZ He, Qingsong verfasserin aut The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’ 2018transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. Association rules analysis Elsevier Urban growth patterns Elsevier Urban vitality Elsevier Geographical big data Elsevier He, Weishan oth Song, Yan oth Wu, Jiayu oth Yin, Chaohui oth Mou, Yanchuan oth Enthalten in Elsevier Science Son, Yang-Ju ELSEVIER Land use policy 2021 the international journal covering all aspects of land use Amsterdam [u.a.] (DE-627)ELV006296785 volume:78 year:2018 pages:726-738 extent:13 https://doi.org/10.1016/j.landusepol.2018.07.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 78 2018 726-738 13 |
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10.1016/j.landusepol.2018.07.020 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001216.pica (DE-627)ELV044523181 (ELSEVIER)S0264-8377(18)30693-8 DE-627 ger DE-627 rakwb eng 630 640 610 VZ He, Qingsong verfasserin aut The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’ 2018transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. Association rules analysis Elsevier Urban growth patterns Elsevier Urban vitality Elsevier Geographical big data Elsevier He, Weishan oth Song, Yan oth Wu, Jiayu oth Yin, Chaohui oth Mou, Yanchuan oth Enthalten in Elsevier Science Son, Yang-Ju ELSEVIER Land use policy 2021 the international journal covering all aspects of land use Amsterdam [u.a.] (DE-627)ELV006296785 volume:78 year:2018 pages:726-738 extent:13 https://doi.org/10.1016/j.landusepol.2018.07.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 78 2018 726-738 13 |
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10.1016/j.landusepol.2018.07.020 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001216.pica (DE-627)ELV044523181 (ELSEVIER)S0264-8377(18)30693-8 DE-627 ger DE-627 rakwb eng 630 640 610 VZ He, Qingsong verfasserin aut The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’ 2018transfer abstract 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. Association rules analysis Elsevier Urban growth patterns Elsevier Urban vitality Elsevier Geographical big data Elsevier He, Weishan oth Song, Yan oth Wu, Jiayu oth Yin, Chaohui oth Mou, Yanchuan oth Enthalten in Elsevier Science Son, Yang-Ju ELSEVIER Land use policy 2021 the international journal covering all aspects of land use Amsterdam [u.a.] (DE-627)ELV006296785 volume:78 year:2018 pages:726-738 extent:13 https://doi.org/10.1016/j.landusepol.2018.07.020 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA AR 78 2018 726-738 13 |
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impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’ |
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The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical ‘big data’ |
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The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. |
| abstractGer |
The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. |
| abstract_unstemmed |
The emergence of geographical ‘big data’ provides new opportunities for studying urban issues. This study uses geographical ‘big data’ on point of interest density (POID), degree of urban function mixing (MIX), location check-in density (CIQD), housing prices (HP), and population change (POPC) to measure the urban vitality of patches of new development that occurred in Chinese cities from 2005 to 2015. The study uses association rule analysis to explore the relationship between different urban growth patterns on urban vitality, and the results indicate that different forms of urban growth have different effects on urban vitality. Infilling is characterized by high values for point of interest density and location check-in density with low values for urban function mixing and mixed values for population change. Edge-expansion is associated with high values for population change and urban function mixtures. Outlying expansion is associated with several negative values for urban vitality, particularly variables related to interactions between people and the environment around them (CIQD). The results indicate that cities may utilize these different forms of urban growth patterns to achieve different goals; for example, infilling may be more effective for office-style development in areas with existing higher population density and urban function mixtures, and edge-expansion may be effective for rapidly absorbing large populations and hosting urban functions that require larger footprints. As such, Chinese cities currently undergoing early stages of development should pursue high-intensity edge-expansion development. To the best of the authors’ knowledge, this is the first attempt to study the relationship between urban expansion types and urban vitality through the use of ‘big data,’ and the results of this study can provide guidance on urban spatial development for government leaders and researchers in the future. |
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