Spatiotemporal impacts of metro network structure on land use change

Numerous studies have presented compelling findings regarding the favorable influence exerted by the construction of metro systems on the development of land use along the routes. However, the effects of metro network structure on land use change, especially the long-term dynamic effects, remain unc...
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Gespeichert in:

Autor*in:	Yan, Xuexin [verfasserIn] Liu, Yue [verfasserIn] Sun, Hanwen [verfasserIn] Li, Jinwen [verfasserIn] Yang, Hong [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Rechteinformationen:	Open Access Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International ; CC BY-NC-ND 4.0

Schlagwörter:	Complex network model Geographically and temporally weighted regression Land-use degree composite index Metro network structure Spatiotemporal analysis

Übergeordnetes Werk:	Enthalten in: Journal of urban management - Amsterdam [u.a.] : Elsevier, 2012, 13(2024), 2 vom: Juni, Seite 183-200
Übergeordnetes Werk:	volume:13 ; year:2024 ; number:2 ; month:06 ; pages:183-200

Links:	Link aufrufen Link aufrufen

DOI / URN:	10.1016/j.jum.2024.04.002

Katalog-ID:	1895655323

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allfields	10.1016/j.jum.2024.04.002 doi (DE-627)1895655323 (DE-599)KXP1895655323 DE-627 ger DE-627 rda eng Yan, Xuexin verfasserin (DE-588)1342444957 (DE-627)1902989767 aut Spatiotemporal impacts of metro network structure on land use change Xuexin Yan, Yue Liu, Hanwen Sun, Jinwen Li, Hong Yang 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Numerous studies have presented compelling findings regarding the favorable influence exerted by the construction of metro systems on the development of land use along the routes. However, the effects of metro network structure on land use change, especially the long-term dynamic effects, remain uncertain. To address this gap, this research utilizes land use coverage data and metro network data from Wuhan, China, spanning the period from 2014 to 2019. A complex network model is employed to analyze changes in the metro network structure, and the GTWR model is employed to investigate the impact of the of metro network structure on land use change. The results indicate that metro construction effectively stimulates land use change along the routes, predominantly leading to the conversion of non-construction land into construction land. Global accessibility, degree centrality, betweenness centrality, and eigenvector centrality, within the metro network structure attributes demonstrate significant positive effects on land use change, and these effects exhibit considerable spatiotemporal non-stationarity. Additionally, built environment factors surrounding metro stations, such as population density, plot ratio, street intersection density, and the quantity of bus stops, also exhibit notably spatiotemporal effects on land use change. These findings indicate that government agencies and urban planners should concentrate on optimizing the distribution of the urban metro network to improve its overall structural efficiency. When planning the construction of the metro network, careful attention should be paid to the built environment near the stations to effectively facilitate land use development in the vicinity. DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/ Complex network model (dpeaa)DE-206 Geographically and temporally weighted regression (dpeaa)DE-206 Land-use degree composite index (dpeaa)DE-206 Metro network structure (dpeaa)DE-206 Spatiotemporal analysis (dpeaa)DE-206 Liu, Yue verfasserin (DE-588)1327284197 (DE-627)1886828679 aut Sun, Hanwen verfasserin (DE-588)1342445163 (DE-627)1902990269 aut Li, Jinwen verfasserin (DE-588)1342445333 (DE-627)190299065X aut Yang, Hong verfasserin (DE-588)132728992X (DE-627)1886829462 aut Enthalten in Journal of urban management Amsterdam [u.a.] : Elsevier, 2012 13(2024), 2 vom: Juni, Seite 183-200 Online-Ressource (DE-627)837630150 (DE-600)2837330-3 (DE-576)446573256 2589-0360 nnns volume:13 year:2024 number:2 month:06 pages:183-200 https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf Verlag kostenfrei https://doi.org/10.1016/j.jum.2024.04.002 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 13 2024 2 6 183-200 26 01 0206 4552450735 x1z 17-07-24 2403 01 DE-LFER 4565457288 00 --%%-- --%%-- n --%%-- l01 12-08-24 2403 01 DE-LFER https://doi.org/10.1016/j.jum.2024.04.002 2403 01 DE-LFER https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf
spelling	10.1016/j.jum.2024.04.002 doi (DE-627)1895655323 (DE-599)KXP1895655323 DE-627 ger DE-627 rda eng Yan, Xuexin verfasserin (DE-588)1342444957 (DE-627)1902989767 aut Spatiotemporal impacts of metro network structure on land use change Xuexin Yan, Yue Liu, Hanwen Sun, Jinwen Li, Hong Yang 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Numerous studies have presented compelling findings regarding the favorable influence exerted by the construction of metro systems on the development of land use along the routes. However, the effects of metro network structure on land use change, especially the long-term dynamic effects, remain uncertain. To address this gap, this research utilizes land use coverage data and metro network data from Wuhan, China, spanning the period from 2014 to 2019. A complex network model is employed to analyze changes in the metro network structure, and the GTWR model is employed to investigate the impact of the of metro network structure on land use change. The results indicate that metro construction effectively stimulates land use change along the routes, predominantly leading to the conversion of non-construction land into construction land. Global accessibility, degree centrality, betweenness centrality, and eigenvector centrality, within the metro network structure attributes demonstrate significant positive effects on land use change, and these effects exhibit considerable spatiotemporal non-stationarity. Additionally, built environment factors surrounding metro stations, such as population density, plot ratio, street intersection density, and the quantity of bus stops, also exhibit notably spatiotemporal effects on land use change. These findings indicate that government agencies and urban planners should concentrate on optimizing the distribution of the urban metro network to improve its overall structural efficiency. When planning the construction of the metro network, careful attention should be paid to the built environment near the stations to effectively facilitate land use development in the vicinity. DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/ Complex network model (dpeaa)DE-206 Geographically and temporally weighted regression (dpeaa)DE-206 Land-use degree composite index (dpeaa)DE-206 Metro network structure (dpeaa)DE-206 Spatiotemporal analysis (dpeaa)DE-206 Liu, Yue verfasserin (DE-588)1327284197 (DE-627)1886828679 aut Sun, Hanwen verfasserin (DE-588)1342445163 (DE-627)1902990269 aut Li, Jinwen verfasserin (DE-588)1342445333 (DE-627)190299065X aut Yang, Hong verfasserin (DE-588)132728992X (DE-627)1886829462 aut Enthalten in Journal of urban management Amsterdam [u.a.] : Elsevier, 2012 13(2024), 2 vom: Juni, Seite 183-200 Online-Ressource (DE-627)837630150 (DE-600)2837330-3 (DE-576)446573256 2589-0360 nnns volume:13 year:2024 number:2 month:06 pages:183-200 https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf Verlag kostenfrei https://doi.org/10.1016/j.jum.2024.04.002 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 13 2024 2 6 183-200 26 01 0206 4552450735 x1z 17-07-24 2403 01 DE-LFER 4565457288 00 --%%-- --%%-- n --%%-- l01 12-08-24 2403 01 DE-LFER https://doi.org/10.1016/j.jum.2024.04.002 2403 01 DE-LFER https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf
allfields_unstemmed	10.1016/j.jum.2024.04.002 doi (DE-627)1895655323 (DE-599)KXP1895655323 DE-627 ger DE-627 rda eng Yan, Xuexin verfasserin (DE-588)1342444957 (DE-627)1902989767 aut Spatiotemporal impacts of metro network structure on land use change Xuexin Yan, Yue Liu, Hanwen Sun, Jinwen Li, Hong Yang 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Numerous studies have presented compelling findings regarding the favorable influence exerted by the construction of metro systems on the development of land use along the routes. However, the effects of metro network structure on land use change, especially the long-term dynamic effects, remain uncertain. To address this gap, this research utilizes land use coverage data and metro network data from Wuhan, China, spanning the period from 2014 to 2019. A complex network model is employed to analyze changes in the metro network structure, and the GTWR model is employed to investigate the impact of the of metro network structure on land use change. The results indicate that metro construction effectively stimulates land use change along the routes, predominantly leading to the conversion of non-construction land into construction land. Global accessibility, degree centrality, betweenness centrality, and eigenvector centrality, within the metro network structure attributes demonstrate significant positive effects on land use change, and these effects exhibit considerable spatiotemporal non-stationarity. Additionally, built environment factors surrounding metro stations, such as population density, plot ratio, street intersection density, and the quantity of bus stops, also exhibit notably spatiotemporal effects on land use change. These findings indicate that government agencies and urban planners should concentrate on optimizing the distribution of the urban metro network to improve its overall structural efficiency. When planning the construction of the metro network, careful attention should be paid to the built environment near the stations to effectively facilitate land use development in the vicinity. DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/ Complex network model (dpeaa)DE-206 Geographically and temporally weighted regression (dpeaa)DE-206 Land-use degree composite index (dpeaa)DE-206 Metro network structure (dpeaa)DE-206 Spatiotemporal analysis (dpeaa)DE-206 Liu, Yue verfasserin (DE-588)1327284197 (DE-627)1886828679 aut Sun, Hanwen verfasserin (DE-588)1342445163 (DE-627)1902990269 aut Li, Jinwen verfasserin (DE-588)1342445333 (DE-627)190299065X aut Yang, Hong verfasserin (DE-588)132728992X (DE-627)1886829462 aut Enthalten in Journal of urban management Amsterdam [u.a.] : Elsevier, 2012 13(2024), 2 vom: Juni, Seite 183-200 Online-Ressource (DE-627)837630150 (DE-600)2837330-3 (DE-576)446573256 2589-0360 nnns volume:13 year:2024 number:2 month:06 pages:183-200 https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf Verlag kostenfrei https://doi.org/10.1016/j.jum.2024.04.002 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 13 2024 2 6 183-200 26 01 0206 4552450735 x1z 17-07-24 2403 01 DE-LFER 4565457288 00 --%%-- --%%-- n --%%-- l01 12-08-24 2403 01 DE-LFER https://doi.org/10.1016/j.jum.2024.04.002 2403 01 DE-LFER https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf
allfieldsGer	10.1016/j.jum.2024.04.002 doi (DE-627)1895655323 (DE-599)KXP1895655323 DE-627 ger DE-627 rda eng Yan, Xuexin verfasserin (DE-588)1342444957 (DE-627)1902989767 aut Spatiotemporal impacts of metro network structure on land use change Xuexin Yan, Yue Liu, Hanwen Sun, Jinwen Li, Hong Yang 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Numerous studies have presented compelling findings regarding the favorable influence exerted by the construction of metro systems on the development of land use along the routes. However, the effects of metro network structure on land use change, especially the long-term dynamic effects, remain uncertain. To address this gap, this research utilizes land use coverage data and metro network data from Wuhan, China, spanning the period from 2014 to 2019. A complex network model is employed to analyze changes in the metro network structure, and the GTWR model is employed to investigate the impact of the of metro network structure on land use change. The results indicate that metro construction effectively stimulates land use change along the routes, predominantly leading to the conversion of non-construction land into construction land. Global accessibility, degree centrality, betweenness centrality, and eigenvector centrality, within the metro network structure attributes demonstrate significant positive effects on land use change, and these effects exhibit considerable spatiotemporal non-stationarity. Additionally, built environment factors surrounding metro stations, such as population density, plot ratio, street intersection density, and the quantity of bus stops, also exhibit notably spatiotemporal effects on land use change. These findings indicate that government agencies and urban planners should concentrate on optimizing the distribution of the urban metro network to improve its overall structural efficiency. When planning the construction of the metro network, careful attention should be paid to the built environment near the stations to effectively facilitate land use development in the vicinity. DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/ Complex network model (dpeaa)DE-206 Geographically and temporally weighted regression (dpeaa)DE-206 Land-use degree composite index (dpeaa)DE-206 Metro network structure (dpeaa)DE-206 Spatiotemporal analysis (dpeaa)DE-206 Liu, Yue verfasserin (DE-588)1327284197 (DE-627)1886828679 aut Sun, Hanwen verfasserin (DE-588)1342445163 (DE-627)1902990269 aut Li, Jinwen verfasserin (DE-588)1342445333 (DE-627)190299065X aut Yang, Hong verfasserin (DE-588)132728992X (DE-627)1886829462 aut Enthalten in Journal of urban management Amsterdam [u.a.] : Elsevier, 2012 13(2024), 2 vom: Juni, Seite 183-200 Online-Ressource (DE-627)837630150 (DE-600)2837330-3 (DE-576)446573256 2589-0360 nnns volume:13 year:2024 number:2 month:06 pages:183-200 https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf Verlag kostenfrei https://doi.org/10.1016/j.jum.2024.04.002 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 13 2024 2 6 183-200 26 01 0206 4552450735 x1z 17-07-24 2403 01 DE-LFER 4565457288 00 --%%-- --%%-- n --%%-- l01 12-08-24 2403 01 DE-LFER https://doi.org/10.1016/j.jum.2024.04.002 2403 01 DE-LFER https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf
allfieldsSound	10.1016/j.jum.2024.04.002 doi (DE-627)1895655323 (DE-599)KXP1895655323 DE-627 ger DE-627 rda eng Yan, Xuexin verfasserin (DE-588)1342444957 (DE-627)1902989767 aut Spatiotemporal impacts of metro network structure on land use change Xuexin Yan, Yue Liu, Hanwen Sun, Jinwen Li, Hong Yang 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 Numerous studies have presented compelling findings regarding the favorable influence exerted by the construction of metro systems on the development of land use along the routes. However, the effects of metro network structure on land use change, especially the long-term dynamic effects, remain uncertain. To address this gap, this research utilizes land use coverage data and metro network data from Wuhan, China, spanning the period from 2014 to 2019. A complex network model is employed to analyze changes in the metro network structure, and the GTWR model is employed to investigate the impact of the of metro network structure on land use change. The results indicate that metro construction effectively stimulates land use change along the routes, predominantly leading to the conversion of non-construction land into construction land. Global accessibility, degree centrality, betweenness centrality, and eigenvector centrality, within the metro network structure attributes demonstrate significant positive effects on land use change, and these effects exhibit considerable spatiotemporal non-stationarity. Additionally, built environment factors surrounding metro stations, such as population density, plot ratio, street intersection density, and the quantity of bus stops, also exhibit notably spatiotemporal effects on land use change. These findings indicate that government agencies and urban planners should concentrate on optimizing the distribution of the urban metro network to improve its overall structural efficiency. When planning the construction of the metro network, careful attention should be paid to the built environment near the stations to effectively facilitate land use development in the vicinity. DE-206 Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International CC BY-NC-ND 4.0 cc https://creativecommons.org/licenses/by-nc-nd/4.0/ Complex network model (dpeaa)DE-206 Geographically and temporally weighted regression (dpeaa)DE-206 Land-use degree composite index (dpeaa)DE-206 Metro network structure (dpeaa)DE-206 Spatiotemporal analysis (dpeaa)DE-206 Liu, Yue verfasserin (DE-588)1327284197 (DE-627)1886828679 aut Sun, Hanwen verfasserin (DE-588)1342445163 (DE-627)1902990269 aut Li, Jinwen verfasserin (DE-588)1342445333 (DE-627)190299065X aut Yang, Hong verfasserin (DE-588)132728992X (DE-627)1886829462 aut Enthalten in Journal of urban management Amsterdam [u.a.] : Elsevier, 2012 13(2024), 2 vom: Juni, Seite 183-200 Online-Ressource (DE-627)837630150 (DE-600)2837330-3 (DE-576)446573256 2589-0360 nnns volume:13 year:2024 number:2 month:06 pages:183-200 https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf Verlag kostenfrei https://doi.org/10.1016/j.jum.2024.04.002 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 13 2024 2 6 183-200 26 01 0206 4552450735 x1z 17-07-24 2403 01 DE-LFER 4565457288 00 --%%-- --%%-- n --%%-- l01 12-08-24 2403 01 DE-LFER https://doi.org/10.1016/j.jum.2024.04.002 2403 01 DE-LFER https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf
language	English
source	Enthalten in Journal of urban management 13(2024), 2 vom: Juni, Seite 183-200 volume:13 year:2024 number:2 month:06 pages:183-200
sourceStr	Enthalten in Journal of urban management 13(2024), 2 vom: Juni, Seite 183-200 volume:13 year:2024 number:2 month:06 pages:183-200
format_phy_str_mv	Article
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institution	findex.gbv.de
selectbib_iln_str_mv	26@1z 2403@01
topic_facet	Complex network model Geographically and temporally weighted regression Land-use degree composite index Metro network structure Spatiotemporal analysis
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container_title	Journal of urban management
authorswithroles_txt_mv	Yan, Xuexin @@aut@@ Liu, Yue @@aut@@ Sun, Hanwen @@aut@@ Li, Jinwen @@aut@@ Yang, Hong @@aut@@
publishDateDaySort_date	2024-06-01T00:00:00Z
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author	Yan, Xuexin
spellingShingle	Yan, Xuexin misc Complex network model misc Geographically and temporally weighted regression misc Land-use degree composite index misc Metro network structure misc Spatiotemporal analysis Spatiotemporal impacts of metro network structure on land use change
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topic_title	Spatiotemporal impacts of metro network structure on land use change Xuexin Yan, Yue Liu, Hanwen Sun, Jinwen Li, Hong Yang Complex network model (dpeaa)DE-206 Geographically and temporally weighted regression (dpeaa)DE-206 Land-use degree composite index (dpeaa)DE-206 Metro network structure (dpeaa)DE-206 Spatiotemporal analysis (dpeaa)DE-206
topic	misc Complex network model misc Geographically and temporally weighted regression misc Land-use degree composite index misc Metro network structure misc Spatiotemporal analysis
topic_unstemmed	misc Complex network model misc Geographically and temporally weighted regression misc Land-use degree composite index misc Metro network structure misc Spatiotemporal analysis
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title	Spatiotemporal impacts of metro network structure on land use change
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title_full	Spatiotemporal impacts of metro network structure on land use change Xuexin Yan, Yue Liu, Hanwen Sun, Jinwen Li, Hong Yang
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title_sort	spatiotemporal impacts of metro network structure on land use change
title_auth	Spatiotemporal impacts of metro network structure on land use change
abstract	Numerous studies have presented compelling findings regarding the favorable influence exerted by the construction of metro systems on the development of land use along the routes. However, the effects of metro network structure on land use change, especially the long-term dynamic effects, remain uncertain. To address this gap, this research utilizes land use coverage data and metro network data from Wuhan, China, spanning the period from 2014 to 2019. A complex network model is employed to analyze changes in the metro network structure, and the GTWR model is employed to investigate the impact of the of metro network structure on land use change. The results indicate that metro construction effectively stimulates land use change along the routes, predominantly leading to the conversion of non-construction land into construction land. Global accessibility, degree centrality, betweenness centrality, and eigenvector centrality, within the metro network structure attributes demonstrate significant positive effects on land use change, and these effects exhibit considerable spatiotemporal non-stationarity. Additionally, built environment factors surrounding metro stations, such as population density, plot ratio, street intersection density, and the quantity of bus stops, also exhibit notably spatiotemporal effects on land use change. These findings indicate that government agencies and urban planners should concentrate on optimizing the distribution of the urban metro network to improve its overall structural efficiency. When planning the construction of the metro network, careful attention should be paid to the built environment near the stations to effectively facilitate land use development in the vicinity.
abstractGer	Numerous studies have presented compelling findings regarding the favorable influence exerted by the construction of metro systems on the development of land use along the routes. However, the effects of metro network structure on land use change, especially the long-term dynamic effects, remain uncertain. To address this gap, this research utilizes land use coverage data and metro network data from Wuhan, China, spanning the period from 2014 to 2019. A complex network model is employed to analyze changes in the metro network structure, and the GTWR model is employed to investigate the impact of the of metro network structure on land use change. The results indicate that metro construction effectively stimulates land use change along the routes, predominantly leading to the conversion of non-construction land into construction land. Global accessibility, degree centrality, betweenness centrality, and eigenvector centrality, within the metro network structure attributes demonstrate significant positive effects on land use change, and these effects exhibit considerable spatiotemporal non-stationarity. Additionally, built environment factors surrounding metro stations, such as population density, plot ratio, street intersection density, and the quantity of bus stops, also exhibit notably spatiotemporal effects on land use change. These findings indicate that government agencies and urban planners should concentrate on optimizing the distribution of the urban metro network to improve its overall structural efficiency. When planning the construction of the metro network, careful attention should be paid to the built environment near the stations to effectively facilitate land use development in the vicinity.
abstract_unstemmed	Numerous studies have presented compelling findings regarding the favorable influence exerted by the construction of metro systems on the development of land use along the routes. However, the effects of metro network structure on land use change, especially the long-term dynamic effects, remain uncertain. To address this gap, this research utilizes land use coverage data and metro network data from Wuhan, China, spanning the period from 2014 to 2019. A complex network model is employed to analyze changes in the metro network structure, and the GTWR model is employed to investigate the impact of the of metro network structure on land use change. The results indicate that metro construction effectively stimulates land use change along the routes, predominantly leading to the conversion of non-construction land into construction land. Global accessibility, degree centrality, betweenness centrality, and eigenvector centrality, within the metro network structure attributes demonstrate significant positive effects on land use change, and these effects exhibit considerable spatiotemporal non-stationarity. Additionally, built environment factors surrounding metro stations, such as population density, plot ratio, street intersection density, and the quantity of bus stops, also exhibit notably spatiotemporal effects on land use change. These findings indicate that government agencies and urban planners should concentrate on optimizing the distribution of the urban metro network to improve its overall structural efficiency. When planning the construction of the metro network, careful attention should be paid to the built environment near the stations to effectively facilitate land use development in the vicinity.
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title_short	Spatiotemporal impacts of metro network structure on land use change
url	https://www.sciencedirect.com/science/article/pii/S222658562400027X/pdfft?md5=027d1724be9e705491fce95d5b563f46&pid=1-s2.0-S222658562400027X-main.pdf https://doi.org/10.1016/j.jum.2024.04.002
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author2	Liu, Yue Sun, Hanwen Li, Jinwen Yang, Hong
author2Str	Liu, Yue Sun, Hanwen Li, Jinwen Yang, Hong
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doi_str	10.1016/j.jum.2024.04.002
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up_date	2024-09-20T05:37:28.006Z
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