Analysis of spatiotemporal changes in cultural heritage protected cities and their influencing factors: Evidence from China
In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal cha...
Ausführliche Beschreibung
Autor*in: |
Cao, Jing [verfasserIn] Li, Tan [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2023 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: Ecological indicators - Amsterdam [u.a.] : Elsevier Science, 2001, 151 |
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Übergeordnetes Werk: |
volume:151 |
DOI / URN: |
10.1016/j.ecolind.2023.110327 |
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Katalog-ID: |
ELV009828885 |
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10.1016/j.ecolind.2023.110327 doi (DE-627)ELV009828885 (ELSEVIER)S1470-160X(23)00469-7 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid Cao, Jing verfasserin aut Analysis of spatiotemporal changes in cultural heritage protected cities and their influencing factors: Evidence from China 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities’ spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs. LUCC Urban expansion Ecological protection PLUS model CHPCs Li, Tan verfasserin aut Enthalten in Ecological indicators Amsterdam [u.a.] : Elsevier Science, 2001 151 Online-Ressource (DE-627)338074163 (DE-600)2063587-4 (DE-576)259272388 1872-7034 nnns volume:151 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 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_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 151 |
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10.1016/j.ecolind.2023.110327 doi (DE-627)ELV009828885 (ELSEVIER)S1470-160X(23)00469-7 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid Cao, Jing verfasserin aut Analysis of spatiotemporal changes in cultural heritage protected cities and their influencing factors: Evidence from China 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities’ spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs. LUCC Urban expansion Ecological protection PLUS model CHPCs Li, Tan verfasserin aut Enthalten in Ecological indicators Amsterdam [u.a.] : Elsevier Science, 2001 151 Online-Ressource (DE-627)338074163 (DE-600)2063587-4 (DE-576)259272388 1872-7034 nnns volume:151 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 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_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 151 |
allfields_unstemmed |
10.1016/j.ecolind.2023.110327 doi (DE-627)ELV009828885 (ELSEVIER)S1470-160X(23)00469-7 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid Cao, Jing verfasserin aut Analysis of spatiotemporal changes in cultural heritage protected cities and their influencing factors: Evidence from China 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities’ spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs. LUCC Urban expansion Ecological protection PLUS model CHPCs Li, Tan verfasserin aut Enthalten in Ecological indicators Amsterdam [u.a.] : Elsevier Science, 2001 151 Online-Ressource (DE-627)338074163 (DE-600)2063587-4 (DE-576)259272388 1872-7034 nnns volume:151 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 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_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 151 |
allfieldsGer |
10.1016/j.ecolind.2023.110327 doi (DE-627)ELV009828885 (ELSEVIER)S1470-160X(23)00469-7 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid Cao, Jing verfasserin aut Analysis of spatiotemporal changes in cultural heritage protected cities and their influencing factors: Evidence from China 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities’ spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs. LUCC Urban expansion Ecological protection PLUS model CHPCs Li, Tan verfasserin aut Enthalten in Ecological indicators Amsterdam [u.a.] : Elsevier Science, 2001 151 Online-Ressource (DE-627)338074163 (DE-600)2063587-4 (DE-576)259272388 1872-7034 nnns volume:151 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 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_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 151 |
allfieldsSound |
10.1016/j.ecolind.2023.110327 doi (DE-627)ELV009828885 (ELSEVIER)S1470-160X(23)00469-7 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid Cao, Jing verfasserin aut Analysis of spatiotemporal changes in cultural heritage protected cities and their influencing factors: Evidence from China 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities’ spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs. LUCC Urban expansion Ecological protection PLUS model CHPCs Li, Tan verfasserin aut Enthalten in Ecological indicators Amsterdam [u.a.] : Elsevier Science, 2001 151 Online-Ressource (DE-627)338074163 (DE-600)2063587-4 (DE-576)259272388 1872-7034 nnns volume:151 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 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_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 151 |
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Cao, Jing |
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analysis of spatiotemporal changes in cultural heritage protected cities and their influencing factors: evidence from china |
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Analysis of spatiotemporal changes in cultural heritage protected cities and their influencing factors: Evidence from China |
abstract |
In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities’ spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs. |
abstractGer |
In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities’ spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs. |
abstract_unstemmed |
In the Anthropocene, it is essential to analyze the spatiotemporal characteristics and causes of land use and landscape pattern changes in cultural heritage protected cities (CHPCs) to promote the sustainable development of CHPCs. Here we use PLUS model to explore and forecast the spatiotemporal changes from 2000 to 2060 in Pingyao, Gucheng, She and Langzhong, where the Four Ancient Cities of China are located. First, we found the spatiotemporal changes and the driving factors with land use transfer matrix, landscape metrics and a random forest analysis strategy. Furthermore, we simulated and predicted the spatiotemporal patterns in 2030 and 2060 by applying a CA model and landscape indexes, testing the carbon peak and carbon neutralization target achieved. The results demonstrate that urban expansion leads to an increase tendency in land use diversity and landscape heterogeneity, as well as adversely affecting the landscape pattern of ecological land. Altitude, socioeconomic conditions, and policies regarding the development and utilization of land resources all significantly impact the four cities’ spatiotemporal changes. Both the land use pattern and the landscape pattern will become more complex significantly in the future. This study offers a new insight to compare and analyze the spatiotemporal changes of different CHPCs. |
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score |
7.4006233 |