Identifying spatial agglomeration and driving forces of land use by green industries: a case study of Jiangsu Province, China
Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu P...
Ausführliche Beschreibung
Autor*in: |
Wang, Qi [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2023 |
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Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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Übergeordnetes Werk: |
Enthalten in: Environmental science and pollution research - Berlin : Springer, 1994, 30(2023), 19 vom: 06. März, Seite 54586-54599 |
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Übergeordnetes Werk: |
volume:30 ; year:2023 ; number:19 ; day:06 ; month:03 ; pages:54586-54599 |
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DOI / URN: |
10.1007/s11356-023-25740-z |
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Katalog-ID: |
SPR050134507 |
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520 | |a Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries. | ||
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650 | 4 | |a Industrial land use |7 (dpeaa)DE-He213 | |
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650 | 4 | |a Jiangsu Province |7 (dpeaa)DE-He213 | |
700 | 1 | |a Zhao, Xiao-feng |4 aut | |
700 | 1 | |a Lin, Sheng-Hau |0 (orcid)0000-0003-0828-6245 |4 aut | |
700 | 1 | |a Huang, Xian-jin |4 aut | |
700 | 1 | |a Lv, Jian-cheng |4 aut | |
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10.1007/s11356-023-25740-z doi (DE-627)SPR050134507 (SPR)s11356-023-25740-z-e DE-627 ger DE-627 rakwb eng Wang, Qi verfasserin aut Identifying spatial agglomeration and driving forces of land use by green industries: a case study of Jiangsu Province, China 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries. Energy saving and environmental protection industry (dpeaa)DE-He213 Industrial land use (dpeaa)DE-He213 Spatial pattern (dpeaa)DE-He213 Influencing factors (dpeaa)DE-He213 Jiangsu Province (dpeaa)DE-He213 Zhao, Xiao-feng aut Lin, Sheng-Hau (orcid)0000-0003-0828-6245 aut Huang, Xian-jin aut Lv, Jian-cheng aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 30(2023), 19 vom: 06. März, Seite 54586-54599 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:30 year:2023 number:19 day:06 month:03 pages:54586-54599 https://dx.doi.org/10.1007/s11356-023-25740-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 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_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 30 2023 19 06 03 54586-54599 |
spelling |
10.1007/s11356-023-25740-z doi (DE-627)SPR050134507 (SPR)s11356-023-25740-z-e DE-627 ger DE-627 rakwb eng Wang, Qi verfasserin aut Identifying spatial agglomeration and driving forces of land use by green industries: a case study of Jiangsu Province, China 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries. Energy saving and environmental protection industry (dpeaa)DE-He213 Industrial land use (dpeaa)DE-He213 Spatial pattern (dpeaa)DE-He213 Influencing factors (dpeaa)DE-He213 Jiangsu Province (dpeaa)DE-He213 Zhao, Xiao-feng aut Lin, Sheng-Hau (orcid)0000-0003-0828-6245 aut Huang, Xian-jin aut Lv, Jian-cheng aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 30(2023), 19 vom: 06. März, Seite 54586-54599 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:30 year:2023 number:19 day:06 month:03 pages:54586-54599 https://dx.doi.org/10.1007/s11356-023-25740-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 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_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 30 2023 19 06 03 54586-54599 |
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10.1007/s11356-023-25740-z doi (DE-627)SPR050134507 (SPR)s11356-023-25740-z-e DE-627 ger DE-627 rakwb eng Wang, Qi verfasserin aut Identifying spatial agglomeration and driving forces of land use by green industries: a case study of Jiangsu Province, China 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries. Energy saving and environmental protection industry (dpeaa)DE-He213 Industrial land use (dpeaa)DE-He213 Spatial pattern (dpeaa)DE-He213 Influencing factors (dpeaa)DE-He213 Jiangsu Province (dpeaa)DE-He213 Zhao, Xiao-feng aut Lin, Sheng-Hau (orcid)0000-0003-0828-6245 aut Huang, Xian-jin aut Lv, Jian-cheng aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 30(2023), 19 vom: 06. März, Seite 54586-54599 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:30 year:2023 number:19 day:06 month:03 pages:54586-54599 https://dx.doi.org/10.1007/s11356-023-25740-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 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_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 30 2023 19 06 03 54586-54599 |
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10.1007/s11356-023-25740-z doi (DE-627)SPR050134507 (SPR)s11356-023-25740-z-e DE-627 ger DE-627 rakwb eng Wang, Qi verfasserin aut Identifying spatial agglomeration and driving forces of land use by green industries: a case study of Jiangsu Province, China 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries. Energy saving and environmental protection industry (dpeaa)DE-He213 Industrial land use (dpeaa)DE-He213 Spatial pattern (dpeaa)DE-He213 Influencing factors (dpeaa)DE-He213 Jiangsu Province (dpeaa)DE-He213 Zhao, Xiao-feng aut Lin, Sheng-Hau (orcid)0000-0003-0828-6245 aut Huang, Xian-jin aut Lv, Jian-cheng aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 30(2023), 19 vom: 06. März, Seite 54586-54599 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:30 year:2023 number:19 day:06 month:03 pages:54586-54599 https://dx.doi.org/10.1007/s11356-023-25740-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 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_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 30 2023 19 06 03 54586-54599 |
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10.1007/s11356-023-25740-z doi (DE-627)SPR050134507 (SPR)s11356-023-25740-z-e DE-627 ger DE-627 rakwb eng Wang, Qi verfasserin aut Identifying spatial agglomeration and driving forces of land use by green industries: a case study of Jiangsu Province, China 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries. Energy saving and environmental protection industry (dpeaa)DE-He213 Industrial land use (dpeaa)DE-He213 Spatial pattern (dpeaa)DE-He213 Influencing factors (dpeaa)DE-He213 Jiangsu Province (dpeaa)DE-He213 Zhao, Xiao-feng aut Lin, Sheng-Hau (orcid)0000-0003-0828-6245 aut Huang, Xian-jin aut Lv, Jian-cheng aut Enthalten in Environmental science and pollution research Berlin : Springer, 1994 30(2023), 19 vom: 06. März, Seite 54586-54599 (DE-627)320517926 (DE-600)2014192-0 1614-7499 nnns volume:30 year:2023 number:19 day:06 month:03 pages:54586-54599 https://dx.doi.org/10.1007/s11356-023-25740-z lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 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_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 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_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 30 2023 19 06 03 54586-54599 |
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Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Energy saving and environmental protection industry</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Industrial land use</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Spatial pattern</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Influencing factors</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Jiangsu Province</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhao, Xiao-feng</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lin, Sheng-Hau</subfield><subfield code="0">(orcid)0000-0003-0828-6245</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Huang, Xian-jin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lv, Jian-cheng</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Environmental science and pollution research</subfield><subfield code="d">Berlin : Springer, 1994</subfield><subfield code="g">30(2023), 19 vom: 06. 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Wang, Qi |
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Wang, Qi misc Energy saving and environmental protection industry misc Industrial land use misc Spatial pattern misc Influencing factors misc Jiangsu Province Identifying spatial agglomeration and driving forces of land use by green industries: a case study of Jiangsu Province, China |
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Identifying spatial agglomeration and driving forces of land use by green industries: a case study of Jiangsu Province, China Energy saving and environmental protection industry (dpeaa)DE-He213 Industrial land use (dpeaa)DE-He213 Spatial pattern (dpeaa)DE-He213 Influencing factors (dpeaa)DE-He213 Jiangsu Province (dpeaa)DE-He213 |
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identifying spatial agglomeration and driving forces of land use by green industries: a case study of jiangsu province, china |
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Identifying spatial agglomeration and driving forces of land use by green industries: a case study of Jiangsu Province, China |
abstract |
Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
abstractGer |
Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
abstract_unstemmed |
Abstract In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
collection_details |
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container_issue |
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title_short |
Identifying spatial agglomeration and driving forces of land use by green industries: a case study of Jiangsu Province, China |
url |
https://dx.doi.org/10.1007/s11356-023-25740-z |
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Zhao, Xiao-feng Lin, Sheng-Hau Huang, Xian-jin Lv, Jian-cheng |
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Zhao, Xiao-feng Lin, Sheng-Hau Huang, Xian-jin Lv, Jian-cheng |
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doi_str |
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up_date |
2024-07-03T13:36:17.393Z |
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score |
7.4013834 |