Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China

Urban 3D morphology significantly influences the outdoor thermal environment. Understanding the influence of urban expansion in both horizontal and vertical landscapes helps the canopy urban heat island (CUHI) effect mitigation. However, the microscale numerical CUHI models are difficult to be appli...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Li, Xiaorui [verfasserIn] Yang, Bisheng [verfasserIn] Liang, Fuxun [verfasserIn] Zhang, Hongsheng [verfasserIn] Xu, Yong [verfasserIn] Dong, Zhen [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Urban heat island Canopy air temperature Local climate zone ENVI-met Urban 3D morphology Random forest regression

Übergeordnetes Werk:	Enthalten in: Building and environment - New York, NY [u.a.] : Elsevier, 1976, 230
Übergeordnetes Werk:	volume:230

DOI / URN:	10.1016/j.buildenv.2023.110000

Katalog-ID:	ELV06232229X

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024	7		\|a 10.1016/j.buildenv.2023.110000 \|2 doi
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100	1		\|a Li, Xiaorui \|e verfasserin \|0 (orcid)0000-0001-6096-3878 \|4 aut
245	1	0	\|a Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China
264		1	\|c 2023
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520			\|a Urban 3D morphology significantly influences the outdoor thermal environment. Understanding the influence of urban expansion in both horizontal and vertical landscapes helps the canopy urban heat island (CUHI) effect mitigation. However, the microscale numerical CUHI models are difficult to be applied for large-area CUHI effect studies. On the other hand, the mesoscale CUHI models make a wider study area workable but lost some of the model accuracies. To perform a large-area study on the CUHI effect with relatively light computing costs and fine accuracy, this paper builds a canopy air temperature predicting model at city-block scale with urban 3D morphology parameters including building coverage ratio (BCR), grass coverage ratio (GCR) and the mean value of building height (BH) to obtain the citywide block-mean 2-m temperature (T2M). The model accuracy was validated through RMSEs and comparison with the mereological station data. The proposed model shows an RMSE of 0.286 straight °C and an R-square of 0.83. Using the validated model, Tianjin with an area of 647 km 2 was performed to investigate the effects of vertical landscape on the canopy air temperature under different scenarios between 2010 and 2016, including the changes in landcover and building heights. It finds that a 40% increase in BCR may lead to the highest canopy air temperature, and the increase of BH may lead to an increase in the canopy air temperature in low-rise and high-rise building areas, but there is an opposite trend in multi-story and mid-rise building areas.
650		4	\|a Urban heat island
650		4	\|a Canopy air temperature
650		4	\|a Local climate zone
650		4	\|a ENVI-met
650		4	\|a Urban 3D morphology
650		4	\|a Random forest regression
700	1		\|a Yang, Bisheng \|e verfasserin \|4 aut
700	1		\|a Liang, Fuxun \|e verfasserin \|0 (orcid)0000-0002-5947-4732 \|4 aut
700	1		\|a Zhang, Hongsheng \|e verfasserin \|4 aut
700	1		\|a Xu, Yong \|e verfasserin \|4 aut
700	1		\|a Dong, Zhen \|e verfasserin \|4 aut
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allfields	10.1016/j.buildenv.2023.110000 doi (DE-627)ELV06232229X (ELSEVIER)S0360-1323(23)00027-6 DE-627 ger DE-627 rda eng 690 VZ 56.00 bkl Li, Xiaorui verfasserin (orcid)0000-0001-6096-3878 aut Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Urban 3D morphology significantly influences the outdoor thermal environment. Understanding the influence of urban expansion in both horizontal and vertical landscapes helps the canopy urban heat island (CUHI) effect mitigation. However, the microscale numerical CUHI models are difficult to be applied for large-area CUHI effect studies. On the other hand, the mesoscale CUHI models make a wider study area workable but lost some of the model accuracies. To perform a large-area study on the CUHI effect with relatively light computing costs and fine accuracy, this paper builds a canopy air temperature predicting model at city-block scale with urban 3D morphology parameters including building coverage ratio (BCR), grass coverage ratio (GCR) and the mean value of building height (BH) to obtain the citywide block-mean 2-m temperature (T2M). The model accuracy was validated through RMSEs and comparison with the mereological station data. The proposed model shows an RMSE of 0.286 straight °C and an R-square of 0.83. Using the validated model, Tianjin with an area of 647 km 2 was performed to investigate the effects of vertical landscape on the canopy air temperature under different scenarios between 2010 and 2016, including the changes in landcover and building heights. It finds that a 40% increase in BCR may lead to the highest canopy air temperature, and the increase of BH may lead to an increase in the canopy air temperature in low-rise and high-rise building areas, but there is an opposite trend in multi-story and mid-rise building areas. Urban heat island Canopy air temperature Local climate zone ENVI-met Urban 3D morphology Random forest regression Yang, Bisheng verfasserin aut Liang, Fuxun verfasserin (orcid)0000-0002-5947-4732 aut Zhang, Hongsheng verfasserin aut Xu, Yong verfasserin aut Dong, Zhen verfasserin aut Enthalten in Building and environment New York, NY [u.a.] : Elsevier, 1976 230 Online-Ressource (DE-627)300188773 (DE-600)1481962-4 (DE-576)104402504 0360-1323 nnns volume:230 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_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_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 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_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.00 Bauwesen: Allgemeines VZ AR 230
spelling	10.1016/j.buildenv.2023.110000 doi (DE-627)ELV06232229X (ELSEVIER)S0360-1323(23)00027-6 DE-627 ger DE-627 rda eng 690 VZ 56.00 bkl Li, Xiaorui verfasserin (orcid)0000-0001-6096-3878 aut Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Urban 3D morphology significantly influences the outdoor thermal environment. Understanding the influence of urban expansion in both horizontal and vertical landscapes helps the canopy urban heat island (CUHI) effect mitigation. However, the microscale numerical CUHI models are difficult to be applied for large-area CUHI effect studies. On the other hand, the mesoscale CUHI models make a wider study area workable but lost some of the model accuracies. To perform a large-area study on the CUHI effect with relatively light computing costs and fine accuracy, this paper builds a canopy air temperature predicting model at city-block scale with urban 3D morphology parameters including building coverage ratio (BCR), grass coverage ratio (GCR) and the mean value of building height (BH) to obtain the citywide block-mean 2-m temperature (T2M). The model accuracy was validated through RMSEs and comparison with the mereological station data. The proposed model shows an RMSE of 0.286 straight °C and an R-square of 0.83. Using the validated model, Tianjin with an area of 647 km 2 was performed to investigate the effects of vertical landscape on the canopy air temperature under different scenarios between 2010 and 2016, including the changes in landcover and building heights. It finds that a 40% increase in BCR may lead to the highest canopy air temperature, and the increase of BH may lead to an increase in the canopy air temperature in low-rise and high-rise building areas, but there is an opposite trend in multi-story and mid-rise building areas. Urban heat island Canopy air temperature Local climate zone ENVI-met Urban 3D morphology Random forest regression Yang, Bisheng verfasserin aut Liang, Fuxun verfasserin (orcid)0000-0002-5947-4732 aut Zhang, Hongsheng verfasserin aut Xu, Yong verfasserin aut Dong, Zhen verfasserin aut Enthalten in Building and environment New York, NY [u.a.] : Elsevier, 1976 230 Online-Ressource (DE-627)300188773 (DE-600)1481962-4 (DE-576)104402504 0360-1323 nnns volume:230 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_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_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 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_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.00 Bauwesen: Allgemeines VZ AR 230
allfields_unstemmed	10.1016/j.buildenv.2023.110000 doi (DE-627)ELV06232229X (ELSEVIER)S0360-1323(23)00027-6 DE-627 ger DE-627 rda eng 690 VZ 56.00 bkl Li, Xiaorui verfasserin (orcid)0000-0001-6096-3878 aut Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Urban 3D morphology significantly influences the outdoor thermal environment. Understanding the influence of urban expansion in both horizontal and vertical landscapes helps the canopy urban heat island (CUHI) effect mitigation. However, the microscale numerical CUHI models are difficult to be applied for large-area CUHI effect studies. On the other hand, the mesoscale CUHI models make a wider study area workable but lost some of the model accuracies. To perform a large-area study on the CUHI effect with relatively light computing costs and fine accuracy, this paper builds a canopy air temperature predicting model at city-block scale with urban 3D morphology parameters including building coverage ratio (BCR), grass coverage ratio (GCR) and the mean value of building height (BH) to obtain the citywide block-mean 2-m temperature (T2M). The model accuracy was validated through RMSEs and comparison with the mereological station data. The proposed model shows an RMSE of 0.286 straight °C and an R-square of 0.83. Using the validated model, Tianjin with an area of 647 km 2 was performed to investigate the effects of vertical landscape on the canopy air temperature under different scenarios between 2010 and 2016, including the changes in landcover and building heights. It finds that a 40% increase in BCR may lead to the highest canopy air temperature, and the increase of BH may lead to an increase in the canopy air temperature in low-rise and high-rise building areas, but there is an opposite trend in multi-story and mid-rise building areas. Urban heat island Canopy air temperature Local climate zone ENVI-met Urban 3D morphology Random forest regression Yang, Bisheng verfasserin aut Liang, Fuxun verfasserin (orcid)0000-0002-5947-4732 aut Zhang, Hongsheng verfasserin aut Xu, Yong verfasserin aut Dong, Zhen verfasserin aut Enthalten in Building and environment New York, NY [u.a.] : Elsevier, 1976 230 Online-Ressource (DE-627)300188773 (DE-600)1481962-4 (DE-576)104402504 0360-1323 nnns volume:230 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_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_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 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_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.00 Bauwesen: Allgemeines VZ AR 230
allfieldsGer	10.1016/j.buildenv.2023.110000 doi (DE-627)ELV06232229X (ELSEVIER)S0360-1323(23)00027-6 DE-627 ger DE-627 rda eng 690 VZ 56.00 bkl Li, Xiaorui verfasserin (orcid)0000-0001-6096-3878 aut Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Urban 3D morphology significantly influences the outdoor thermal environment. Understanding the influence of urban expansion in both horizontal and vertical landscapes helps the canopy urban heat island (CUHI) effect mitigation. However, the microscale numerical CUHI models are difficult to be applied for large-area CUHI effect studies. On the other hand, the mesoscale CUHI models make a wider study area workable but lost some of the model accuracies. To perform a large-area study on the CUHI effect with relatively light computing costs and fine accuracy, this paper builds a canopy air temperature predicting model at city-block scale with urban 3D morphology parameters including building coverage ratio (BCR), grass coverage ratio (GCR) and the mean value of building height (BH) to obtain the citywide block-mean 2-m temperature (T2M). The model accuracy was validated through RMSEs and comparison with the mereological station data. The proposed model shows an RMSE of 0.286 straight °C and an R-square of 0.83. Using the validated model, Tianjin with an area of 647 km 2 was performed to investigate the effects of vertical landscape on the canopy air temperature under different scenarios between 2010 and 2016, including the changes in landcover and building heights. It finds that a 40% increase in BCR may lead to the highest canopy air temperature, and the increase of BH may lead to an increase in the canopy air temperature in low-rise and high-rise building areas, but there is an opposite trend in multi-story and mid-rise building areas. Urban heat island Canopy air temperature Local climate zone ENVI-met Urban 3D morphology Random forest regression Yang, Bisheng verfasserin aut Liang, Fuxun verfasserin (orcid)0000-0002-5947-4732 aut Zhang, Hongsheng verfasserin aut Xu, Yong verfasserin aut Dong, Zhen verfasserin aut Enthalten in Building and environment New York, NY [u.a.] : Elsevier, 1976 230 Online-Ressource (DE-627)300188773 (DE-600)1481962-4 (DE-576)104402504 0360-1323 nnns volume:230 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_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_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 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_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.00 Bauwesen: Allgemeines VZ AR 230
allfieldsSound	10.1016/j.buildenv.2023.110000 doi (DE-627)ELV06232229X (ELSEVIER)S0360-1323(23)00027-6 DE-627 ger DE-627 rda eng 690 VZ 56.00 bkl Li, Xiaorui verfasserin (orcid)0000-0001-6096-3878 aut Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Urban 3D morphology significantly influences the outdoor thermal environment. Understanding the influence of urban expansion in both horizontal and vertical landscapes helps the canopy urban heat island (CUHI) effect mitigation. However, the microscale numerical CUHI models are difficult to be applied for large-area CUHI effect studies. On the other hand, the mesoscale CUHI models make a wider study area workable but lost some of the model accuracies. To perform a large-area study on the CUHI effect with relatively light computing costs and fine accuracy, this paper builds a canopy air temperature predicting model at city-block scale with urban 3D morphology parameters including building coverage ratio (BCR), grass coverage ratio (GCR) and the mean value of building height (BH) to obtain the citywide block-mean 2-m temperature (T2M). The model accuracy was validated through RMSEs and comparison with the mereological station data. The proposed model shows an RMSE of 0.286 straight °C and an R-square of 0.83. Using the validated model, Tianjin with an area of 647 km 2 was performed to investigate the effects of vertical landscape on the canopy air temperature under different scenarios between 2010 and 2016, including the changes in landcover and building heights. It finds that a 40% increase in BCR may lead to the highest canopy air temperature, and the increase of BH may lead to an increase in the canopy air temperature in low-rise and high-rise building areas, but there is an opposite trend in multi-story and mid-rise building areas. Urban heat island Canopy air temperature Local climate zone ENVI-met Urban 3D morphology Random forest regression Yang, Bisheng verfasserin aut Liang, Fuxun verfasserin (orcid)0000-0002-5947-4732 aut Zhang, Hongsheng verfasserin aut Xu, Yong verfasserin aut Dong, Zhen verfasserin aut Enthalten in Building and environment New York, NY [u.a.] : Elsevier, 1976 230 Online-Ressource (DE-627)300188773 (DE-600)1481962-4 (DE-576)104402504 0360-1323 nnns volume:230 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 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_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_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 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_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 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_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 56.00 Bauwesen: Allgemeines VZ AR 230
language	English
source	Enthalten in Building and environment 230 volume:230
sourceStr	Enthalten in Building and environment 230 volume:230
format_phy_str_mv	Article
bklname	Bauwesen: Allgemeines
institution	findex.gbv.de
topic_facet	Urban heat island Canopy air temperature Local climate zone ENVI-met Urban 3D morphology Random forest regression
dewey-raw	690
isfreeaccess_bool	false
container_title	Building and environment
authorswithroles_txt_mv	Li, Xiaorui @@aut@@ Yang, Bisheng @@aut@@ Liang, Fuxun @@aut@@ Zhang, Hongsheng @@aut@@ Xu, Yong @@aut@@ Dong, Zhen @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	300188773
dewey-sort	3690
id	ELV06232229X
language_de	englisch
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author	Li, Xiaorui
spellingShingle	Li, Xiaorui ddc 690 bkl 56.00 misc Urban heat island misc Canopy air temperature misc Local climate zone misc ENVI-met misc Urban 3D morphology misc Random forest regression Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China
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topic_title	690 VZ 56.00 bkl Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China Urban heat island Canopy air temperature Local climate zone ENVI-met Urban 3D morphology Random forest regression
topic	ddc 690 bkl 56.00 misc Urban heat island misc Canopy air temperature misc Local climate zone misc ENVI-met misc Urban 3D morphology misc Random forest regression
topic_unstemmed	ddc 690 bkl 56.00 misc Urban heat island misc Canopy air temperature misc Local climate zone misc ENVI-met misc Urban 3D morphology misc Random forest regression
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title	Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China
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title_full	Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China
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title_sort	modeling urban canopy air temperature at city-block scale based on urban 3d morphology parameters– a study in tianjin, north china
title_auth	Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China
abstract	Urban 3D morphology significantly influences the outdoor thermal environment. Understanding the influence of urban expansion in both horizontal and vertical landscapes helps the canopy urban heat island (CUHI) effect mitigation. However, the microscale numerical CUHI models are difficult to be applied for large-area CUHI effect studies. On the other hand, the mesoscale CUHI models make a wider study area workable but lost some of the model accuracies. To perform a large-area study on the CUHI effect with relatively light computing costs and fine accuracy, this paper builds a canopy air temperature predicting model at city-block scale with urban 3D morphology parameters including building coverage ratio (BCR), grass coverage ratio (GCR) and the mean value of building height (BH) to obtain the citywide block-mean 2-m temperature (T2M). The model accuracy was validated through RMSEs and comparison with the mereological station data. The proposed model shows an RMSE of 0.286 straight °C and an R-square of 0.83. Using the validated model, Tianjin with an area of 647 km 2 was performed to investigate the effects of vertical landscape on the canopy air temperature under different scenarios between 2010 and 2016, including the changes in landcover and building heights. It finds that a 40% increase in BCR may lead to the highest canopy air temperature, and the increase of BH may lead to an increase in the canopy air temperature in low-rise and high-rise building areas, but there is an opposite trend in multi-story and mid-rise building areas.
abstractGer	Urban 3D morphology significantly influences the outdoor thermal environment. Understanding the influence of urban expansion in both horizontal and vertical landscapes helps the canopy urban heat island (CUHI) effect mitigation. However, the microscale numerical CUHI models are difficult to be applied for large-area CUHI effect studies. On the other hand, the mesoscale CUHI models make a wider study area workable but lost some of the model accuracies. To perform a large-area study on the CUHI effect with relatively light computing costs and fine accuracy, this paper builds a canopy air temperature predicting model at city-block scale with urban 3D morphology parameters including building coverage ratio (BCR), grass coverage ratio (GCR) and the mean value of building height (BH) to obtain the citywide block-mean 2-m temperature (T2M). The model accuracy was validated through RMSEs and comparison with the mereological station data. The proposed model shows an RMSE of 0.286 straight °C and an R-square of 0.83. Using the validated model, Tianjin with an area of 647 km 2 was performed to investigate the effects of vertical landscape on the canopy air temperature under different scenarios between 2010 and 2016, including the changes in landcover and building heights. It finds that a 40% increase in BCR may lead to the highest canopy air temperature, and the increase of BH may lead to an increase in the canopy air temperature in low-rise and high-rise building areas, but there is an opposite trend in multi-story and mid-rise building areas.
abstract_unstemmed	Urban 3D morphology significantly influences the outdoor thermal environment. Understanding the influence of urban expansion in both horizontal and vertical landscapes helps the canopy urban heat island (CUHI) effect mitigation. However, the microscale numerical CUHI models are difficult to be applied for large-area CUHI effect studies. On the other hand, the mesoscale CUHI models make a wider study area workable but lost some of the model accuracies. To perform a large-area study on the CUHI effect with relatively light computing costs and fine accuracy, this paper builds a canopy air temperature predicting model at city-block scale with urban 3D morphology parameters including building coverage ratio (BCR), grass coverage ratio (GCR) and the mean value of building height (BH) to obtain the citywide block-mean 2-m temperature (T2M). The model accuracy was validated through RMSEs and comparison with the mereological station data. The proposed model shows an RMSE of 0.286 straight °C and an R-square of 0.83. Using the validated model, Tianjin with an area of 647 km 2 was performed to investigate the effects of vertical landscape on the canopy air temperature under different scenarios between 2010 and 2016, including the changes in landcover and building heights. It finds that a 40% increase in BCR may lead to the highest canopy air temperature, and the increase of BH may lead to an increase in the canopy air temperature in low-rise and high-rise building areas, but there is an opposite trend in multi-story and mid-rise building areas.
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title_short	Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China
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author2	Yang, Bisheng Liang, Fuxun Zhang, Hongsheng Xu, Yong Dong, Zhen
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up_date	2024-07-06T18:39:18.110Z
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Modeling urban canopy air temperature at city-block scale based on urban 3D morphology parameters– A study in Tianjin, North China

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