Luojia nighttime light data with a 130m spatial resolution providing a better measurement of gridded anthropogenic heat flux than VIIRS
被引:9
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作者:
Liu, Xue
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East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R ChinaEast China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
Liu, Xue
[1
,2
]
Li, Xia
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East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R ChinaEast China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
Li, Xia
[1
,2
]
机构:
[1] East China Normal Univ, Sch Geog Sci, Shanghai 200241, Peoples R China
[2] East China Normal Univ, Key Lab Geog Informat Sci, Minist Educ, Shanghai 200241, Peoples R China
Anthropogenic heat flux (AHF) was generally estimated using the nighttime light (NTL) data with a 500 m (NPP-VIIRS) spatial resolution, creating significant uncertainties and distortions. A few studies have attempted to estimate AHF using a 130 m NTL data from the newly launched Luojia 1-01 satellite. However, there is a general lack of work aimed at comparing and validating the advantages of Luojia over its predecessor NTL data on AHF estimation. Therefore, we estimated AHF using Luojia and VIIRS and analyzed the consistency and accuracy of these results by using land cover/land use data. The analysis reveals that VIIRS overestimates the AHF for the natural lands and underestimates the AHF for the urban lands. Compared with VIIRS, Luojia can reduce 1.5-46.9% of AHF overestimations for the natural lands and 13.1-214.9% of AHF underestimations for the urban lands. The analysis also demonstrates that vegetation adjustment is unnecessary to AHF estimation using Luojia NTL data. Besides, the radiance value of Luojia NTL data is more suitable for AHF estimation than other forms (e. g., the digital number value, logarithmic transformation of the radiance value). These results can provide valuable information to improve the understanding of anthropogenic heat and urban thermal environments.
机构:
College of Architecture and Urban Planning, Fujian University of Technology, FuzhouCollege of Architecture and Urban Planning, Fujian University of Technology, Fuzhou
Lin Z.
Xu H.
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机构:
Ministry of Education Key Laboratory of Spatial Data Mining & Information Sharing, College of Environmental and Safety Engineering, Fuzhou University, Fuzhou
Fujian Provincial Key Laboratory of Remote Sensing Soil Erosion and Disaster Prevention, Institute of Remote Sensing Information Engineering, Fuzhou University, FuzhouCollege of Architecture and Urban Planning, Fujian University of Technology, Fuzhou
Xu H.
Lin C.
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机构:
College of Architecture and Urban Planning, Fujian University of Technology, FuzhouCollege of Architecture and Urban Planning, Fujian University of Technology, Fuzhou
机构:
Capital Normal Univ, Coll Resource Environm & Tourism, Beijing 100048, Peoples R China
Capital Normal Univ, Key Lab 3D Informat Acquisit & Applicat, Minist Educ, Beijing 100048, Peoples R ChinaCapital Normal Univ, Coll Resource Environm & Tourism, Beijing 100048, Peoples R China
Kuang, Huiwu
Hu, Deyong
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机构:
Capital Normal Univ, Coll Resource Environm & Tourism, Beijing 100048, Peoples R China
Capital Normal Univ, Key Lab 3D Informat Acquisit & Applicat, Minist Educ, Beijing 100048, Peoples R ChinaCapital Normal Univ, Coll Resource Environm & Tourism, Beijing 100048, Peoples R China
Hu, Deyong
Guo, Biyun
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机构:
Capital Normal Univ, Coll Resource Environm & Tourism, Beijing 100048, Peoples R China
Capital Normal Univ, Key Lab 3D Informat Acquisit & Applicat, Minist Educ, Beijing 100048, Peoples R ChinaCapital Normal Univ, Coll Resource Environm & Tourism, Beijing 100048, Peoples R China
Guo, Biyun
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,
2022,
60