School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
Collaborative Innovation Centre on Forecast and Evaluation of
Meteorological Disasters, School of Atmospheric Physics, Nanjing University
of Information Science & Technology, Nanjing 210044, China
Collaborative Innovation Centre on Forecast and Evaluation of
Meteorological Disasters, School of Atmospheric Physics, Nanjing University
of Information Science & Technology, Nanjing 210044, China
Fei Deng
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
Yanhao Zhang
Collaborative Innovation Centre on Forecast and Evaluation of
Meteorological Disasters, School of Atmospheric Physics, Nanjing University
of Information Science & Technology, Nanjing 210044, China
Duanyang Liu
Key Laboratory of Transportation Meteorology, China Meteorological
Administration, Nanjing 210008, China
China Meteorological Administration, Nanjing Joint Institute For Atmospheric Sciences, Nanjing 210008, China
Chao Liu
Collaborative Innovation Centre on Forecast and Evaluation of
Meteorological Disasters, School of Atmospheric Physics, Nanjing University
of Information Science & Technology, Nanjing 210044, China
Zhiqiu Gao
Collaborative Innovation Centre on Forecast and Evaluation of
Meteorological Disasters, School of Atmospheric Physics, Nanjing University
of Information Science & Technology, Nanjing 210044, China
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4,075
1,211
100
5,386
280
115
154
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PDF: 1,211
XML: 100
Total: 5,386
Supplement: 280
BibTeX: 115
EndNote: 154
Views and downloads (calculated since 27 Oct 2021)
Cumulative views and downloads
(calculated since 27 Oct 2021)
Total article views: 4,470 (including HTML, PDF, and XML)
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EndNote
3,489
896
85
4,470
151
108
141
HTML: 3,489
PDF: 896
XML: 85
Total: 4,470
Supplement: 151
BibTeX: 108
EndNote: 141
Views and downloads (calculated since 09 Feb 2022)
Cumulative views and downloads
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Total article views: 916 (including HTML, PDF, and XML)
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586
315
15
916
129
7
13
HTML: 586
PDF: 315
XML: 15
Total: 916
Supplement: 129
BibTeX: 7
EndNote: 13
Views and downloads (calculated since 27 Oct 2021)
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Viewed (geographical distribution)
Total article views: 5,386 (including HTML, PDF, and XML)
Thereof 5,299 with geography defined
and 87 with unknown origin.
Total article views: 4,470 (including HTML, PDF, and XML)
Thereof 4,419 with geography defined
and 51 with unknown origin.
Total article views: 916 (including HTML, PDF, and XML)
Thereof 880 with geography defined
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This paper proposes a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. The spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. The present RF model framework for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII.
This paper proposes a method for evaluating canopy UHI intensity (CUHII) at high resolution by...
