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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Total article views: 5,991 (including HTML, PDF, and XML)
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4,461
1,419
111
5,991
308
126
173
HTML: 4,461
PDF: 1,419
XML: 111
Total: 5,991
Supplement: 308
BibTeX: 126
EndNote: 173
Views and downloads (calculated since 27 Oct 2021)
Cumulative views and downloads
(calculated since 27 Oct 2021)
Total article views: 5,031 (including HTML, PDF, and XML)
HTML
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Total
Supplement
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EndNote
3,862
1,075
94
5,031
168
116
159
HTML: 3,862
PDF: 1,075
XML: 94
Total: 5,031
Supplement: 168
BibTeX: 116
EndNote: 159
Views and downloads (calculated since 09 Feb 2022)
Cumulative views and downloads
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Total article views: 960 (including HTML, PDF, and XML)
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Total
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599
344
17
960
140
10
14
HTML: 599
PDF: 344
XML: 17
Total: 960
Supplement: 140
BibTeX: 10
EndNote: 14
Views and downloads (calculated since 27 Oct 2021)
Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 5,991 (including HTML, PDF, and XML)
Thereof 5,896 with geography defined
and 95 with unknown origin.
Total article views: 5,031 (including HTML, PDF, and XML)
Thereof 4,969 with geography defined
and 62 with unknown origin.
Total article views: 960 (including HTML, PDF, and XML)
Thereof 927 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...
