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
Viewed
Total article views: 5,105 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
3,869
1,140
96
5,105
267
109
145
HTML: 3,869
PDF: 1,140
XML: 96
Total: 5,105
Supplement: 267
BibTeX: 109
EndNote: 145
Views and downloads (calculated since 27 Oct 2021)
Cumulative views and downloads
(calculated since 27 Oct 2021)
Total article views: 4,206 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
3,290
835
81
4,206
146
102
132
HTML: 3,290
PDF: 835
XML: 81
Total: 4,206
Supplement: 146
BibTeX: 102
EndNote: 132
Views and downloads (calculated since 09 Feb 2022)
Cumulative views and downloads
(calculated since 09 Feb 2022)
Total article views: 899 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
579
305
15
899
121
7
13
HTML: 579
PDF: 305
XML: 15
Total: 899
Supplement: 121
BibTeX: 7
EndNote: 13
Views and downloads (calculated since 27 Oct 2021)
Cumulative views and downloads
(calculated since 27 Oct 2021)
Viewed (geographical distribution)
Total article views: 5,105 (including HTML, PDF, and XML)
Thereof 5,035 with geography defined
and 70 with unknown origin.
Total article views: 4,206 (including HTML, PDF, and XML)
Thereof 4,170 with geography defined
and 36 with unknown origin.
Total article views: 899 (including HTML, PDF, and XML)
Thereof 865 with geography defined
and 34 with unknown origin.
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...
