Key Laboratory for Environment and Disaster Monitoring and Evaluation,
Hubei, Innovation Academy for Precision Measurement Science and Technology,
Chinese Academy of Sciences, Wuhan, 430077, China
University of Chinese Academy of Sciences, Beijing 100049, China
Anhui Province Key Laboratory of Wetland Ecosystem Protection and
Restoration, Anhui University, Hefei, 230601, China
Xiaodong Li
Key Laboratory for Environment and Disaster Monitoring and Evaluation,
Hubei, Innovation Academy for Precision Measurement Science and Technology,
Chinese Academy of Sciences, Wuhan, 430077, China
Yong Ge
State Key Laboratory of Resources and Environmental Information
System, Institute of Geographic Sciences and Natural Resources Research,
Chinese Academy of Sciences, Beijing 100101, China
Cheng Shang
Key Laboratory for Environment and Disaster Monitoring and Evaluation,
Hubei, Innovation Academy for Precision Measurement Science and Technology,
Chinese Academy of Sciences, Wuhan, 430077, China
University of Chinese Academy of Sciences, Beijing 100049, China
Xinyan Li
Key Laboratory for Environment and Disaster Monitoring and Evaluation,
Hubei, Innovation Academy for Precision Measurement Science and Technology,
Chinese Academy of Sciences, Wuhan, 430077, China
University of Chinese Academy of Sciences, Beijing 100049, China
Yun Du
Key Laboratory for Environment and Disaster Monitoring and Evaluation,
Hubei, Innovation Academy for Precision Measurement Science and Technology,
Chinese Academy of Sciences, Wuhan, 430077, China
Key Laboratory for Environment and Disaster Monitoring and Evaluation,
Hubei, Innovation Academy for Precision Measurement Science and Technology,
Chinese Academy of Sciences, Wuhan, 430077, China
Viewed
Total article views: 3,229 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
2,097
1,024
108
3,229
116
192
HTML: 2,097
PDF: 1,024
XML: 108
Total: 3,229
BibTeX: 116
EndNote: 192
Views and downloads (calculated since 11 Jan 2021)
Cumulative views and downloads
(calculated since 11 Jan 2021)
Total article views: 2,357 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,572
696
89
2,357
104
179
HTML: 1,572
PDF: 696
XML: 89
Total: 2,357
BibTeX: 104
EndNote: 179
Views and downloads (calculated since 24 Jun 2021)
Cumulative views and downloads
(calculated since 24 Jun 2021)
Total article views: 872 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
525
328
19
872
12
13
HTML: 525
PDF: 328
XML: 19
Total: 872
BibTeX: 12
EndNote: 13
Views and downloads (calculated since 11 Jan 2021)
Cumulative views and downloads
(calculated since 11 Jan 2021)
Viewed (geographical distribution)
Total article views: 3,229 (including HTML, PDF, and XML)
Thereof 3,165 with geography defined
and 64 with unknown origin.
Total article views: 2,357 (including HTML, PDF, and XML)
Thereof 2,335 with geography defined
and 22 with unknown origin.
Total article views: 872 (including HTML, PDF, and XML)
Thereof 830 with geography defined
and 42 with unknown origin.
MODIS thermal infrared (TIR) imagery provides promising data to study the rapid variations in the Arctic turbulent heat flux (THF). The accuracy of estimated THF, however, is low (especially for small leads) due to the coarse resolution of the MODIS TIR data. We train a deep neural network to enhance the spatial resolution of estimated THF over leads from MODIS TIR imagery. The method is found to be effective and can generate a result which is close to that derived from Landsat-8 TIR imagery.
MODIS thermal infrared (TIR) imagery provides promising data to study the rapid variations in...
