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
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Views and downloads (calculated since 11 Jan 2021)
Cumulative views and downloads
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Total article views: 2,246 (including HTML, PDF, and XML)
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Total article views: 3,076 (including HTML, PDF, and XML)
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Total article views: 2,246 (including HTML, PDF, and XML)
Thereof 2,227 with geography defined
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Total article views: 830 (including HTML, PDF, and XML)
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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...