TU3.P4.2
Tropical cyclone intensity estimation based on multiple features of satellite remote sensing images using deep learning method
Xiaofeng Yang, Nanjing University, China
Session:
TU3.P4: High-Resolution Wind Vectors of Extreme Tropical Cyclones from Scatterometers and SAR: Methods and Applications I Oral
Track:
Community-Contributed Sessions
Location:
Plaza: Room P4
Presentation Time:
Tuesday, 5 August, 13:30 - 13:45
Session Co-Chairs:
Xingou Xu, National Space Science Center, Chinese Academy of Sciences and Xiaofeng Yang, Nanjing University and Shubham Awasthi, Virginia Polytechnic Institute and State University
Presentation
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Discussion
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Session TU3.P4
TU3.P4.1: SAR-LEARNED SCATTEROMETER RESOLUTION ENHANCEMENT FOR TROPICAL CYCLONES
Ad Stoffelen, Royal Netherlands Meteorological Institute (KNMI), Netherlands; Weicheng Ni, ZJU, China; Xingou Xu, Microwave Remote-Sensing Lab., China; Ke Zhao, CMA, China
TU3.P4.2: Tropical cyclone intensity estimation based on multiple features of satellite remote sensing images using deep learning method
Xiaofeng Yang, Nanjing University, China
TU3.P4.3: SIMULATION OF TROPICAL CYCLONE OBSERVATION WITH DIFFERENT SCATTEROMETER SYSTEMS
Ziming Dong, Xingou Xu, National Space Science Center, Chinese Academy of Sciences, China
TU3.P4.4: Deep Neural Network for High wind speed retrieval from Sentinel-1 SAR images
Letian Lv, Qing Xu, Ocean University of China, China
TU3.P4.5: THE APPLICATION PROCEDURES OF HIGH WIND FROM SCATTEROMETER PRODUCTS IN HAINAN ISLAND
Chang Xu, Xiaoqing Xiong, Hainan Geomatics Centre of Ministry of Natural Resources, China; Xingou Xu, National Space Science Center, Chinese Academy of Sciences, China
Resources
No resources available.