The Fusion of Physical, Textural, and Morphological Information in SAR Imagery for Hurricane Wind Speed Retrieval Based on Deep Learning-Reference-Cited by-同舟云学术

The Fusion of Physical, Textural, and Morphological Information in SAR Imagery for Hurricane Wind Speed Retrieval Based on Deep Learning

Published:2022 Issue: Volume:60 Page:1-13
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Mu Shanshan¹^ORCID,Li Xiaofeng²^ORCID,Wang Haoyu¹

Affiliation:

1. Key Laboratory of Ocean Circulation and Waves, Institute of Oceanography, Chinese Academy of Sciences, Qingdao, China

2. Key Laboratory of Ocean Circulation and Waves, Institute of Oceanography, and the Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao, China

Funder

Strategic Priority Research Program of the Chinese Academy of Sciences

Key Research and Development Project of Shandong Province

Key Deployment Project of the Centre for Ocean Mega-Science

CAS Programs

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09774407.pdf?arnumber=9774407

Reference42 articles.

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4. Capability of the SMAP Mission to Measure Ocean Surface Winds in Storms

5. Hurricane Surface Wind Measurements from an Operational Stepped Frequency Microwave Radiometer

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