Obtaining Cloud Base Height and Phase From Thermal Infrared Radiometry Using a Deep Learning Algorithm-Reference-Cited by-同舟云学术

Obtaining Cloud Base Height and Phase From Thermal Infrared Radiometry Using a Deep Learning Algorithm

Published:2023 Issue: Volume:61 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Wang Quan¹^ORCID,Zhou Chen¹,Letu Husi²^ORCID,Zhu Yannian¹,Zhuge Xiaoyong³^ORCID,Liu Chao⁴^ORCID,Weng Fuzhong⁵,Wang Minghuai¹

Affiliation:

1. School of Atmospheric Sciences and the Joint International Research Laboratory of Atmospheric and Earth System Sciences, Institute for Climate and Global Change Research, Nanjing University, Nanjing, China

2. State Key Laboratory of Remote Sensing Science, The Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

3. Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing, China

4. Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, China

5. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Research Funds for the Frontiers Science Center for Critical Earth Material Cycling, Nanjing University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10256250.pdf?arnumber=10256250

Reference78 articles.

1. Cloud base height retrieval from multi-angle satellite data