Triple Collocation-Based Merging of Winter Snow Depth Retrievals on Arctic Sea Ice Derived From Three Different Algorithms Using AMSR2
Author:
Affiliation:
1. School of Geospatial Engineering and Science, Sun Yat-sen University and the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Funder
Guangdong Natural Science Foundation
Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10164238.pdf?arnumber=10164238
Reference74 articles.
1. Snow depth product over Antarctic sea ice from 2002 to 2020 using multisource passive microwave radiometers
2. Random forest in remote sensing: A review of applications and future directions
3. On the Synergy of SMAP and AMSR2 for Estimating Snow Depth on Arctic Sea Ice
4. Simultaneous estimation of wintertime sea ice thickness and snow depth from space-borne freeboard measurements
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1. The Varied Role of Atmospheric Rivers in Arctic Snow Depth Variations;Geophysical Research Letters;2024-07-24
2. Toward Daily Snow Depth Estimation on Arctic Sea Ice During the Whole Winter Season From Passive Microwave Radiometer Data;IEEE Transactions on Geoscience and Remote Sensing;2024
3. An Extended Triple Collocation Method With Maximized Correlation for Near Global‐Land Precipitation Fusion;Geophysical Research Letters;2023-12-19
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