Refinement of NOAA AMSR-2 Soil Moisture Data Product: 2. Development with the Optimal Machine Learning Model

Yin, Jifu; Zhan, Xiwu; Barlage, Michael; Liu, Jicheng; Meng, Huan; Ferraro, Ralph R.

doi:10.1109/tgrs.2023.3280176

i

Refinement of NOAA AMSR-2 Soil Moisture Data Product: 2. Development with the Optimal Machine Learning Model

2023
By Yin, Jifu ; Zhan, Xiwu ; Barlage, Michael ; ...

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Journal Title:

IEEE Transactions on Geoscience and Remote Sensing
Personal Author:

Yin, Jifu ; Zhan, Xiwu ; Barlage, Michael ; Liu, Jicheng ; Meng, Huan ; Ferraro, Ralph R.
NOAA Program & Office:

NESDIS (National Environmental Satellite, Data, and Information Service) ; NWS (National Weather Service) ; CICS (Cooperative Institute for Climate and Satellites) ; EMC (Environmental Modelling Center) ; NCEP (National Centers for Environmental Prediction) ; STAR (Center for Satellite Applications and Research)
Description:

— Advanced Microwave Scanning Radiometer-2 (AMSR2) is a successor of AMSR for Earth-Observation System (AMSR-E), while the third generation of AMSR (AMSR3) will be launched in the near future. The AMSR2 soil moisture (SM) product is also an important component of the SM operational products system (SMOPS) datasets that are operationally produced by National Oceanic and Atmospheric
Keywords:

Electrical And Electronic Engineering General Earth And Planetary Sciences Electrical And Electronic Engineering General Earth And Planetary Sciences Electrical And Electronic Engineering General Earth And Planetary Sciences
Source:

IEEE Transactions on Geoscience and Remote Sensing (2023)
DOI:

https://doi.org/10.1109/tgrs.2023.3280176
ISSN:

0196-2892 ; 1558-0644
Format:

PDF
Publisher:

Institute of Electrical and Electronics Engineers (IEEE)
Document Type:

Journal Article
Funding:

Grant no. NA19NES4320002
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Library
Main Document Checksum:

urn:sha256:76c89ab5db011bce056c296e5c5c3b407e3f71a3eee24092809abf9de060533f
Download URL:

https://repository.library.noaa.gov/view/noaa/55145/noaa_55145_DS1.pdf
File Type:

[PDF - 8.31 MB ]

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