Joint Inversion Algorithm of Sea Surface Temperature From Microwave and Infrared Brightness Temperature

The demand for high-precision sea surface temperature (SST) has been growing rapidly in recent years because SST is one of the key parameters to describe the thermal state of the sea surface. This article analyzes the differences between microwave remote sensing and infrared remote sensing for SST,...

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Vydané v:IEEE transactions on geoscience and remote sensing Ročník 60; s. 1 - 13
Hlavní autori: Chen, Zhiwei, Jin, Rong, Li, Qingxia, Zhao, Guanghui, Xiao, Chengwang, Lei, Zhenyu, Huang, Yuhang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Brightness
Brightness temperature
Electromagnetic heating
Infrared analysis
Infrared remote sensing
joint inversion algorithm
Microwave measurement
Microwave radiometry
microwave remote sensing
MODIS
Ocean temperature
Penetration depth
Remote sensing
Sea surface
Sea surface temperature
sea surface temperature (SST)
Spatial discrimination
Spatial resolution
Surface radiation temperature
Surface temperature
Temperature
Temperature measurement
Wind effects
Wind speed
ISSN:0196-2892, 1558-0644
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Popis
Shrnutí:The demand for high-precision sea surface temperature (SST) has been growing rapidly in recent years because SST is one of the key parameters to describe the thermal state of the sea surface. This article analyzes the differences between microwave remote sensing and infrared remote sensing for SST, including the spatial resolution difference and the penetration depth difference. In order to improve the accuracy of retrieved SST, this article proposes a joint inversion algorithm for SST from combining microwave brightness temperature (BT) and infrared BT, which has also taken the influence of wind speed and atmosphere into consideration. Experiments confirm that SST data obtained from the joint inversion algorithm are more accurate than those obtained from the existing inversion algorithms.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2022.3168984