High-precision retrieval of offshore sea surface temperature: A machine learning framework based on MODIS and in-situ measurements-Reference-Cited by-同舟云学术

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High-precision retrieval of offshore sea surface temperature: A machine learning framework based on MODIS and in-situ measurements

Published:2024-03 Issue: Volume:137 Page:105129
ISSN:1350-4495
Container-title:Infrared Physics & Technology
language:en
Short-container-title:Infrared Physics & Technology

Author:

Hu Jiaochan,Tao Tingting,Jia Jia,Zhao Tong,Li Qingbo,Yu Haoyang

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

National Key Research and Development Program of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Reference37 articles.

1. A comprehensive review on water quality parameters estimation using remote sensing techniques;Gholizadeh;Sensors.,2016

2. Review and assessment of latent and sensible heat flux accuracy over the global oceans;Bentamy;Remote Sens. Environ.,2017

3. Estimation of sea surface temperatures from two infrared window measurements with different absorption;McMillin;J. Geophys. Res.,1975

4. Land Surface Temperature Measurements from the Split Window Channels of the NOAA 7 Advanced very High Resolution Radiometer;Price;J. Geophys. Res.,1984

5. Accurate land surface temperature retrieval from AVHRR data with use of an improved split window algorithm;Kerr;Remote Sens. Environ.,1992

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