A machine learning approach to estimate surface ocean pCO2 from satellite measurements-Reference-Cited by-同舟云学术

A machine learning approach to estimate surface ocean pCO2 from satellite measurements

Published:2019-07 Issue: Volume:228 Page:203-226
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Chen Shuangling^ORCID,Hu Chuanmin^ORCID,Barnes Brian B.,Wanninkhof Rik,Cai Wei-Jun,Barbero Leticia,Pierrot Denis

Funder

University of South Florida

NASA

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference158 articles.

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3. Cross-sensor continuity of satellite-derived water clarity in the Gulf of Mexico: insights into temporal aliasing and implications for long-term water clarity assessment;Barnes;IEEE Trans. Geosci. Remote Sens.,2015

4. The influence of short-term wind variability on air-sea CO2 exchange;Bates;Geophys. Res. Lett.,2001

5. Contribution of hurricanes to local and global estimates of air–sea exchange of CO2;Bates;Nature,1998

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