28 citations as recorded by crossref.

1. Applications of Machine Learning in Chemical and Biological Oceanography B. Sadaiappan et al.
2. Remote Sensing Estimations of the Seawater Partial Pressure of CO₂ Using Sea Surface Roughness Derived From Synthetic Aperture Radar Y. Wang et al.
3. Using satellite data to estimate partial pressure of CO2 in the Baltic Sea G. Parard et al.
4. Net Sea–Air CO$_{2}$ Fluxes and Modeled Partial Pressure of CO$_{2}$ in Open Ocean of Bay of Bengal A. Dixit et al.
5. Remote estimation of surface pCO2 on the West Florida Shelf S. Chen et al.
6. Variations in the summer oceanic pCO2 and carbon sink in Prydz Bay using the self-organizing map analysis approach S. Xu et al.
7. Estimating spatial and temporal variation in ocean surface pCO2 in the Gulf of Mexico using remote sensing and machine learning techniques Z. Fu et al.
8. Assessment of Air–Sea CO2 Flux in Global Surface Oceans Using Satellite Data I. Shaik et al.
9. Estimating temporal and spatial variation of ocean surface pCO2 in the North Pacific using a self-organizing map neural network technique S. Nakaoka et al.
10. A statistical gap‐filling method to interpolate global monthly surface ocean carbon dioxide data S. Jones et al.
11. At‐sea intercomparison of three underway pCO2 systems R. Arruda et al.
12. Estimation of sea surface pCO2 and air–sea CO2 flux in the East China Sea using in-situ and satellite data over the period 2000–2016 J. Liu et al.
13. A seamless ensemble-based reconstruction of surface ocean pCO2 and air–sea CO2 fluxes over the global coastal and open oceans T. Chau et al.
14. Investigating the complex relationship between in situ Southern Ocean $$pCO_{2}$$ p C O 2 and its ocean physics and biogeochemical drivers using a nonparametric regression approach W. Pretorius et al.
15. Space-Time Sea Surface pCO2 Estimation in the North Atlantic Based on CatBoost H. Sun et al.
16. A Review of Machine Learning Applications in Ocean Color Remote Sensing Z. Zhang et al.
17. A Global Surface Ocean fCO2 Climatology Based on a Feed-Forward Neural Network J. Zeng et al.
18. A novel sea surface pCO2-product for the global coastal ocean resolving trends over 1982–2020 A. Roobaert et al.
19. A Multiparametric Nonlinear Regression Approach for the Estimation of Global Surface Ocean pCO2 Using Satellite Oceanographic Data K. Krishna et al.
20. Satellite-derived CO2 flux in the surface seawater of the Austral Ocean south of Australia M. Benallal et al.
21. A machine learning approach to estimate surface ocean pCO2 from satellite measurements S. Chen et al.
22. Estimating mixed layer nitrate in the North Atlantic Ocean T. Steinhoff et al.
23. Estimating the monthly pCO2 distribution in the North Atlantic using a self-organizing neural network M. Telszewski et al.
24. Global ocean surface pCO2 retrieval and the influence of mesoscale eddies on its performance Y. Wang et al.
25. The Distribution of pCO2W and Air-Sea CO2 Fluxes Using FFNN at the Continental Shelf Areas of the Arctic Ocean I. Wrobel-Niedzwiecka et al.
26. Remote sensing the sea surface CO2 of the Baltic Sea using the SOMLO methodology G. Parard et al.
27. Technical note: Evaluation of three machine learning models for surface ocean CO2 mapping J. Zeng et al.
28. Satellite-derived CO2fugacity in surface seawater of the tropical Atlantic Ocean using a feedforward neural network H. Moussa et al.