23 citations as recorded by crossref.

1. The potential of using remote sensing data to estimate air–sea CO2 exchange in the Baltic Sea G. Parard et al. 10.5194/esd-8-1093-2017
2. Quantifying the Atmospheric CO2 Forcing Effect on Surface Ocean pCO2 in the North Pacific Subtropical Gyre in the Past Two Decades S. Chen et al. 10.3389/fmars.2021.636881
3. Development of subsurface chlorophyll maximum layer and its contribution to the primary productivity of water column in a large subtropical reservoir H. Miao et al. 10.1016/j.envres.2023.116118
4. Subsurface temperature estimation from remote sensing data using a clustering-neural network method W. Lu et al. 10.1016/j.rse.2019.04.009
5. From data to insights: Upscaling riverine GHG fluxes in Germany with machine learning R. Mwanake et al. 10.1016/j.scitotenv.2024.177984
6. Machine Learning Application in Water Quality Using Satellite Data N. Hassan & C. Woo 10.1088/1755-1315/842/1/012018
7. Remote Sensing of Sea Surface pCO2 in the Bering Sea in Summer Based on a Mechanistic Semi-Analytical Algorithm (MeSAA) X. Song et al. 10.3390/rs8070558
8. Net Sea–Air CO$_{2}$ Fluxes and Modeled Partial Pressure of CO$_{2}$ in Open Ocean of Bay of Bengal A. Dixit et al. 10.1109/JSTARS.2019.2902253
9. Estimating surface pCO2 in the northern Gulf of Mexico: Which remote sensing model to use? S. Chen et al. 10.1016/j.csr.2017.10.013
10. Data‐Driven Method With Numerical Model: A Combining Framework for Predicting Subtropical River Plumes W. Lu et al. 10.1029/2021JC017925
11. Remote Sensing Supported Sea Surface pCO2 Estimation and Variable Analysis in the Baltic Sea S. Zhang et al. 10.3390/rs13020259
12. Seasonal Variability in Chlorophyll and Air-Sea CO2 Flux in the Sri Lanka Dome: Hydrodynamic Implications W. Ma et al. 10.3390/rs14143239
13. pCO2 Algorithms for the Baltic Sea Based on Ship, Modelled, and Satellite Data S. Kuzmina & P. Lobanova 10.1134/S0001437024700917
14. An offshore subsurface thermal structure inversion method by coupling ensemble learning and tide model for the South Yellow Sea F. Yu et al. 10.3389/fmars.2022.1075938
15. Air–sea CO2exchange in the Baltic Sea—A sensitivity analysis of the gas transfer velocity L. Gutiérrez-Loza et al. 10.1016/j.jmarsys.2021.103603
16. Estimation of Fugacity of Carbon Dioxide in the East Sea Using In Situ Measurements and Geostationary Ocean Color Imager Satellite Data E. Jang et al. 10.3390/rs9080821
17. A Multiparametric Nonlinear Regression Approach for the Estimation of Global Surface Ocean pCO2 Using Satellite Oceanographic Data K. Krishna et al. 10.1109/JSTARS.2020.3026363
18. Estimating marine carbon uptake in the northeast Pacific using a neural network approach P. Duke et al. 10.5194/bg-20-3919-2023
19. Remote Sensing Estimations of the Seawater Partial Pressure of CO₂ Using Sea Surface Roughness Derived From Synthetic Aperture Radar Y. Wang et al. 10.1109/TGRS.2024.3379984
20. Using satellite data to estimate partial pressure of CO2 in the Baltic Sea G. Parard et al. 10.1002/2015JG003064
21. Remote sensing and machine learning method to support sea surface pCO2 estimation in the Yellow Sea W. Li et al. 10.3389/fmars.2023.1181095
22. The potential of using remote sensing data to estimate air–sea CO2 exchange in the Baltic Sea G. Parard et al. 10.5194/esd-8-1093-2017
23. Completion of a Sparse GLIDER Database Using Multi-iterative Self-Organizing Maps (ITCOMP SOM) A. Charantonis et al. 10.1016/j.procs.2015.05.496