31 citations as recorded by crossref.

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10. Testing the suitability of Marginal Distribution Sampling as a gap‐filling method using some meteorological data from seven sites in West Africa D. Koukoui et al. 10.1002/met.2152
11. Spatial and temporal variation of three Eddy-Covariance flux footprints in a Tropical Dry Forest M. Abdaki et al. 10.1016/j.agrformet.2023.109863
12. Air–sea interactions in stable atmospheric conditions: lessons from the desert semi-enclosed Gulf of Eilat (Aqaba) S. Abir et al. 10.5194/acp-24-6177-2024
13. A comparative analysis of machine learning approaches to gap filling meteorological datasets B. Lalic et al. 10.1007/s12665-024-11982-8
14. Gap-filling carbon dioxide, water, energy, and methane fluxes in challenging ecosystems: Comparing between methods, drivers, and gap-lengths S. Zhu et al. 10.1016/j.agrformet.2023.109365
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19. Spatiotemporal lagging of predictors improves machine learning estimates of atmosphere–forest CO2 exchange M. Kämäräinen et al. 10.5194/bg-20-897-2023
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23. Machine Learning-Based Prediction of Ecosystem-Scale CO2 Flux Measurements J. Uyekawa et al. 10.3390/land14010124
24. Multiple Gap-Filling for Eddy Covariance Datasets A. Lucas-Moffat et al. 10.2139/ssrn.4065277
25. Dynamic and high methane emission flux in pond and lake aquaculture J. Zhao et al. 10.1016/j.jhydrol.2025.132765
26. Trading a little water for substantial carbon gains during the first years of a Eucalyptus globulus plantation M. Silva et al. 10.1016/j.agrformet.2022.108910
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28. Temporally dynamic carbon dioxide and methane emission factors for rewetted peatlands A. Kalhori et al. 10.1038/s43247-024-01226-9
29. Commercial forest carbon protocol over-credit bias delimited by zero-threshold carbon accounting B. Marino & N. Bautista 10.1016/j.tfp.2021.100171
30. Drainage effects on carbon budgets of degraded peatlands in the north of the Netherlands T. Nijman et al. 10.1016/j.scitotenv.2024.172882
31. Technical note: Uncertainties in eddy covariance CO2 fluxes in a semiarid sagebrush ecosystem caused by gap-filling approaches J. Yao et al. 10.5194/acp-21-15589-2021