11 citations as recorded by crossref.

1. A physical full-factorial scheme for gap-filling of eddy covariance measurements of daytime evapotranspiration Y. Jiang et al. 10.1016/j.agrformet.2022.109087
2. Eddy Covariance CO2 Flux Gap Filling for Long Data Gaps: A Novel Framework Based on Machine Learning and Time Series Decomposition D. Gao et al. 10.3390/rs15102695
3. Quantifying the Spatial Representativeness of Carbon Flux Footprints of a Grassland Ecosystem in the Semi‐Arid Region H. Gong et al. 10.1029/2022JD038269
4. 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
5. Multiple-Win Effects and Beneficial Implications from Analyzing Long-Term Variations of Carbon Exchange in a Subtropical Coniferous Plantation in China J. Bai et al. 10.3390/atmos15101218
6. Impact of Shifts in Vegetation Phenology on the Carbon Balance of a Semiarid Sagebrush Ecosystem J. Yao et al. 10.3390/rs14235924
7. Upscaling net ecosystem CO2 exchanges in croplands: The application of integrating object-based image analysis and machine learning approaches D. Gao et al. 10.1016/j.scitotenv.2024.173887
8. The turning of ecological change in the Yellow River Basin T. Gu et al. 10.1002/hyp.15055
9. Artificial intelligence and Eddy covariance: A review A. Lucarini et al. 10.1016/j.scitotenv.2024.175406
10. A gap filling method for daily evapotranspiration of global flux data sets based on deep learning L. Qian et al. 10.1016/j.jhydrol.2024.131787
11. A ground-independent method for obtaining complete time series of in situ evapotranspiration observations W. Li et al. 10.1016/j.jhydrol.2024.130888