Mingjuan Xie
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Machine learning-based investigation of forest evapotranspiration, net ecosystem productivity, water use efficiency and their climate controls at meteorological station level
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The increasing rate of net carbon uptake in Eurasia has been declining since the early 2000s
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Comparing the use of all data or specific subsets for training machine learning models in hydrology : a case study of evapotranspiration prediction
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- Journal Article
- A1
- open access
Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing
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- Journal Article
- A1
- open access
New data‐driven method for estimation of net ecosystem carbon exchange at meteorological stations effectively increases the global carbon flux data
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- Journal Article
- A1
- open access
Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning : a meta-analysis
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- Journal Article
- A1
- open access
Variability and uncertainty in flux-site-scale net ecosystem exchange simulations based on machine learning and remote sensing : a systematic evaluation