Research graph
References from Simulating ecosystem water and carbon fluxes by integrating remote sensing indices with multiple machine learning models. Local targets link to admitted publications; unresolved targets remain external evidence.
Upscaled diurnal cycles of land–atmosphere fluxes: A new global half-hourly data product
10.5194/essd-10-1327-2018 · 2018 · External reference
Random forests
10.1023/a:1010933404324 · 2001 · External reference
XGBoost: A scalable tree boosting system
2016 · External reference
Moisture availability mediates the relationship between terrestrial gross primary production and solar-induced chlorophyll fluorescence: Insights from global-scale variations
10.1111/gcb.15373 · 2021 · External reference
Predicting carbon and water vapor fluxes using machine learning and novel feature ranking algorithms
10.1016/j.scitotenv.2021.145130 · 2021 · External reference
Canopy structure explains the relationship between photosynthesis and sun-induced chlorophyll fluorescence in crops
10.1016/j.rse.2020.111733 · 2020 · External reference
Unresolved reference
External reference
An interpretable machine learning approach based on DNN, SVR, extra tree, and XGBoost models for predicting daily pan evaporation
10.1016/j.jenvman.2022.116890 · 2023 · External reference
Explainable machine learning to quantify the value of proximal remote sensing in latent energy flux estimation
10.1016/j.agwat.2025.109643 · 2025 · External reference
The non-uniform time-lag and cumulative responses of terrestrial ecosystem water use efficiency to climate change in Lake Victoria Basin, East Africa
10.1016/j.jhydrol.2023.130081 · 2023 · External reference
Modeling the evapotranspiration and its long-term trend over Northwest China using different machine learning models
2023 · External reference
Water use efficiency and its drivers in four typical agroecosystems based on flux tower measurements
10.1016/j.agrformet.2020.108200 · 2020 · External reference
Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach
10.5194/bg-17-1343-2020 · 2020 · External reference
LightGBM: A highly efficient gradient boosting decision tree
2017 · External reference
A global, 0.05-degree product of solar-induced chlorophyll fluorescence derived from OCO-2, MODIS, and reanalysis data
10.3390/rs11050517 · 2019 · External reference
Explainable machine learning for joint estimation of evapotranspiration and gross primary productivity in a winter wheat cropland in Northwest China
10.1016/j.agwat.2026.110163 · 2026 · External reference
A unified approach to interpreting model predictions
2017 · External reference
From local explanations to global understanding with explainable AI for trees
10.1038/s42256-019-0138-9 · 2020 · External reference
Optimization of ecosystem model parameters through assimilating eddy covariance flux data with an ensemble kalman filter
10.1016/j.ecolmodel.2008.06.021 · 2008 · External reference
CatBoost: Unbiased boosting with categorical features
2018 · External reference
Temperature sensitivity of decomposition in relation to soil organic matter pools: critique and outlook
10.5194/bg-2-317-2005 · 2005 · External reference
Deep learning and process understanding for data-driven earth system science
10.1038/s41586-019-0912-1 · 2019 · External reference
Modeling of carbon and water fluxes of Qianyanzhou subtropical coniferous plantation using model-data fusion approach (in Chinese)
10.5846/stxb201203230397 · 2012 · External reference
Trends and methodological impacts in soil CO2 efflux partitioning: A metaanalytical review
10.1111/j.1365-2486.2006.01117.x · 2006 · External reference
Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms
10.5194/bg-13-4291-2016 · 2016 · External reference
Global synthesis of vegetation control on evapotranspiration partitioning
2014 · External reference
Revisiting the contribution of transpiration to global terrestrial evapotranspiration
10.1002/2016gl072235 · 2017 · External reference
Basic and extensible post-processing of eddy covariance flux data with REddyProc
10.5194/bg-15-5015-2018 · 2018 · External reference
Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years
10.1016/j.rse.2019.111383 · 2019 · External reference
Study on the coupling cycle of water-carbon and process management in terrestrial ecosystems
2004 · External reference
Global terrestrial carbon fluxes of 1999–2019 estimated by upscaling eddy covariance data with a random forest
10.1038/s41597-020-00653-5 · 2020 · External reference
Response of ecosystem gross primary productivity to drought in northern China based on multi-source remote sensing data
10.1016/j.jhydrol.2022.128808 · 2023 · External reference
Spatial and temporal variation analysis of ecosystem water use efficiency in Central Asia and Xinjiang in recent 15 years
2017 · External reference
