Articles | Volume 13, issue 14
https://doi.org/10.5194/bg-13-4291-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/bg-13-4291-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms
Gianluca Tramontana
CORRESPONDING AUTHOR
Department for Innovation in Biological, Agro-food and Forest
systems (DIBAF), University of Tuscia, Viterbo, 01100, Italy
Martin Jung
Max
Planck Institute for Biogeochemistry, Jena, 07745, Germany
Christopher R. Schwalm
Woods
Hole Research Center, Falmouth, MA 02540, USA
Kazuhito Ichii
Department of
Environmental Geochemical Cycle Research, Japan Agency for Marine-Earth
Science and Technology, Yokohama, 236-0001, Japan
Center for
Global Environmental Research, National Institute for Environmental Studies,
Tsukuba, 305-8506, Japan
Gustau Camps-Valls
Image Processing Laboratory (IPL),
Universitat de València, Paterna (València), 46980, Spain
Botond Ráduly
Department for Innovation in Biological, Agro-food and Forest
systems (DIBAF), University of Tuscia, Viterbo, 01100, Italy
Department of Bioengineering, Sapientia Hungarian University of
Transylvania, Miercurea Ciuc, 530104, Romania
Markus Reichstein
Max
Planck Institute for Biogeochemistry, Jena, 07745, Germany
M. Altaf Arain
School of Geography
and Earth Sciences, McMaster University, Hamilton (Ontario), L8S4L8, Canada
Alessandro Cescatti
European Commission, Joint Research Centre, Directorate for
Sustainable Resources, Ispra, Italy
Gerard Kiely
Civil & Environmental
Engineering and Environmental Research Institute, University College, Cork,
T12 YN60, Ireland
Lutz Merbold
Department of Environmental Systems Science,
Institute of Agricultural Sciences, ETH Zurich, Zurich, 8092, Switzerland
Mazingira Centre, Livestock Systems and Environment, International
Livestock Research Institute (ILRI), 00100, Nairobi, Kenya
Penelope Serrano-Ortiz
Department of Ecology, University of Granada, Granada, 18071,
Spain
Sven Sickert
Computer Vision Group, Friedrich Schiller University Jena,
07743 Jena, Germany
Sebastian Wolf
Department of Environmental Systems Science,
Institute of Agricultural Sciences, ETH Zurich, Zurich, 8092, Switzerland
Dario Papale
Department for Innovation in Biological, Agro-food and Forest
systems (DIBAF), University of Tuscia, Viterbo, 01100, Italy
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- Spatial pattern and attribution of ecosystem drought recovery in China T. Wu et al. 10.1016/j.jhydrol.2024.131578
- Analysis of variations and controls of evapotranspiration over major Indian River Basins (1982–2014) A. Soni & T. Syed 10.1016/j.scitotenv.2020.141892
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- Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink? C. Seiler et al. 10.1029/2021MS002946
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- Machine learning in photosynthesis: Prospects on sustainable crop development R. Varghese et al. 10.1016/j.plantsci.2023.111795
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- Technical note: Flagging inconsistencies in flux tower data M. Jung et al. 10.5194/bg-21-1827-2024
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- Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network J. Beringer et al. 10.1111/gcb.16141
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- Application of machine-learning methods in forest ecology: recent progress and future challenges Z. Liu et al. 10.1139/er-2018-0034
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- Understanding the Land Carbon Cycle with Space Data: Current Status and Prospects J. Exbrayat et al. 10.1007/s10712-019-09506-2
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- Effects of Anthropogenic Activity on Global Terrestrial Gross Primary Production I. Melnikova & T. Sasai 10.1029/2019JG005403
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- Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties A. Virkkala et al. 10.1111/gcb.15659
- Soil carbon response to land-use change: evaluation of a global vegetation model using observational meta-analyses S. Nyawira et al. 10.5194/bg-13-5661-2016
- Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques M. Flach et al. 10.5194/esd-8-677-2017
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- Extreme anomaly event detection in biosphere using linear regression and a spatiotemporal MRF model Y. Guanche García et al. 10.1007/s11069-018-3415-8
- Implications of the steady-state assumption for the global vegetation carbon turnover N. Fan et al. 10.1088/1748-9326/acfb22
- Assessment of Carbon Productivity Trends and Their Resilience to Drought Disturbances in the Middle East Based on Multi-Decadal Space-Based Datasets K. Alsafadi et al. 10.3390/rs14246237
- Hybrid modeling of evapotranspiration: inferring stomatal and aerodynamic resistances using combined physics-based and machine learning R. ElGhawi et al. 10.1088/1748-9326/acbbe0
- Estimating Global Gross Primary Production Using an Improved MODIS Leaf Area Index Dataset S. Wang et al. 10.3390/rs16193731
- Emergent relationships with respect to burned area in global satellite observations and fire-enabled vegetation models M. Forkel et al. 10.5194/bg-16-57-2019
- Uncertainty analysis of intra-module environmental stress parameter design in light use efficiency-based gross primary productivity estimation models C. Zhao & W. Zhu 10.1177/2754124X241235545
- Retrieval of solar-induced chlorophyll fluorescence (SIF) from satellite measurements: comparison of SIF between TanSat and OCO-2 L. Yao et al. 10.5194/amt-15-2125-2022
- CARDAMOM-FluxVal version 1.0: a FLUXNET-based validation system for CARDAMOM carbon and water flux estimates Y. Yang et al. 10.5194/gmd-15-1789-2022
- Divergent seasonal responses of carbon fluxes to extreme droughts over China Y. Deng et al. 10.1016/j.agrformet.2022.109253
- Triple collocation-based merging of multi-source gridded evapotranspiration data in the Nordic Region X. Li et al. 10.1016/j.agrformet.2023.109451
- Technical note: A view from space on global flux towers by MODIS and Landsat: the FluxnetEO data set S. Walther et al. 10.5194/bg-19-2805-2022
- Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations O. Peltola et al. 10.5194/essd-11-1263-2019
- A hybrid deep learning framework with physical process description for simulation of evapotranspiration H. Chen et al. 10.1016/j.jhydrol.2021.127422
- A framework for constructing machine learning models with feature set optimisation for evapotranspiration partitioning A. Stapleton et al. 10.1016/j.acags.2022.100105
- Combining flux variance similarity partitioning with artificial neural networks to gap-fill measurements of net ecosystem production of a Pacific Northwest Douglas-fir stand S. Lee et al. 10.1016/j.agrformet.2021.108382
- Data assimilation for continuous global assessment of severe conditions over terrestrial surfaces C. Albergel et al. 10.5194/hess-24-4291-2020
- The Global Distribution of Biological Nitrogen Fixation in Terrestrial Natural Ecosystems T. Davies‐Barnard & P. Friedlingstein 10.1029/2019GB006387
- Monitoring tropical forests under a functional perspective with satellite‐based vegetation optical depth G. Vaglio Laurin et al. 10.1111/gcb.15072
- Compensatory water effects link yearly global land CO2 sink changes to temperature M. Jung et al. 10.1038/nature20780
- Reduction of structural impacts and distinction of photosynthetic pathways in a global estimation of GPP from space-borne solar-induced chlorophyll fluorescence Z. Zhang et al. 10.1016/j.rse.2020.111722
- Multisatellite Analyses of Spatiotemporal Variability in Photosynthetic Activity Over the Tibetan Plateau X. Wang et al. 10.1029/2019JG005249
- Interannual variability in the Australian carbon cycle over 2015–2019, based on assimilation of Orbiting Carbon Observatory-2 (OCO-2) satellite data Y. Villalobos et al. 10.5194/acp-22-8897-2022
- An Online Deep Convolutional Model of Gross Primary Productivity and Net Ecosystem Exchange Estimation for Global Forests W. Wu et al. 10.1109/JSTARS.2019.2954556
- Evaluation of forest carbon uptake in South Korea using the national flux tower network, remote sensing, and data-driven technology S. Cho et al. 10.1016/j.agrformet.2021.108653
- Estimation of Net Ecosystem Productivity on the Tibetan Plateau Grassland from 1982 to 2018 Based on Random Forest Model J. Zheng et al. 10.3390/rs15092375
- Modeling the effects of litter stoichiometry and soil mineral N availability on soil organic matter formation using CENTURY-CUE (v1.0) H. Zhang et al. 10.5194/gmd-11-4779-2018
- Disequilibrium of terrestrial ecosystem CO<sub>2</sub> budget caused by disturbance-induced emissions and non-CO<sub>2</sub> carbon export flows: a global model assessment A. Ito 10.5194/esd-10-685-2019
- Uniform upscaling techniques for eddy covariance FLUXes (UFLUX) S. Zhu et al. 10.1080/01431161.2024.2312266
- Reply to: Large influence of atmospheric vapor pressure deficit on ecosystem production efficiency L. Liu et al. 10.1038/s41467-022-29010-3
- Improved Global Maps of the Optimum Growth Temperature, Maximum Light Use Efficiency, and Gross Primary Production for Vegetation Y. Chen et al. 10.1029/2020JG005651
- Four years of global carbon cycle observed from the Orbiting Carbon Observatory 2 (OCO-2) version 9 and in situ data and comparison to OCO-2 version 7 H. Peiro et al. 10.5194/acp-22-1097-2022
- Monitoring 2019 Drought and Assessing Its Effects on Vegetation Using Solar-Induced Chlorophyll Fluorescence and Vegetation Indexes in the Middle and Lower Reaches of Yangtze River, China M. Li et al. 10.3390/rs14112569
- Comprehensive accuracy assessment of long-term geostationary SEVIRI-MSG evapotranspiration estimates across Europe B. Bayat et al. 10.1016/j.rse.2023.113875
- Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land Y. Wang et al. 10.1029/2021MS002964
- Long-term gridded land evapotranspiration reconstruction using Deep Forest with high generalizability Q. Feng et al. 10.1038/s41597-023-02822-8
- Global modeling diurnal gross primary production from OCO-3 solar-induced chlorophyll fluorescence Z. Zhang et al. 10.1016/j.rse.2022.113383
- Interannual variation of terrestrial carbon cycle: Issues and perspectives S. Piao et al. 10.1111/gcb.14884
- Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model A. Norton et al. 10.5194/bg-16-3069-2019
- Changes in Water Use Efficiency Caused by Climate Change, CO2 Fertilization, and Land Use Changes on the Tibetan Plateau B. Jia et al. 10.1007/s00376-022-2172-5
- LDAS-Monde Sequential Assimilation of Satellite Derived Observations Applied to the Contiguous US: An ERA-5 Driven Reanalysis of the Land Surface Variables C. Albergel et al. 10.3390/rs10101627
- Ideas and perspectives: enhancing the impact of the FLUXNET network of eddy covariance sites D. Papale 10.5194/bg-17-5587-2020
- Synergy between TROPOMI sun-induced chlorophyll fluorescence and MODIS spectral reflectance for understanding the dynamics of gross primary productivity at Integrated Carbon Observatory System (ICOS) ecosystem flux sites H. Balde et al. 10.5194/bg-20-1473-2023
- Contrasting Drought Propagation Into the Terrestrial Water Cycle Between Dry and Wet Regions W. Li et al. 10.1029/2022EF003441
- Evaluating Cumulative Drought Effect on Global Vegetation Photosynthesis Using Numerous GPP Products C. Wu & T. Wang 10.3389/fenvs.2022.908875
- Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations C. Abadie et al. 10.1029/2023JG007407
- Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence S. Alemohammad et al. 10.5194/bg-14-4101-2017
- Machine Learning Research Trends in Africa: A 30 Years Overview with Bibliometric Analysis Review A. Ezugwu et al. 10.1007/s11831-023-09930-z
- Gross primary productivity of terrestrial ecosystems: a review of observations, remote sensing, and modelling studies over South Asia V. Pandey et al. 10.1007/s00704-024-05158-4
- An ensemble square root filter for the joint assimilation of surface soil moisture and leaf area index within the Land Data Assimilation System LDAS-Monde: application over the Euro-Mediterranean region B. Bonan et al. 10.5194/hess-24-325-2020
- Methane emissions reduce the radiative cooling effect of a subtropical estuarine mangrove wetland by half J. Liu et al. 10.1111/gcb.15247
- Nonlinear PCA for Spatio-Temporal Analysis of Earth Observation Data D. Bueso et al. 10.1109/TGRS.2020.2969813
- Increasing drought sensitivity of plant photosynthetic phenology and physiology Y. Wang et al. 10.1016/j.ecolind.2024.112469
- Large‐Scale Droughts Responsible for Dramatic Reductions of Terrestrial Net Carbon Uptake Over North America in 2011 and 2012 W. He et al. 10.1029/2018JG004520
- Towards a universal evapotranspiration model based on optimality principles S. Tan et al. 10.1016/j.agrformet.2023.109478
- Decreasing Cropping Intensity Dominated the Negative Trend of Cropland Productivity in Southern China in 2000–2015 Z. Niu et al. 10.3390/su122310070
- Comparing the use of all data or specific subsets for training machine learning models in hydrology: A case study of evapotranspiration prediction H. Shi et al. 10.1016/j.jhydrol.2023.130399
- Exploring the spatial relationship between airborne-derived red and far-red sun-induced fluorescence and process-based GPP estimates in a forest ecosystem G. Tagliabue et al. 10.1016/j.rse.2019.111272
- Global Carbon Fluxes Using Multioutput Gaussian Processes Regression and MODIS Products M. Campos-Taberner et al. 10.1109/JSTARS.2024.3413184
- Warming inhibits increases in vegetation net primary productivity despite greening in India R. Das et al. 10.1038/s41598-023-48614-3
- Empirical upscaling of OzFlux eddy covariance for high-resolution monitoring of terrestrial carbon uptake in Australia C. Burton et al. 10.5194/bg-20-4109-2023
- Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers J. De Pue et al. 10.5194/bg-20-4795-2023
- Accelerated dryland expansion regulates future variability in dryland gross primary production J. Yao et al. 10.1038/s41467-020-15515-2
- Apparent ecosystem carbon turnover time: uncertainties and robust features N. Fan et al. 10.5194/essd-12-2517-2020
- Land use change and El Niño-Southern Oscillation drive decadal carbon balance shifts in Southeast Asia M. Kondo et al. 10.1038/s41467-018-03374-x
- TAVIs: Topographically Adjusted Vegetation Index for a Reliable Proxy of Gross Primary Productivity in Mountain Ecosystems X. Xie et al. 10.1109/TGRS.2023.3336727
- Estimating Ecosystem Respiration in the Grasslands of Northern China Using Machine Learning: Model Evaluation and Comparison X. Zhu et al. 10.3390/su12052099
- Causal hybrid modeling with double machine learning—applications in carbon flux modeling K. Cohrs et al. 10.1088/2632-2153/ad5a60
- Predicting multi-annual green roof net ecosystem exchange using machine learning T. Husting et al. 10.1016/j.buildenv.2024.111878
- Recent trends in gross primary production and their drivers: analysis and modelling at flux-site and global scales W. Cai & I. Prentice 10.1088/1748-9326/abc64e
- Addressing biases in Arctic–boreal carbon cycling in the Community Land Model Version 5 L. Birch et al. 10.5194/gmd-14-3361-2021
- More severe drought detected by the assimilation of brightness temperature and terrestrial water storage anomalies in Texas during 2010–2013 W. Chen et al. 10.1016/j.jhydrol.2021.126802
- Remote sensing of terrestrial gross primary productivity: a review of advances in theoretical foundation, key parameters and methods W. Zhu et al. 10.1080/15481603.2024.2318846
- The potential of remote sensing-based models on global water-use efficiency estimation: An evaluation and intercomparison of an ecosystem model (BESS) and algorithm (MODIS) using site level and upscaled eddy covariance data S. Yang et al. 10.1016/j.agrformet.2020.107959
- Earth system data cubes unravel global multivariate dynamics M. Mahecha et al. 10.5194/esd-11-201-2020
- A model for urban biogenic CO<sub>2</sub> fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1) D. Wu et al. 10.5194/gmd-14-3633-2021
- Non-linear correlations exist between solar-induced chlorophyll fluorescence and canopy photosynthesis in a subtropical evergreen forest in Southwest China Y. Wang et al. 10.1016/j.ecolind.2023.111311
- Monitoring soil carbon flux with in-situ measurements and satellite observations in a forested region C. Xu et al. 10.1016/j.geoderma.2020.114617
- Recent global decline in rainfall interception loss due to altered rainfall regimes X. Lian et al. 10.1038/s41467-022-35414-y
- High-resolution spatial patterns and drivers of terrestrial ecosystem carbon dioxide, methane, and nitrous oxide fluxes in the tundra A. Virkkala et al. 10.5194/bg-21-335-2024
- Causal inference reveals the dominant role of interannual variability of carbon sinks in complicated environmental-terrestrial ecosystems C. Dang et al. 10.1016/j.rse.2024.114300
- Global terrestrial carbon fluxes of 1999–2019 estimated by upscaling eddy covariance data with a random forest J. Zeng et al. 10.1038/s41597-020-00653-5
- A Novel Approach for Predicting Anthropogenic CO2 Emissions Using Machine Learning Based on Clustering of the CO2 Concentration Z. Ji et al. 10.3390/atmos15030323
- A carbon sink-driven approach to estimate gross primary production from microwave satellite observations I. Teubner et al. 10.1016/j.rse.2019.04.022
- A pigment ratio index based on remotely sensed reflectance provides the potential for universal gross primary production estimation W. Wu et al. 10.1088/1748-9326/abf3dc
- Effect of tree demography and flexible root water uptake for modeling the carbon and water cycles of Amazonia E. Joetzjer et al. 10.1016/j.ecolmodel.2022.109969
- MEBA: AI-powered precise building monthly energy benchmarking approach T. Li et al. 10.1016/j.apenergy.2024.122716
- A Practical Algorithm for Correcting Topographical Effects on Global GPP Products X. Xie et al. 10.1029/2023JG007553
- Identifying thresholds of time-lag and accumulative effects of extreme precipitation on major vegetation types at global scale M. Liu et al. 10.1016/j.agrformet.2024.110239
- Rapid recovery of net ecosystem production in a semi-arid woodland after a wildfire Q. Sun et al. 10.1016/j.agrformet.2020.108099
- Coupling a light use efficiency model with a machine learning-based water constraint for predicting grassland gross primary production R. Yu et al. 10.1016/j.agrformet.2023.109634
- The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model A. Rahman et al. 10.3390/rs14030437
- A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks Y. Zhang et al. 10.5194/bg-15-5779-2018
- Estimation of Global Grassland Net Ecosystem Carbon Exchange Using a Model Tree Ensemble Approach W. Liang et al. 10.1029/2019JG005034
- The Relationship of Gross Primary Productivity with NDVI Rather than Solar-Induced Chlorophyll Fluorescence Is Weakened under the Stress of Drought W. Zhao et al. 10.3390/rs16030555
- Globally Scalable Approach to Estimate Net Ecosystem Exchange Based on Remote Sensing, Meteorological Data, and Direct Measurements of Eddy Covariance Sites R. Zhuravlev et al. 10.3390/rs14215529
- Carbon fluxes and environmental controls across different alpine grassland types on the Tibetan Plateau Y. Wang et al. 10.1016/j.agrformet.2021.108694
- Soil respiration–driven CO 2 pulses dominate Australia’s flux variability E. Metz et al. 10.1126/science.add7833
- Deep learning and process understanding for data-driven Earth system science M. Reichstein et al. 10.1038/s41586-019-0912-1
- Global Estimates of Marine Gross Primary Production Based on Machine Learning Upscaling of Field Observations Y. Huang et al. 10.1029/2020GB006718
- Estimation of vegetation traits with kernel NDVI Q. Wang et al. 10.1016/j.isprsjprs.2022.12.019
- Five years of variability in the global carbon cycle: comparing an estimate from the Orbiting Carbon Observatory-2 and process-based models Z. Chen et al. 10.1088/1748-9326/abfac1
- Machine learning methods for assessing photosynthetic activity: environmental monitoring applications S. Khruschev et al. 10.1007/s12551-022-00982-2
- Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years J. Xiao et al. 10.1016/j.rse.2019.111383
- Biological factors dominate the interannual variability of evapotranspiration in an irrigated cropland in the North China Plain H. Lei et al. 10.1016/j.agrformet.2018.01.007
- Towards effective drought monitoring in the Middle East and North Africa (MENA) region: implications from assimilating leaf area index and soil moisture into the Noah-MP land surface model for Morocco W. Nie et al. 10.5194/hess-26-2365-2022
- Remote-Sensing Inversion Method for Evapotranspiration by Fusing Knowledge and Multisource Data J. Wang et al. 10.1155/2022/2076633
- Warmer spring alleviated the impacts of 2018 European summer heatwave and drought on vegetation photosynthesis S. Wang et al. 10.1016/j.agrformet.2020.108195
- Improved water use efficiency of vegetation due to carbon fertilization not translating to increased soil moisture in India A. Verma & S. Ghosh 10.1016/j.jhydrol.2024.131890
- A review of machine learning models and influential factors for estimating evapotranspiration using remote sensing and ground-based data S. Amani & H. Shafizadeh-Moghadam 10.1016/j.agwat.2023.108324
- Gap‐Filled Multivariate Observations of Global Land–Climate Interactions V. Bessenbacher et al. 10.1029/2023JD039099
- A framework for estimating actual evapotranspiration at weather stations without flux observations by combining data from MODIS and flux towers through a machine learning approach C. Zhang et al. 10.1016/j.jhydrol.2021.127047
- Resolve the Clear‐Sky Continuous Diurnal Cycle of High‐Resolution ECOSTRESS Evapotranspiration and Land Surface Temperature J. Wen et al. 10.1029/2022WR032227
- Evaluating GPP and Respiration Estimates Over Northern Midlatitude Ecosystems Using Solar‐Induced Fluorescence and Atmospheric CO2 Measurements B. Byrne et al. 10.1029/2018JG004472
- Use of Sun-Induced Chlorophyll Fluorescence Obtained by OCO-2 and GOME-2 for GPP Estimates of the Heihe River Basin, China X. Wei et al. 10.3390/rs10122039
- Increased photosynthesis during spring drought in energy-limited ecosystems D. Miller et al. 10.1038/s41467-023-43430-9
- Estimating Global GPP From the Plant Functional Type Perspective Using a Machine Learning Approach R. Guo et al. 10.1029/2022JG007100
- Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability K. Wang et al. 10.1038/s41467-022-31175-w
- Schätzung der Verdunstung mithilfe von Machine- und Deep Learning-Methoden C. Brenner et al. 10.1007/s00506-021-00768-y
- Predicting carbon and water vapor fluxes using machine learning and novel feature ranking algorithms X. Cui et al. 10.1016/j.scitotenv.2021.145130
- Estimating Gross Primary Productivity (GPP) over Rice–Wheat-Rotation Croplands by Using the Random Forest Model and Eddy Covariance Measurements: Upscaling and Comparison with the MODIS Product Z. Duan et al. 10.3390/rs13214229
- The impact of indicator selection on assessment of global greening B. Qiu et al. 10.1080/15481603.2021.1879494
- A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1) M. Forkel et al. 10.5194/gmd-10-4443-2017
- Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products B. Martínez et al. 10.1016/j.jag.2017.10.011
- CO2 exchange and evapotranspiration across dryland ecosystems of southwestern North America J. Biederman et al. 10.1111/gcb.13686
- A multi-perspective input selection strategy for daily net ecosystem exchange predictions based on machine learning methods Ö. Ekmekcioğlu et al. 10.1007/s00704-022-04265-4
- Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis S. Walther et al. 10.5194/bg-15-6221-2018
- Impacts of extreme summers on European ecosystems: a comparative analysis of 2003, 2010 and 2018 A. Bastos et al. 10.1098/rstb.2019.0507
- Validation of drought indices using environmental indicators: streamflow and carbon flux data U. Bhuyan-Erhardt et al. 10.1016/j.agrformet.2018.11.016
- Moisture availability mediates the relationship between terrestrial gross primary production and solar‐induced chlorophyll fluorescence: Insights from global‐scale variations A. Chen et al. 10.1111/gcb.15373
- Artificial intelligence and Eddy covariance: A review A. Lucarini et al. 10.1016/j.scitotenv.2024.175406
- Vegetation clumping modulates global photosynthesis through adjusting canopy light environment F. Li et al. 10.1111/gcb.16503
- Actual Evapotranspiration Estimates in Arid Cold Regions Using Machine Learning Algorithms with In Situ and Remote Sensing Data J. Mosre & F. Suárez 10.3390/w13060870
- Increased productivity of temperate vegetation in the preceding year drives early spring phenology in the subsequent year in northern China Q. Zhang et al. 10.1016/j.scitotenv.2023.166676
- Global increase in the optimal temperature for the productivity of terrestrial ecosystems Z. Fang et al. 10.1038/s43247-024-01636-9
- Global dryland aridity changes indicated by atmospheric, hydrological, and vegetation observations at meteorological stations H. Shi et al. 10.5194/hess-27-4551-2023
- Kernel methods and their derivatives: Concept and perspectives for the earth system sciences J. Johnson et al. 10.1371/journal.pone.0235885
- Benchmarking large-scale evapotranspiration estimates: A perspective from a calibration-free complementary relationship approach and FLUXCOM N. Ma et al. 10.1016/j.jhydrol.2020.125221
- Exploring the Best-Matching Plant Traits and Environmental Factors for Vegetation Indices in Estimates of Global Gross Primary Productivity W. Zhao & Z. Zhu 10.3390/rs14246316
- Gaussianizing the Earth: Multidimensional information measures for Earth data analysis J. Johnson et al. 10.1109/MGRS.2021.3066260
- Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks B. He et al. 10.1093/nsr/nwab150
- Large loss of CO2 in winter observed across the northern permafrost region S. Natali et al. 10.1038/s41558-019-0592-8
- Non-growing season carbon emissions in a northern peatland are projected to increase under global warming A. Rafat et al. 10.1038/s43247-021-00184-w
- Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations J. Zscheischler et al. 10.5194/bg-14-3685-2017
- The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data G. Pastorello et al. 10.1038/s41597-020-0534-3
- A Promising Tool to Determine Daily Et by Monitoring Soil Water Changes Caused by Evapotranspiration in the Hilly and Gully Regions of the Loess Plateau W. Sun et al. 10.2139/ssrn.4156073
- Spatial-temporal patterns of land surface evapotranspiration from global products R. Tang et al. 10.1016/j.rse.2024.114066
- Coupling the Canadian Terrestrial Ecosystem Model (CTEM v. 2.0) to Environment and Climate Change Canada's greenhouse gas forecast model (v.107-glb) B. Badawy et al. 10.5194/gmd-11-631-2018
- Detecting drought-induced GPP spatiotemporal variabilities with sun-induced chlorophyll fluorescence during the 2009/2010 droughts in China S. Chen et al. 10.1016/j.ecolind.2020.107092
- Contrasting and interacting changes in simulated spring and summer carbon cycle extremes in European ecosystems S. Sippel et al. 10.1088/1748-9326/aa7398
- Carbon Flux Variability From a Relatively Simple Ecosystem Model With Assimilated Data Is Consistent With Terrestrial Biosphere Model Estimates G. Quetin et al. 10.1029/2019MS001889
- Comparison between deep learning architectures for the 1 km, 10/15-min estimation of downward shortwave radiation from AHI and ABI R. Li et al. 10.1016/j.rse.2023.113697
- Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions T. Lippmann et al. 10.5194/gmd-16-6773-2023
- Primary productivity estimation of forest based on in-situ biophysical parameters and sentinel satellite data using vegetation photosynthesis model in an eastern Indian tropical dry deciduous forest S. Ahmad et al. 10.1007/s42965-022-00220-6
- Upscaling Net Ecosystem Exchange Over Heterogeneous Landscapes With Machine Learning O. Reitz et al. 10.1029/2020JG005814
- Using automated machine learning for the upscaling of gross primary productivity M. Gaber et al. 10.5194/bg-21-2447-2024
- Inferring causal relations from observational long-term carbon and water fluxes records E. Díaz et al. 10.1038/s41598-022-05377-7
- Physics‐Constrained Machine Learning of Evapotranspiration W. Zhao et al. 10.1029/2019GL085291
- Ground‐Based Multiangle Solar‐Induced Chlorophyll Fluorescence Observation and Angular Normalization for Assessing Crop Productivity Q. Zhang et al. 10.1029/2020JG006082
- Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison G. McNicol et al. 10.1029/2023AV000956
- Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project S. Hantson et al. 10.5194/gmd-13-3299-2020
- 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
- Spatio-temporal patterns of evapotranspiration based on upscaling eddy covariance measurements in the dryland of the North China Plain B. Fang et al. 10.1016/j.agrformet.2019.107844
- Defining model complexity: An ecological perspective C. Malmborg et al. 10.1002/met.2202
- A Review of Machine Learning Applications in Land Surface Modeling S. Pal & P. Sharma 10.3390/earth2010011
- A Data‐Driven Global Soil Heterotrophic Respiration Dataset and the Drivers of Its Inter‐Annual Variability Y. Yao et al. 10.1029/2020GB006918
- Contributions of climate change, land use change and CO2 to changes in the gross primary productivity of the Tibetan Plateau X. LUO et al. 10.1080/16742834.2020.1695515
- Fluxes all of the time? A primer on the temporal representativeness of FLUXNET H. Chu et al. 10.1002/2016JG003576
- Selected breakpoints of net forest carbon uptake at four eddy-covariance sites T. Foken et al. 10.1080/16000889.2021.1915648
- Carbon cycle: ESP and UAV data processing approaches for forest ecosystem monitoring examples M. Platonova et al. 10.18303/2619-1563-2023-4-45
- Reverse engineering model structures for soil and ecosystem respiration: the potential of gene expression programming I. Ilie et al. 10.5194/gmd-10-3519-2017
- Atmospheric dryness reduces photosynthesis along a large range of soil water deficits Z. Fu et al. 10.1038/s41467-022-28652-7
- A 1 km Global Carbon Flux Dataset Using In Situ Measurements and Deep Learning W. Shangguan et al. 10.3390/f14050913
- Estimating Global Anthropogenic CO2 Gridded Emissions Using a Data-Driven Stacked Random Forest Regression Model Y. Zhang et al. 10.3390/rs14163899
- Technical note: Uncertainties in eddy covariance CO<sub>2</sub> fluxes in a semiarid sagebrush ecosystem caused by gap-filling approaches J. Yao et al. 10.5194/acp-21-15589-2021
- Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation R. Oliver et al. 10.5194/gmd-15-5567-2022
- Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data J. Joiner et al. 10.3390/rs10091346
- Optimizing variables selection of random forest to predict radial growth of Larix gmelinii var. principis-rupprechtii in temperate regions Y. Zhang et al. 10.1016/j.foreco.2024.122159
- Increasing impact of warm droughts on northern ecosystem productivity over recent decades D. Gampe et al. 10.1038/s41558-021-01112-8
- Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model A. Rahman et al. 10.3389/frwa.2021.789352
- A novel approach for retrieving GPP of evergreen forest regions of India using random forest regression D. Sarkar et al. 10.1016/j.rsase.2023.101116
- Climate‐Driven Variability and Trends in Plant Productivity Over Recent Decades Based on Three Global Products M. O'Sullivan et al. 10.1029/2020GB006613
- Advanced time-lagged effects of drought on global vegetation growth and its social risk in the 21st century T. Chen et al. 10.1016/j.jenvman.2023.119253
- Summarizing the state of the terrestrial biosphere in few dimensions G. Kraemer et al. 10.5194/bg-17-2397-2020
- Evaluation of remotely sensed global evapotranspiration data from inland river basins Z. Liu 10.1002/hyp.14774
- Spatiotemporal Modeling of Carbon Fluxes over Complex Underlying Surfaces along the North Shore of Hangzhou Bay K. Zhang et al. 10.3390/atmos15060727
- Increasing terrestrial ecosystem carbon release in response to autumn cooling and warming R. Tang et al. 10.1038/s41558-022-01304-w
- Prediction of global water use efficiency and its response to vapor pressure deficit and soil moisture coupling in the 21st century T. Chen et al. 10.1016/j.jhydrol.2024.131203
- Contrasting drought legacy effects on gross primary productivity in a mixed versus pure beech forest X. Yu et al. 10.5194/bg-19-4315-2022
- Investigating the ability of deep learning on actual evapotranspiration estimation in the scarcely observed region X. Wang et al. 10.1016/j.jhydrol.2022.127506
- Assimilation of Remotely Sensed Leaf Area Index into the Noah-MP Land Surface Model: Impacts on Water and Carbon Fluxes and States over the Continental United States S. Kumar et al. 10.1175/JHM-D-18-0237.1
- Using an object-based machine learning ensemble approach to upscale evapotranspiration measured from eddy covariance towers in a subtropical wetland C. Zhang et al. 10.1016/j.scitotenv.2022.154969
- The Spatio-Temporal Variations of GPP and Its Climatic Driving Factors in the Yangtze River Basin during 2000–2018 C. Nie et al. 10.3390/f14091898
- Long term variation of evapotranspiration and water balance based on upscaling eddy covariance observations over the temperate semi-arid grassland of China X. Pang et al. 10.1016/j.agrformet.2021.108566
- Early forecasting of corn yield and price variations using satellite vegetation products F. Teste et al. 10.1016/j.compag.2024.108962
- Evaluating global ecosystem water use efficiency response to drought based on multi-model analysis S. Yang et al. 10.1016/j.scitotenv.2021.146356
- Investigation of Carbon-Dioxide-Emissions from Underutilized Grassland between 2019 and 2020 K. Varga et al. 10.3390/agronomy12040931
- Concurrent and lagged effects of spring greening on seasonal carbon gain and water loss across the Northern Hemisphere J. Jin et al. 10.1007/s00484-020-01913-0
- A decreasing carbon allocation to belowground autotrophic respiration in global forest ecosystems X. Tang et al. 10.1016/j.scitotenv.2021.149273
- A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research D. Montero et al. 10.1038/s41597-023-02096-0
- Vegetation modulates the impact of climate extremes on gross primary production M. Flach et al. 10.5194/bg-18-39-2021
- Responses of vegetation greenness and carbon cycle to extreme droughts in China Y. Deng et al. 10.1016/j.agrformet.2020.108307
- Partitioning Net Ecosystem Exchange (NEE) of CO2 Using Solar‐Induced Chlorophyll Fluorescence (SIF) O. Kira et al. 10.1029/2020GL091247
- Constraining biospheric carbon dioxide fluxes by combined top-down and bottom-up approaches S. Upton et al. 10.5194/acp-24-2555-2024
- Characterizing satellite-derived freeze/thaw regimes through spatial and temporal clustering for the identification of growing season constraints on vegetation productivity R. Melser et al. 10.1016/j.rse.2024.114210
- Recent Changes in Global Photosynthesis and Terrestrial Ecosystem Respiration Constrained From Multiple Observations W. Li et al. 10.1002/2017GL076622
- Improving estimations of ecosystem respiration with asymmetric daytime and nighttime temperature sensitivity and relative humidity N. Li et al. 10.1016/j.agrformet.2021.108709
- Global estimates of L-band vegetation optical depth and soil permittivity of snow-covered boreal forests and permafrost landscape using SMAP satellite data D. Kumawat et al. 10.1016/j.rse.2024.114145
- P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production B. Stocker et al. 10.5194/gmd-13-1545-2020
- An Ecosystem-Scale Flux Measurement Strategy to Assess Natural Climate Solutions K. Hemes et al. 10.1021/acs.est.0c06421
- Forecasting CO2 emissions of fuel vehicles for an ecological world using ensemble learning, machine learning, and deep learning models F. Gurcan 10.7717/peerj-cs.2234
- Assessing the relationship between microwave vegetation optical depth and gross primary production I. Teubner et al. 10.1016/j.jag.2017.10.006
- Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask? S. Gallup et al. 10.1029/2021MS002555
- Cropland Carbon Uptake Delayed and Reduced by 2019 Midwest Floods Y. Yin et al. 10.1029/2019AV000140
- Seasonality of Tropical Photosynthesis: A Pantropical Map of Correlations With Precipitation and Radiation and Comparison to Model Outputs M. Uribe et al. 10.1029/2020JG006123
- Satellite-observed solar-induced chlorophyll fluorescence reveals higher sensitivity of alpine ecosystems to snow cover on the Tibetan Plateau B. Qiu et al. 10.1016/j.agrformet.2019.02.045
- Contrasting biosphere responses to hydrometeorological extremes: revisiting the 2010 western Russian heatwave M. Flach et al. 10.5194/bg-15-6067-2018
- Detecting impacts of extreme events with ecological in situ monitoring networks M. Mahecha et al. 10.5194/bg-14-4255-2017
- Mapping global forest age from forest inventories, biomass and climate data S. Besnard et al. 10.5194/essd-13-4881-2021
- BESSv2.0: A satellite-based and coupled-process model for quantifying long-term global land–atmosphere fluxes B. Li et al. 10.1016/j.rse.2023.113696
- Intercomparison of global terrestrial carbon fluxes estimated by MODIS and Earth system models Q. Hu et al. 10.1016/j.scitotenv.2021.152231
- The Global Land Carbon Cycle Simulated With ISBA‐CTRIP: Improvements Over the Last Decade C. Delire et al. 10.1029/2019MS001886
- Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands J. Irvin et al. 10.1016/j.agrformet.2021.108528
- Characterizing the effect of scaling errors on the spatial downscaling of mountain vegetation gross primary productivity X. Xie & A. Li 10.1080/10095020.2023.2265149
- Constraining modelled global vegetation dynamics and carbon turnover using multiple satellite observations M. Forkel et al. 10.1038/s41598-019-55187-7
- Sensitivity of atmospheric CO2 growth rate to observed changes in terrestrial water storage V. Humphrey et al. 10.1038/s41586-018-0424-4
- Evaluation of earth system model and atmospheric inversion using total column CO2 observations from GOSAT and OCO-2 P. Patra et al. 10.1186/s40645-021-00420-z
- Weather data-centric prediction of maize non-stressed canopy temperature in semi-arid climates for irrigation management H. Nakabuye et al. 10.1007/s00271-023-00863-w
- A machine learning method trained by radiative transfer model inversion for generating seven global land and atmospheric estimates from VIIRS top-of-atmosphere observations G. Zhang et al. 10.1016/j.rse.2022.113132
- Improving Estimates of Gross Primary Productivity by Assimilating Solar‐Induced Fluorescence Satellite Retrievals in a Terrestrial Biosphere Model Using a Process‐Based SIF Model C. Bacour et al. 10.1029/2019JG005040
- An end-to-end satellite-based GPP estimation model devoid of meteorological and land cover data W. Zhu et al. 10.1016/j.agrformet.2023.109337
- Numerical modeling of ozone damage to plants and its effects on atmospheric CO2 in China X. Xie et al. 10.1016/j.atmosenv.2019.116970
- Contrasting responses of relationship between solar-induced fluorescence and gross primary production to drought across aridity gradients R. Qiu et al. 10.1016/j.rse.2023.113984
- Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties J. Exbrayat et al. 10.5194/esd-9-153-2018
- Improving the ability of solar-induced chlorophyll fluorescence to track gross primary production through differentiating sunlit and shaded leaves Z. Zhang et al. 10.1016/j.agrformet.2023.109658
- Minimum carbon uptake controls the interannual variability of ecosystem productivity in tropical evergreen forests Z. Li et al. 10.1016/j.gloplacha.2020.103343
- Using SMAP Level-4 soil moisture to constrain MOD16 evapotranspiration over the contiguous USA C. Brust et al. 10.1016/j.rse.2020.112277
- Evaluating the Interplay Between Biophysical Processes and Leaf Area Changes in Land Surface Models G. Forzieri et al. 10.1002/2018MS001284
- Definitions and methods to estimate regional land carbon fluxes for the second phase of the REgional Carbon Cycle Assessment and Processes Project (RECCAP-2) P. Ciais et al. 10.5194/gmd-15-1289-2022
- Characterization and Evaluation of Global Solar-Induced Chlorophyll Fluorescence Products: Estimation of Gross Primary Productivity and Phenology X. Zheng et al. 10.34133/remotesensing.0173
- The fate and transit time of carbon in a tropical forest C. Sierra et al. 10.1111/1365-2745.13723
- Simulation of site‐scale water fluxes in desert and natural oasis ecosystems of the arid region in Northwest China M. Xie et al. 10.1002/hyp.14444
- Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global‐scale models J. Jian et al. 10.1111/gcb.15795
- Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations A. Wolanin et al. 10.1016/j.rse.2019.03.002
- Do State‐Of‐The‐Art Atmospheric CO2 Inverse Models Capture Drought Impacts on the European Land Carbon Uptake? W. He et al. 10.1029/2022MS003150
- Future reversal of warming-enhanced vegetation productivity in the Northern Hemisphere Y. Zhang et al. 10.1038/s41558-022-01374-w
- Comparison of Phenology Estimated From Monthly Vegetation Indices and Solar-Induced Chlorophyll Fluorescence in China X. Wang et al. 10.3389/feart.2022.802763
- Upscaled diurnal cycles of land–atmosphere fluxes: a new global half-hourly data product P. Bodesheim et al. 10.5194/essd-10-1327-2018
- Implementation of Groundwater Lateral Flow and Human Water Regulation in CAS‐FGOALS‐g3 L. Wang et al. 10.1029/2019JD032289
- Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks G. Tramontana et al. 10.1111/gcb.15203
- Upscaling GOME-2 SIF from clear-sky instantaneous observations to all-sky sums leading to an improved SIF–GPP correlation J. Hu et al. 10.1016/j.agrformet.2021.108439
- Contrasting Performance of the Remotely-Derived GPP Products over Different Climate Zones across China Y. Chen et al. 10.3390/rs11161855
- Comparative Analysis of Two Machine Learning Algorithms in Predicting Site-Level Net Ecosystem Exchange in Major Biomes J. Liu et al. 10.3390/rs13122242
- A Scalable Earth Observations‐Based Decision Support System for Hydropower Planning in Africa A. Koppa et al. 10.1111/1752-1688.12914
- Inverse Determination of the Influence of Fire on Vegetation Carbon Turnover in the Pantropics J. Exbrayat et al. 10.1029/2018GB005925
- What is global photosynthesis? History, uncertainties and opportunities Y. Ryu et al. 10.1016/j.rse.2019.01.016
- Memory effects of climate and vegetation affecting net ecosystem CO2 fluxes in global forests S. Besnard et al. 10.1371/journal.pone.0211510
- On what scales can GOSAT flux inversions constrain anomalies in terrestrial ecosystems? B. Byrne et al. 10.5194/acp-19-13017-2019
- Bioenergy Crops for Low Warming Targets Require Half of the Present Agricultural Fertilizer Use W. Li et al. 10.1021/acs.est.1c02238
- Machine learning-based investigation of forest evapotranspiration, net ecosystem productivity, water use efficiency and their climate controls at meteorological station level H. Shi et al. 10.1016/j.jhydrol.2024.131811
- Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East‐West Divide of Temperate North America B. Byrne et al. 10.1029/2020GB006598
- Machine learning estimates of eddy covariance carbon flux in a scrub in the Mexican highland A. Guevara-Escobar et al. 10.5194/bg-18-367-2021
- Spatial Predictions and Associated Uncertainty of Annual Soil Respiration at the Global Scale D. Warner et al. 10.1029/2019GB006264
- Carbon–water flux coupling under progressive drought S. Boese et al. 10.5194/bg-16-2557-2019
- Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale W. Li et al. 10.5194/essd-12-789-2020
- Improving the Gross Primary Production Estimate by Merging and Downscaling Based on Deep Learning J. Lu et al. 10.3390/f14061201
- Different Satellite Products Revealing Variable Trends in Global Gross Primary Production Y. Bai et al. 10.1029/2022JG006918
- Aridity‐Dependent Land Surface Skin Temperature Biases in CMIP5/6 W. Wu & Z. Yang 10.1029/2022GL098952
- An abrupt shift in gross primary productivity over Eastern China-Mongolia and its inter-model diversity in land surface models D. Lee et al. 10.1038/s41598-023-49763-1
- Multi-sensor remote sensing for drought characterization: current status, opportunities and a roadmap for the future W. Jiao et al. 10.1016/j.rse.2021.112313
- Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity A. Bastos et al. 10.1126/sciadv.aba2724
- Peak growing season patterns and climate extremes-driven responses of gross primary production estimated by satellite and process based models over North America W. He et al. 10.1016/j.agrformet.2020.108292
- Modeling and Predicting Carbon and Water Fluxes Using Data-Driven Techniques in a Forest Ecosystem X. Dou & Y. Yang 10.3390/f8120498
- Correction to a Simple Biosphere Model 2 (SiB2) Simulation of Energy and Carbon Dioxide Fluxes over a Wheat Cropland in East China Using the Random Forest Model S. Zhang et al. 10.3390/atmos13122080
- Evaluating photosynthetic activity across Arctic-Boreal land cover types using solar-induced fluorescence R. Cheng et al. 10.1088/1748-9326/ac9dae
- Partitioning eddy covariance CO2 fluxes into ecosystem respiration and gross primary productivity through a new hybrid four sub-deep neural network H. Chen et al. 10.1016/j.agee.2023.108810
- Varying performance of eight evapotranspiration products with aridity and vegetation greenness across the globe H. Wang et al. 10.3389/fenvs.2023.1079520
- Terrestrial gross primary production: Using NIRV to scale from site to globe G. Badgley et al. 10.1111/gcb.14729
- Linking the complementary evaporation relationship with the Budyko framework for ungauged areas in Australia D. Kim et al. 10.5194/hess-26-5955-2022
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- Environmental control of land-atmosphere CO<sub>2</sub> fluxes from temperate ecosystems: a statistical approach based on homogenized time series from five land-use types V. Moreaux et al. 10.1080/16000889.2020.1784689
- Asymmetric responses of ecosystem productivity to rainfall anomalies vary inversely with mean annual rainfall over the conterminous United States A. Al‐Yaari et al. 10.1111/gcb.15345
- Eco‐evolutionary optimality as a means to improve vegetation and land‐surface models S. Harrison et al. 10.1111/nph.17558
- Imprints of evaporative conditions and vegetation type in diurnal temperature variations A. Panwar et al. 10.5194/hess-24-4923-2020
- Barium stable isotopes as a fingerprint of biological cycling in the Amazon River basin Q. Charbonnier et al. 10.5194/bg-17-5989-2020
- Environmental response characteristics of the carbon and water fluxes above complex urban surfaces of a subtropical megacity in China Y. Zhan et al. 10.1016/j.pce.2024.103681
- Impact of temperature and water availability on microwave-derived gross primary production I. Teubner et al. 10.5194/bg-18-3285-2021
- ERA-5 and ERA-Interim driven ISBA land surface model simulations: which one performs better? C. Albergel et al. 10.5194/hess-22-3515-2018
- Comparison of Regional Simulation of Biospheric CO2 Flux from the Updated Version of CarbonTracker Asia with FLUXCOM and Other Inversions over Asia S. Kenea et al. 10.3390/rs12010145
- A boreal forest model benchmarking dataset for North America: a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) B. Qu et al. 10.1088/1748-9326/ace376
- Global distribution of groundwater‐vegetation spatial covariation S. Koirala et al. 10.1002/2017GL072885
- Joint improvement on absorbed photosynthetically active radiation and intrinsic quantum yield efficiency algorithms in the P model betters the estimate of terrestrial gross primary productivity Z. Zhang et al. 10.1016/j.agrformet.2023.109883
- A Neural Network Model for Estimating Carbon Fluxes in Forest Ecosystems from Remote Sensing Data A. Rozanov & K. Gribanov 10.1134/S1024856023040152
- How the CMIP6 climate models project the historical terrestrial GPP in China C. Zhang et al. 10.1002/joc.7834
- Toward Robust Parameterizations in Ecosystem‐Level Photosynthesis Models S. Bao et al. 10.1029/2022MS003464
- Constraining global terrestrial gross primary productivity in a global carbon assimilation system with OCO-2 chlorophyll fluorescence data J. Wang et al. 10.1016/j.agrformet.2021.108424
- Understanding terrestrial water storage variations in northern latitudes across scales T. Trautmann et al. 10.5194/hess-22-4061-2018
- Three Decades of Gross Primary Production (GPP) in China: Variations, Trends, Attributions, and Prediction Inferred from Multiple Datasets and Time Series Modeling Y. Bo et al. 10.3390/rs14112564
- Improving the Estimation of Gross Primary Productivity across Global Biomes by Modeling Light Use Efficiency through Machine Learning D. Kong et al. 10.3390/rs15082086
- The spatial heterogeneity of the relationship between gross primary production and sun-induced chlorophyll fluorescence regulated by climate conditions during 2007–2018 Y. Wang et al. 10.1016/j.gecco.2021.e01721
- An Artificial Intelligence Approach to Predict Gross Primary Productivity in the Forests of South Korea Using Satellite Remote Sensing Data B. Lee et al. 10.3390/f11091000
- Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites H. Chu et al. 10.1016/j.agrformet.2021.108350
- Time‐Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity N. Linscheid et al. 10.1029/2021GL093285
- How well do light-use efficiency models capture large-scale drought impacts on vegetation productivity compared with data-driven estimates? Y. Lv et al. 10.1016/j.ecolind.2022.109739
- Impact of climate change on snowpack dynamics in coastal Central-Western Greenland J. Bonsoms et al. 10.1016/j.scitotenv.2023.169616
- New data‐driven estimation of terrestrial CO2 fluxes in Asia using a standardized database of eddy covariance measurements, remote sensing data, and support vector regression K. Ichii et al. 10.1002/2016JG003640
- A methodology to derive global maps of leaf traits using remote sensing and climate data Á. Moreno-Martínez et al. 10.1016/j.rse.2018.09.006
- No Proportional Increase of Terrestrial Gross Carbon Sequestration From the Greening Earth Y. Zhang et al. 10.1029/2018JG004917
- Can we replace observed forcing with weather generator in land surface modeling? Insights from long-term simulations at two contrasting boreal sites M. Alves et al. 10.1007/s00704-021-03615-y
- Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange Z. Fu et al. 10.1111/gcb.14731
- Modelling sun-induced fluorescence for improved evaluation of forest carbon flux (GPP): Case study of tropical deciduous forest, India S. Sinha et al. 10.1016/j.ecolmodel.2021.109552
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- Towards hybrid modeling of the global hydrological cycle B. Kraft et al. 10.5194/hess-26-1579-2022
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- A global moderate resolution dataset of gross primary production of vegetation for 2000–2016 Y. Zhang et al. 10.1038/sdata.2017.165
- Estimating Forest Carbon Fluxes Using Machine Learning Techniques Based on Eddy Covariance Measurements X. Dou et al. 10.3390/su10010203
- Improving E3SM Land Model Photosynthesis Parameterization via Satellite SIF, Machine Learning, and Surrogate Modeling A. Chen et al. 10.1029/2022MS003135
- Satellite-based solar-induced fluorescence tracks seasonal and elevational patterns of photosynthesis in California’s Sierra Nevada mountains L. Kunik et al. 10.1088/1748-9326/ad07b4
- Application of machine learning techniques to simulate the evaporative fraction and its relationship with environmental variables in corn crops T. Zenone et al. 10.1186/s13717-022-00400-1
- Improving CLM5.0 Biomass and Carbon Exchange Across the Western United States Using a Data Assimilation System B. Raczka et al. 10.1029/2020MS002421
- ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO<sub>2</sub>, water, and energy fluxes on daily to annual scales C. Qiu et al. 10.5194/gmd-11-497-2018
- Estimation of China’s terrestrial ecosystem carbon sink: Methods, progress and prospects S. Piao et al. 10.1007/s11430-021-9892-6
- Integration of flux footprint and physical mechanism into convolutional neural network model for enhanced simulation of urban evapotranspiration H. Chen et al. 10.1016/j.jhydrol.2022.129016
- Aircraft Measurements of Tropospheric CO2 in the North China Plain in Autumn and Winter of 2018–2019 H. Zhang et al. 10.3390/atmos14121835
- Uncertainty analysis of multiple global GPP datasets in characterizing the lagged effect of drought on photosynthesis X. Xie et al. 10.1016/j.ecolind.2020.106224
- Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink? C. Seiler et al. 10.1029/2021MS002946
- MODIS-based modeling of evapotranspiration from woody vegetation supported by root-zone water storage G. Cui et al. 10.1016/j.rse.2024.114000
- Machine learning models inaccurately predict current and future high-latitude C balances I. Shirley et al. 10.1088/1748-9326/acacb2
- Ecosystems are showing symptoms of resilience loss J. Rocha 10.1088/1748-9326/ac73a8
- Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1 A. Druel et al. 10.5194/gmd-15-8453-2022
- Ensemble Machine Learning Outperforms Empirical Equations for the Ground Heat Flux Estimation with Remote Sensing Data J. Bonsoms & G. Boulet 10.3390/rs14081788
- Improving global terrestrial evapotranspiration estimation using support vector machine by integrating three process-based algorithms Y. Yao et al. 10.1016/j.agrformet.2017.04.011
- Inner Mongolia grasslands act as a weak regional carbon sink: A new estimation based on upscaling eddy covariance observations C. You et al. 10.1016/j.agrformet.2023.109719
- Simulating Erosion‐Induced Soil and Carbon Delivery From Uplands to Rivers in a Global Land Surface Model H. Zhang et al. 10.1029/2020MS002121
- Spatiotemporal Changes and Driver Analysis of Ecosystem Respiration in the Tibetan and Inner Mongolian Grasslands W. Liu et al. 10.3390/rs14153563
- Machine learning in photosynthesis: Prospects on sustainable crop development R. Varghese et al. 10.1016/j.plantsci.2023.111795
- Climate drivers of the variations of vegetation productivity in India A. Verma et al. 10.1088/1748-9326/ac7c7f
- Technical note: Flagging inconsistencies in flux tower data M. Jung et al. 10.5194/bg-21-1827-2024
- Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach M. Jung et al. 10.5194/bg-17-1343-2020
- Upscaling of Latent Heat Flux in Heihe River Basin Based on Transfer Learning Model J. Lin et al. 10.3390/rs15071901
- Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network J. Beringer et al. 10.1111/gcb.16141
- Quantifying the effect of forest age in annual net forest carbon balance S. Besnard et al. 10.1088/1748-9326/aaeaeb
- Application of machine-learning methods in forest ecology: recent progress and future challenges Z. Liu et al. 10.1139/er-2018-0034
- High-Resolution Mapping of Gross Primary Production in Northeast China Using Landsat-8/9 and Sentinel-2 A/B X. Ma et al. 10.1109/JSTARS.2024.3432581
- Assimilation of Global Satellite Leaf Area Estimates Reduces Modeled Global Carbon Uptake and Energy Loss by Terrestrial Ecosystems A. Fox et al. 10.1029/2022JG006830
- Observational Constraints on the Response of High‐Latitude Northern Forests to Warming J. Liu et al. 10.1029/2020AV000228
- Modeling the daytime net primary productivity of maize at the canopy scale based on UAV multispectral imagery and machine learning M. Peng et al. 10.1016/j.jclepro.2022.133041
- Assimilation of Earth Observation Data Over Cropland and Grassland Sites into a Simple GPP Model M. Meroni et al. 10.3390/rs11070749
- The Impact of the 20–50-Day Atmospheric Intraseasonal Oscillation on the Gross Primary Productivity between the Yangtze and Yellow Rivers J. Li et al. 10.1175/JCLI-D-19-0575.1
- An evapotranspiration deficit-based drought index to detect variability of terrestrial carbon productivity in the Middle East K. Alsafadi et al. 10.1088/1748-9326/ac4765
- Validation of terrestrial biogeochemistry in CMIP6 Earth system models: a review L. Spafford & A. MacDougall 10.5194/gmd-14-5863-2021
- Revisiting and attributing the global controls over terrestrial ecosystem functions of climate and plant traits at FLUXNET sites via causal graphical models H. Shi et al. 10.5194/bg-20-2727-2023
- Research on Improving the Accuracy of SIF Data in Estimating Gross Primary Productivity in Arid Regions W. Liu et al. 10.3390/land13081222
- Satellite-based reflectances capture large fraction of variability in global gross primary production (GPP) at weekly time scales J. Joiner & Y. Yoshida 10.1016/j.agrformet.2020.108092
- A unified vegetation index for quantifying the terrestrial biosphere G. Camps-Valls et al. 10.1126/sciadv.abc7447
- Improved Estimation of the Gross Primary Production of Europe by Considering the Spatial and Temporal Changes in Photosynthetic Capacity from 2001 to 2016 Q. Wu et al. 10.3390/rs15051172
- Seasonal biological carryover dominates northern vegetation growth X. Lian et al. 10.1038/s41467-021-21223-2
- Estimating the Net Ecosystem Exchange at Global FLUXNET Sites Using a Random Forest Model N. Huang et al. 10.1109/JSTARS.2021.3114190
- Assimilation of vegetation optical depth retrievals from passive microwave radiometry S. Kumar et al. 10.5194/hess-24-3431-2020
- A fine spatial resolution estimation scheme for large-scale gross primary productivity (GPP) in mountain ecosystems by integrating an eco-hydrological model with the combination of linear and non-linear downscaling processes X. Xie et al. 10.1016/j.jhydrol.2022.128833
- Understanding the diurnal cycle of land–atmosphere interactions from flux site observations E. Seo & P. Dirmeyer 10.5194/hess-26-5411-2022
- Machine learning approach to predict terrestrial gross primary productivity using topographical and remote sensing data D. Prakash Sarkar et al. 10.1016/j.ecoinf.2022.101697
- Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes U. Marconato et al. 10.3389/fsoil.2022.903544
- Understanding the Land Carbon Cycle with Space Data: Current Status and Prospects J. Exbrayat et al. 10.1007/s10712-019-09506-2
- On the relationship between sub-daily instantaneous and daily total gross primary production: Implications for interpreting satellite-based SIF retrievals Y. Zhang et al. 10.1016/j.rse.2017.12.009
- Evaluation of water flux predictive models developed using eddy-covariance observations and machine learning: a meta-analysis H. Shi et al. 10.5194/hess-26-4603-2022
- Revisiting the choice of the driving temperature for eddy covariance CO2 flux partitioning G. Wohlfahrt & M. Galvagno 10.1016/j.agrformet.2017.02.012
- Spatiotemporal lagging of predictors improves machine learning estimates of atmosphere–forest CO2 exchange M. Kämäräinen et al. 10.5194/bg-20-897-2023
- Comparisons of numerical phenology models and machine learning methods on predicting the spring onset of natural vegetation across the Northern Hemisphere W. Li et al. 10.1016/j.ecolind.2021.108126
- Sun-induced fluorescence as a proxy for primary productivity across vegetation types and climates M. Pickering et al. 10.5194/bg-19-4833-2022
- Gap‐filling approaches for eddy covariance methane fluxes: A comparison of three machine learning algorithms and a traditional method with principal component analysis Y. Kim et al. 10.1111/gcb.14845
- Quantitative assessment of the scale conversion from instantaneous to daily GPP under various sky conditions based on MODIS local overpassing time J. Lee & J. Im 10.1080/15481603.2024.2319372
- Estimation of Turbulent Heat Fluxes and Gross Primary Productivity by Assimilating Land Surface Temperature and Leaf Area Index X. He et al. 10.1029/2020WR028224
- On the Potential of Sentinel-2 for Estimating Gross Primary Production D. Pabon-Moreno et al. 10.1109/TGRS.2022.3152272
- Carbon cycle responses to climate change across China's terrestrial ecosystem: Sensitivity and driving process K. Jiao et al. 10.1016/j.scitotenv.2024.170053
- Improved Constraints on Northern Extratropical CO2 Fluxes Obtained by Combining Surface‐Based and Space‐Based Atmospheric CO2 Measurements B. Byrne et al. 10.1029/2019JD032029
- Inferring global terrestrial carbon fluxes from the synergy of Sentinel 3 & 5P with Gaussian process hybrid models P. Reyes-Muñoz et al. 10.1016/j.rse.2024.114072
- GriddingMachine, a database and software for Earth system modeling at global and regional scales Y. Wang et al. 10.1038/s41597-022-01346-x
- The FLUXCOM ensemble of global land-atmosphere energy fluxes M. Jung et al. 10.1038/s41597-019-0076-8
- The Response of Vegetation to Regional Climate Change on the Tibetan Plateau Based on Remote Sensing Products and the Dynamic Global Vegetation Model M. Deng et al. 10.3390/rs14143337
- The importance of forest structure for carbon fluxes of the Amazon rainforest E. Rödig et al. 10.1088/1748-9326/aabc61
- Soil moisture–atmosphere feedback dominates land carbon uptake variability V. Humphrey et al. 10.1038/s41586-021-03325-5
- OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence Y. Sun et al. 10.1126/science.aam5747
- Seasonal changes in GPP/SIF ratios and their climatic determinants across the Northern Hemisphere A. Chen et al. 10.1111/gcb.15775
- Monitoring Drought Effects on Vegetation Productivity Using Satellite Solar-Induced Chlorophyll Fluorescence L. Zhang et al. 10.3390/rs11040378
- Machine learning models perform better than traditional empirical models for stomatal conductance when applied to multiple tree species across different forest biomes A. Saunders et al. 10.1016/j.tfp.2021.100139
- Supporting hierarchical soil biogeochemical modeling: version 2 of the Biogeochemical Transport and Reaction model (BeTR-v2) J. Tang et al. 10.5194/gmd-15-1619-2022
- Vegetation Index‐Based Models Without Meteorological Constraints Underestimate the Impact of Drought on Gross Primary Productivity X. Chen et al. 10.1029/2023JG007499
- Modeled Surface‐Atmosphere Fluxes From Paired Sites in the Upper Great Lakes Region Using Neural Networks D. Reed et al. 10.1029/2021JG006363
- Improving global gross primary productivity estimation using two-leaf light use efficiency model by considering various environmental factors via machine learning Z. Li et al. 10.1016/j.scitotenv.2024.176673
- Impacts of droughts and extreme-temperature events on gross primary production and ecosystem respiration: a systematic assessment across ecosystems and climate zones J. von Buttlar et al. 10.5194/bg-15-1293-2018
- Incorporating Spatial Autocorrelation into GPP Estimation Using Eigenvector Spatial Filtering R. Xu et al. 10.3390/f15071198
- Global trends in land-atmosphere CO<SUB>2</SUB> exchange fluxes: an analysis of a flux measurement dataset and comparison with terrestrial model simulations A. ITO 10.2480/agrmet.D-21-00015
- Midwest US Croplands Determine Model Divergence in North American Carbon Fluxes W. Sun et al. 10.1029/2020AV000310
- Evaluation of photosynthesis estimation from machine learning-based solar-induced chlorophyll fluorescence downscaling from canopy to leaf level H. Li et al. 10.1016/j.ecolind.2024.112439
- Increasing exposure of global croplands productivity to growing season heatwaves under climate warming Y. Chen et al. 10.1088/1748-9326/ad7868
- Global satellite-driven estimates of heterotrophic respiration A. Konings et al. 10.5194/bg-16-2269-2019
- Tracking Global Patterns of Drought‐Induced Productivity Loss Along Severity Gradient Y. Wang et al. 10.1029/2021JG006753
- Nitrogen leaching from natural ecosystems under global change: a modelling study M. Braakhekke et al. 10.5194/esd-8-1121-2017
- Joint Gaussian Processes for Biophysical Parameter Retrieval D. Svendsen et al. 10.1109/TGRS.2017.2767205
- Assimilation of Remotely Sensed LAI Into CLM4CN Using DART X. Ling et al. 10.1029/2019MS001634
- Evaluation of the LSA-SAF gross primary production product derived from SEVIRI/MSG data (MGPP) B. Martínez et al. 10.1016/j.isprsjprs.2019.11.010
- Effects of Anthropogenic Activity on Global Terrestrial Gross Primary Production I. Melnikova & T. Sasai 10.1029/2019JG005403
- Patterns and trends of the dominant environmental controls of net biome productivity B. Marcolla et al. 10.5194/bg-17-2365-2020
- Evaluating gross primary productivity over 9 ChinaFlux sites based on random forest regression models, remote sensing, and eddy covariance data X. Chang et al. 10.1016/j.scitotenv.2023.162601
- Simulating emission and scattering of solar-induced chlorophyll fluorescence at far-red band in global vegetation with different canopy structures B. Qiu et al. 10.1016/j.rse.2019.111373
- Variability and Trends of Actual Evapotranspiration over West Africa: The Role of Environmental Drivers. O. Adeyeri & K. Ishola 10.1016/j.agrformet.2021.108574
- Environment-sensitivity functions for gross primary productivity in light use efficiency models S. Bao et al. 10.1016/j.agrformet.2021.108708
- CLIMFILL v0.9: a framework for intelligently gap filling Earth observations V. Bessenbacher et al. 10.5194/gmd-15-4569-2022
- Large-Scale Analysis of the Spatiotemporal Changes of Net Ecosystem Production in Hindu Kush Himalayan Region D. Guo et al. 10.3390/rs13061180
- The fate of vegetation carbon stocks of India: Insights from a remote-sensed evaluation of carbon use efficiency A. Chakraborty et al. 10.1016/j.ecoinf.2023.102374
- Resolving heterogeneous fluxes from tundra halves the growing season carbon budget S. Ludwig et al. 10.5194/bg-21-1301-2024
- Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties A. Virkkala et al. 10.1111/gcb.15659
- Soil carbon response to land-use change: evaluation of a global vegetation model using observational meta-analyses S. Nyawira et al. 10.5194/bg-13-5661-2016
- Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques M. Flach et al. 10.5194/esd-8-677-2017
- Vegetation greenness and land carbon-flux anomalies associated with climate variations: a focus on the year 2015 C. Yue et al. 10.5194/acp-17-13903-2017
- Actual evapotranspiration estimation over the Tuojiang River Basin based on a hybrid CNN-RF model Y. Li et al. 10.1016/j.jhydrol.2022.127788
- Budyko‐Based Long‐Term Water and Energy Balance Closure in Global Watersheds From Earth Observations A. Koppa et al. 10.1029/2020WR028658
- Evaluating data-driven and hybrid modeling of terrestrial actual evapotranspiration based on an automatic machine learning approach N. Guo et al. 10.1016/j.jhydrol.2023.130594
- Making ecological models adequate W. Getz et al. 10.1111/ele.12893
- Extreme anomaly event detection in biosphere using linear regression and a spatiotemporal MRF model Y. Guanche García et al. 10.1007/s11069-018-3415-8
- Implications of the steady-state assumption for the global vegetation carbon turnover N. Fan et al. 10.1088/1748-9326/acfb22
- Assessment of Carbon Productivity Trends and Their Resilience to Drought Disturbances in the Middle East Based on Multi-Decadal Space-Based Datasets K. Alsafadi et al. 10.3390/rs14246237
- Hybrid modeling of evapotranspiration: inferring stomatal and aerodynamic resistances using combined physics-based and machine learning R. ElGhawi et al. 10.1088/1748-9326/acbbe0
- Estimating Global Gross Primary Production Using an Improved MODIS Leaf Area Index Dataset S. Wang et al. 10.3390/rs16193731
- Emergent relationships with respect to burned area in global satellite observations and fire-enabled vegetation models M. Forkel et al. 10.5194/bg-16-57-2019
- Uncertainty analysis of intra-module environmental stress parameter design in light use efficiency-based gross primary productivity estimation models C. Zhao & W. Zhu 10.1177/2754124X241235545
- Retrieval of solar-induced chlorophyll fluorescence (SIF) from satellite measurements: comparison of SIF between TanSat and OCO-2 L. Yao et al. 10.5194/amt-15-2125-2022
- CARDAMOM-FluxVal version 1.0: a FLUXNET-based validation system for CARDAMOM carbon and water flux estimates Y. Yang et al. 10.5194/gmd-15-1789-2022
- Divergent seasonal responses of carbon fluxes to extreme droughts over China Y. Deng et al. 10.1016/j.agrformet.2022.109253
- Triple collocation-based merging of multi-source gridded evapotranspiration data in the Nordic Region X. Li et al. 10.1016/j.agrformet.2023.109451
- Technical note: A view from space on global flux towers by MODIS and Landsat: the FluxnetEO data set S. Walther et al. 10.5194/bg-19-2805-2022
- Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations O. Peltola et al. 10.5194/essd-11-1263-2019
- A hybrid deep learning framework with physical process description for simulation of evapotranspiration H. Chen et al. 10.1016/j.jhydrol.2021.127422
- A framework for constructing machine learning models with feature set optimisation for evapotranspiration partitioning A. Stapleton et al. 10.1016/j.acags.2022.100105
- Combining flux variance similarity partitioning with artificial neural networks to gap-fill measurements of net ecosystem production of a Pacific Northwest Douglas-fir stand S. Lee et al. 10.1016/j.agrformet.2021.108382
- Data assimilation for continuous global assessment of severe conditions over terrestrial surfaces C. Albergel et al. 10.5194/hess-24-4291-2020
- The Global Distribution of Biological Nitrogen Fixation in Terrestrial Natural Ecosystems T. Davies‐Barnard & P. Friedlingstein 10.1029/2019GB006387
- Monitoring tropical forests under a functional perspective with satellite‐based vegetation optical depth G. Vaglio Laurin et al. 10.1111/gcb.15072
- Compensatory water effects link yearly global land CO2 sink changes to temperature M. Jung et al. 10.1038/nature20780
- Reduction of structural impacts and distinction of photosynthetic pathways in a global estimation of GPP from space-borne solar-induced chlorophyll fluorescence Z. Zhang et al. 10.1016/j.rse.2020.111722
- Multisatellite Analyses of Spatiotemporal Variability in Photosynthetic Activity Over the Tibetan Plateau X. Wang et al. 10.1029/2019JG005249
- Interannual variability in the Australian carbon cycle over 2015–2019, based on assimilation of Orbiting Carbon Observatory-2 (OCO-2) satellite data Y. Villalobos et al. 10.5194/acp-22-8897-2022
- An Online Deep Convolutional Model of Gross Primary Productivity and Net Ecosystem Exchange Estimation for Global Forests W. Wu et al. 10.1109/JSTARS.2019.2954556
- Evaluation of forest carbon uptake in South Korea using the national flux tower network, remote sensing, and data-driven technology S. Cho et al. 10.1016/j.agrformet.2021.108653
- Estimation of Net Ecosystem Productivity on the Tibetan Plateau Grassland from 1982 to 2018 Based on Random Forest Model J. Zheng et al. 10.3390/rs15092375
- Modeling the effects of litter stoichiometry and soil mineral N availability on soil organic matter formation using CENTURY-CUE (v1.0) H. Zhang et al. 10.5194/gmd-11-4779-2018
- Disequilibrium of terrestrial ecosystem CO<sub>2</sub> budget caused by disturbance-induced emissions and non-CO<sub>2</sub> carbon export flows: a global model assessment A. Ito 10.5194/esd-10-685-2019
- Uniform upscaling techniques for eddy covariance FLUXes (UFLUX) S. Zhu et al. 10.1080/01431161.2024.2312266
- Reply to: Large influence of atmospheric vapor pressure deficit on ecosystem production efficiency L. Liu et al. 10.1038/s41467-022-29010-3
- Improved Global Maps of the Optimum Growth Temperature, Maximum Light Use Efficiency, and Gross Primary Production for Vegetation Y. Chen et al. 10.1029/2020JG005651
- Four years of global carbon cycle observed from the Orbiting Carbon Observatory 2 (OCO-2) version 9 and in situ data and comparison to OCO-2 version 7 H. Peiro et al. 10.5194/acp-22-1097-2022
- Monitoring 2019 Drought and Assessing Its Effects on Vegetation Using Solar-Induced Chlorophyll Fluorescence and Vegetation Indexes in the Middle and Lower Reaches of Yangtze River, China M. Li et al. 10.3390/rs14112569
- Comprehensive accuracy assessment of long-term geostationary SEVIRI-MSG evapotranspiration estimates across Europe B. Bayat et al. 10.1016/j.rse.2023.113875
- Modeling Global Vegetation Gross Primary Productivity, Transpiration and Hyperspectral Canopy Radiative Transfer Simultaneously Using a Next Generation Land Surface Model—CliMA Land Y. Wang et al. 10.1029/2021MS002964
- Long-term gridded land evapotranspiration reconstruction using Deep Forest with high generalizability Q. Feng et al. 10.1038/s41597-023-02822-8
- Global modeling diurnal gross primary production from OCO-3 solar-induced chlorophyll fluorescence Z. Zhang et al. 10.1016/j.rse.2022.113383
- Interannual variation of terrestrial carbon cycle: Issues and perspectives S. Piao et al. 10.1111/gcb.14884
- Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model A. Norton et al. 10.5194/bg-16-3069-2019
- Changes in Water Use Efficiency Caused by Climate Change, CO2 Fertilization, and Land Use Changes on the Tibetan Plateau B. Jia et al. 10.1007/s00376-022-2172-5
- LDAS-Monde Sequential Assimilation of Satellite Derived Observations Applied to the Contiguous US: An ERA-5 Driven Reanalysis of the Land Surface Variables C. Albergel et al. 10.3390/rs10101627
- Ideas and perspectives: enhancing the impact of the FLUXNET network of eddy covariance sites D. Papale 10.5194/bg-17-5587-2020
- Synergy between TROPOMI sun-induced chlorophyll fluorescence and MODIS spectral reflectance for understanding the dynamics of gross primary productivity at Integrated Carbon Observatory System (ICOS) ecosystem flux sites H. Balde et al. 10.5194/bg-20-1473-2023
- Contrasting Drought Propagation Into the Terrestrial Water Cycle Between Dry and Wet Regions W. Li et al. 10.1029/2022EF003441
- Evaluating Cumulative Drought Effect on Global Vegetation Photosynthesis Using Numerous GPP Products C. Wu & T. Wang 10.3389/fenvs.2022.908875
- Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations C. Abadie et al. 10.1029/2023JG007407
- Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence S. Alemohammad et al. 10.5194/bg-14-4101-2017
- Machine Learning Research Trends in Africa: A 30 Years Overview with Bibliometric Analysis Review A. Ezugwu et al. 10.1007/s11831-023-09930-z
- Gross primary productivity of terrestrial ecosystems: a review of observations, remote sensing, and modelling studies over South Asia V. Pandey et al. 10.1007/s00704-024-05158-4
- An ensemble square root filter for the joint assimilation of surface soil moisture and leaf area index within the Land Data Assimilation System LDAS-Monde: application over the Euro-Mediterranean region B. Bonan et al. 10.5194/hess-24-325-2020
- Methane emissions reduce the radiative cooling effect of a subtropical estuarine mangrove wetland by half J. Liu et al. 10.1111/gcb.15247
- Nonlinear PCA for Spatio-Temporal Analysis of Earth Observation Data D. Bueso et al. 10.1109/TGRS.2020.2969813
- Increasing drought sensitivity of plant photosynthetic phenology and physiology Y. Wang et al. 10.1016/j.ecolind.2024.112469
- Large‐Scale Droughts Responsible for Dramatic Reductions of Terrestrial Net Carbon Uptake Over North America in 2011 and 2012 W. He et al. 10.1029/2018JG004520
- Towards a universal evapotranspiration model based on optimality principles S. Tan et al. 10.1016/j.agrformet.2023.109478
- Decreasing Cropping Intensity Dominated the Negative Trend of Cropland Productivity in Southern China in 2000–2015 Z. Niu et al. 10.3390/su122310070
- Comparing the use of all data or specific subsets for training machine learning models in hydrology: A case study of evapotranspiration prediction H. Shi et al. 10.1016/j.jhydrol.2023.130399
- Exploring the spatial relationship between airborne-derived red and far-red sun-induced fluorescence and process-based GPP estimates in a forest ecosystem G. Tagliabue et al. 10.1016/j.rse.2019.111272
- Global Carbon Fluxes Using Multioutput Gaussian Processes Regression and MODIS Products M. Campos-Taberner et al. 10.1109/JSTARS.2024.3413184
- Warming inhibits increases in vegetation net primary productivity despite greening in India R. Das et al. 10.1038/s41598-023-48614-3
- Empirical upscaling of OzFlux eddy covariance for high-resolution monitoring of terrestrial carbon uptake in Australia C. Burton et al. 10.5194/bg-20-4109-2023
- Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers J. De Pue et al. 10.5194/bg-20-4795-2023
- Accelerated dryland expansion regulates future variability in dryland gross primary production J. Yao et al. 10.1038/s41467-020-15515-2
- Apparent ecosystem carbon turnover time: uncertainties and robust features N. Fan et al. 10.5194/essd-12-2517-2020
- Land use change and El Niño-Southern Oscillation drive decadal carbon balance shifts in Southeast Asia M. Kondo et al. 10.1038/s41467-018-03374-x
- TAVIs: Topographically Adjusted Vegetation Index for a Reliable Proxy of Gross Primary Productivity in Mountain Ecosystems X. Xie et al. 10.1109/TGRS.2023.3336727
- Estimating Ecosystem Respiration in the Grasslands of Northern China Using Machine Learning: Model Evaluation and Comparison X. Zhu et al. 10.3390/su12052099
- Causal hybrid modeling with double machine learning—applications in carbon flux modeling K. Cohrs et al. 10.1088/2632-2153/ad5a60
- Predicting multi-annual green roof net ecosystem exchange using machine learning T. Husting et al. 10.1016/j.buildenv.2024.111878
- Recent trends in gross primary production and their drivers: analysis and modelling at flux-site and global scales W. Cai & I. Prentice 10.1088/1748-9326/abc64e
- Addressing biases in Arctic–boreal carbon cycling in the Community Land Model Version 5 L. Birch et al. 10.5194/gmd-14-3361-2021
- More severe drought detected by the assimilation of brightness temperature and terrestrial water storage anomalies in Texas during 2010–2013 W. Chen et al. 10.1016/j.jhydrol.2021.126802
- Remote sensing of terrestrial gross primary productivity: a review of advances in theoretical foundation, key parameters and methods W. Zhu et al. 10.1080/15481603.2024.2318846
- The potential of remote sensing-based models on global water-use efficiency estimation: An evaluation and intercomparison of an ecosystem model (BESS) and algorithm (MODIS) using site level and upscaled eddy covariance data S. Yang et al. 10.1016/j.agrformet.2020.107959
- Earth system data cubes unravel global multivariate dynamics M. Mahecha et al. 10.5194/esd-11-201-2020
- A model for urban biogenic CO<sub>2</sub> fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1) D. Wu et al. 10.5194/gmd-14-3633-2021
- Non-linear correlations exist between solar-induced chlorophyll fluorescence and canopy photosynthesis in a subtropical evergreen forest in Southwest China Y. Wang et al. 10.1016/j.ecolind.2023.111311
- Monitoring soil carbon flux with in-situ measurements and satellite observations in a forested region C. Xu et al. 10.1016/j.geoderma.2020.114617
- Recent global decline in rainfall interception loss due to altered rainfall regimes X. Lian et al. 10.1038/s41467-022-35414-y
- High-resolution spatial patterns and drivers of terrestrial ecosystem carbon dioxide, methane, and nitrous oxide fluxes in the tundra A. Virkkala et al. 10.5194/bg-21-335-2024
- Causal inference reveals the dominant role of interannual variability of carbon sinks in complicated environmental-terrestrial ecosystems C. Dang et al. 10.1016/j.rse.2024.114300
- Global terrestrial carbon fluxes of 1999–2019 estimated by upscaling eddy covariance data with a random forest J. Zeng et al. 10.1038/s41597-020-00653-5
- A Novel Approach for Predicting Anthropogenic CO2 Emissions Using Machine Learning Based on Clustering of the CO2 Concentration Z. Ji et al. 10.3390/atmos15030323
- A carbon sink-driven approach to estimate gross primary production from microwave satellite observations I. Teubner et al. 10.1016/j.rse.2019.04.022
- A pigment ratio index based on remotely sensed reflectance provides the potential for universal gross primary production estimation W. Wu et al. 10.1088/1748-9326/abf3dc
- Effect of tree demography and flexible root water uptake for modeling the carbon and water cycles of Amazonia E. Joetzjer et al. 10.1016/j.ecolmodel.2022.109969
- MEBA: AI-powered precise building monthly energy benchmarking approach T. Li et al. 10.1016/j.apenergy.2024.122716
- A Practical Algorithm for Correcting Topographical Effects on Global GPP Products X. Xie et al. 10.1029/2023JG007553
- Identifying thresholds of time-lag and accumulative effects of extreme precipitation on major vegetation types at global scale M. Liu et al. 10.1016/j.agrformet.2024.110239
- Rapid recovery of net ecosystem production in a semi-arid woodland after a wildfire Q. Sun et al. 10.1016/j.agrformet.2020.108099
- Coupling a light use efficiency model with a machine learning-based water constraint for predicting grassland gross primary production R. Yu et al. 10.1016/j.agrformet.2023.109634
- The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model A. Rahman et al. 10.3390/rs14030437
- A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks Y. Zhang et al. 10.5194/bg-15-5779-2018
- Estimation of Global Grassland Net Ecosystem Carbon Exchange Using a Model Tree Ensemble Approach W. Liang et al. 10.1029/2019JG005034
- The Relationship of Gross Primary Productivity with NDVI Rather than Solar-Induced Chlorophyll Fluorescence Is Weakened under the Stress of Drought W. Zhao et al. 10.3390/rs16030555
- Globally Scalable Approach to Estimate Net Ecosystem Exchange Based on Remote Sensing, Meteorological Data, and Direct Measurements of Eddy Covariance Sites R. Zhuravlev et al. 10.3390/rs14215529
- Carbon fluxes and environmental controls across different alpine grassland types on the Tibetan Plateau Y. Wang et al. 10.1016/j.agrformet.2021.108694
- Soil respiration–driven CO 2 pulses dominate Australia’s flux variability E. Metz et al. 10.1126/science.add7833
- Deep learning and process understanding for data-driven Earth system science M. Reichstein et al. 10.1038/s41586-019-0912-1
- Global Estimates of Marine Gross Primary Production Based on Machine Learning Upscaling of Field Observations Y. Huang et al. 10.1029/2020GB006718
- Estimation of vegetation traits with kernel NDVI Q. Wang et al. 10.1016/j.isprsjprs.2022.12.019
- Five years of variability in the global carbon cycle: comparing an estimate from the Orbiting Carbon Observatory-2 and process-based models Z. Chen et al. 10.1088/1748-9326/abfac1
- Machine learning methods for assessing photosynthetic activity: environmental monitoring applications S. Khruschev et al. 10.1007/s12551-022-00982-2
- Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years J. Xiao et al. 10.1016/j.rse.2019.111383
- Biological factors dominate the interannual variability of evapotranspiration in an irrigated cropland in the North China Plain H. Lei et al. 10.1016/j.agrformet.2018.01.007
- Towards effective drought monitoring in the Middle East and North Africa (MENA) region: implications from assimilating leaf area index and soil moisture into the Noah-MP land surface model for Morocco W. Nie et al. 10.5194/hess-26-2365-2022
- Remote-Sensing Inversion Method for Evapotranspiration by Fusing Knowledge and Multisource Data J. Wang et al. 10.1155/2022/2076633
- Warmer spring alleviated the impacts of 2018 European summer heatwave and drought on vegetation photosynthesis S. Wang et al. 10.1016/j.agrformet.2020.108195
- Improved water use efficiency of vegetation due to carbon fertilization not translating to increased soil moisture in India A. Verma & S. Ghosh 10.1016/j.jhydrol.2024.131890
- A review of machine learning models and influential factors for estimating evapotranspiration using remote sensing and ground-based data S. Amani & H. Shafizadeh-Moghadam 10.1016/j.agwat.2023.108324
- Gap‐Filled Multivariate Observations of Global Land–Climate Interactions V. Bessenbacher et al. 10.1029/2023JD039099
- A framework for estimating actual evapotranspiration at weather stations without flux observations by combining data from MODIS and flux towers through a machine learning approach C. Zhang et al. 10.1016/j.jhydrol.2021.127047
- Resolve the Clear‐Sky Continuous Diurnal Cycle of High‐Resolution ECOSTRESS Evapotranspiration and Land Surface Temperature J. Wen et al. 10.1029/2022WR032227
- Evaluating GPP and Respiration Estimates Over Northern Midlatitude Ecosystems Using Solar‐Induced Fluorescence and Atmospheric CO2 Measurements B. Byrne et al. 10.1029/2018JG004472
- Use of Sun-Induced Chlorophyll Fluorescence Obtained by OCO-2 and GOME-2 for GPP Estimates of the Heihe River Basin, China X. Wei et al. 10.3390/rs10122039
- Increased photosynthesis during spring drought in energy-limited ecosystems D. Miller et al. 10.1038/s41467-023-43430-9
- Estimating Global GPP From the Plant Functional Type Perspective Using a Machine Learning Approach R. Guo et al. 10.1029/2022JG007100
- Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability K. Wang et al. 10.1038/s41467-022-31175-w
- Schätzung der Verdunstung mithilfe von Machine- und Deep Learning-Methoden C. Brenner et al. 10.1007/s00506-021-00768-y
- Predicting carbon and water vapor fluxes using machine learning and novel feature ranking algorithms X. Cui et al. 10.1016/j.scitotenv.2021.145130
- Estimating Gross Primary Productivity (GPP) over Rice–Wheat-Rotation Croplands by Using the Random Forest Model and Eddy Covariance Measurements: Upscaling and Comparison with the MODIS Product Z. Duan et al. 10.3390/rs13214229
- The impact of indicator selection on assessment of global greening B. Qiu et al. 10.1080/15481603.2021.1879494
- A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1) M. Forkel et al. 10.5194/gmd-10-4443-2017
- Retrieval of daily gross primary production over Europe and Africa from an ensemble of SEVIRI/MSG products B. Martínez et al. 10.1016/j.jag.2017.10.011
- CO2 exchange and evapotranspiration across dryland ecosystems of southwestern North America J. Biederman et al. 10.1111/gcb.13686
- A multi-perspective input selection strategy for daily net ecosystem exchange predictions based on machine learning methods Ö. Ekmekcioğlu et al. 10.1007/s00704-022-04265-4
- Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis S. Walther et al. 10.5194/bg-15-6221-2018
- Impacts of extreme summers on European ecosystems: a comparative analysis of 2003, 2010 and 2018 A. Bastos et al. 10.1098/rstb.2019.0507
- Validation of drought indices using environmental indicators: streamflow and carbon flux data U. Bhuyan-Erhardt et al. 10.1016/j.agrformet.2018.11.016
- Moisture availability mediates the relationship between terrestrial gross primary production and solar‐induced chlorophyll fluorescence: Insights from global‐scale variations A. Chen et al. 10.1111/gcb.15373
- Artificial intelligence and Eddy covariance: A review A. Lucarini et al. 10.1016/j.scitotenv.2024.175406
- Vegetation clumping modulates global photosynthesis through adjusting canopy light environment F. Li et al. 10.1111/gcb.16503
- Actual Evapotranspiration Estimates in Arid Cold Regions Using Machine Learning Algorithms with In Situ and Remote Sensing Data J. Mosre & F. Suárez 10.3390/w13060870
- Increased productivity of temperate vegetation in the preceding year drives early spring phenology in the subsequent year in northern China Q. Zhang et al. 10.1016/j.scitotenv.2023.166676
- Global increase in the optimal temperature for the productivity of terrestrial ecosystems Z. Fang et al. 10.1038/s43247-024-01636-9
- Global dryland aridity changes indicated by atmospheric, hydrological, and vegetation observations at meteorological stations H. Shi et al. 10.5194/hess-27-4551-2023
- Kernel methods and their derivatives: Concept and perspectives for the earth system sciences J. Johnson et al. 10.1371/journal.pone.0235885
- Benchmarking large-scale evapotranspiration estimates: A perspective from a calibration-free complementary relationship approach and FLUXCOM N. Ma et al. 10.1016/j.jhydrol.2020.125221
- Exploring the Best-Matching Plant Traits and Environmental Factors for Vegetation Indices in Estimates of Global Gross Primary Productivity W. Zhao & Z. Zhu 10.3390/rs14246316
- Gaussianizing the Earth: Multidimensional information measures for Earth data analysis J. Johnson et al. 10.1109/MGRS.2021.3066260
- Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks B. He et al. 10.1093/nsr/nwab150
- Large loss of CO2 in winter observed across the northern permafrost region S. Natali et al. 10.1038/s41558-019-0592-8
- Non-growing season carbon emissions in a northern peatland are projected to increase under global warming A. Rafat et al. 10.1038/s43247-021-00184-w
- Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations J. Zscheischler et al. 10.5194/bg-14-3685-2017
- The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data G. Pastorello et al. 10.1038/s41597-020-0534-3
- A Promising Tool to Determine Daily Et by Monitoring Soil Water Changes Caused by Evapotranspiration in the Hilly and Gully Regions of the Loess Plateau W. Sun et al. 10.2139/ssrn.4156073
- Spatial-temporal patterns of land surface evapotranspiration from global products R. Tang et al. 10.1016/j.rse.2024.114066
- Coupling the Canadian Terrestrial Ecosystem Model (CTEM v. 2.0) to Environment and Climate Change Canada's greenhouse gas forecast model (v.107-glb) B. Badawy et al. 10.5194/gmd-11-631-2018
- Detecting drought-induced GPP spatiotemporal variabilities with sun-induced chlorophyll fluorescence during the 2009/2010 droughts in China S. Chen et al. 10.1016/j.ecolind.2020.107092
- Contrasting and interacting changes in simulated spring and summer carbon cycle extremes in European ecosystems S. Sippel et al. 10.1088/1748-9326/aa7398
- Carbon Flux Variability From a Relatively Simple Ecosystem Model With Assimilated Data Is Consistent With Terrestrial Biosphere Model Estimates G. Quetin et al. 10.1029/2019MS001889
- Comparison between deep learning architectures for the 1 km, 10/15-min estimation of downward shortwave radiation from AHI and ABI R. Li et al. 10.1016/j.rse.2023.113697
- Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions T. Lippmann et al. 10.5194/gmd-16-6773-2023
- Primary productivity estimation of forest based on in-situ biophysical parameters and sentinel satellite data using vegetation photosynthesis model in an eastern Indian tropical dry deciduous forest S. Ahmad et al. 10.1007/s42965-022-00220-6
- Upscaling Net Ecosystem Exchange Over Heterogeneous Landscapes With Machine Learning O. Reitz et al. 10.1029/2020JG005814
- Using automated machine learning for the upscaling of gross primary productivity M. Gaber et al. 10.5194/bg-21-2447-2024
- Inferring causal relations from observational long-term carbon and water fluxes records E. Díaz et al. 10.1038/s41598-022-05377-7
- Physics‐Constrained Machine Learning of Evapotranspiration W. Zhao et al. 10.1029/2019GL085291
- Ground‐Based Multiangle Solar‐Induced Chlorophyll Fluorescence Observation and Angular Normalization for Assessing Crop Productivity Q. Zhang et al. 10.1029/2020JG006082
- Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison G. McNicol et al. 10.1029/2023AV000956
- Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project S. Hantson et al. 10.5194/gmd-13-3299-2020
- 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
- Spatio-temporal patterns of evapotranspiration based on upscaling eddy covariance measurements in the dryland of the North China Plain B. Fang et al. 10.1016/j.agrformet.2019.107844
- Defining model complexity: An ecological perspective C. Malmborg et al. 10.1002/met.2202
- A Review of Machine Learning Applications in Land Surface Modeling S. Pal & P. Sharma 10.3390/earth2010011
- A Data‐Driven Global Soil Heterotrophic Respiration Dataset and the Drivers of Its Inter‐Annual Variability Y. Yao et al. 10.1029/2020GB006918
- Contributions of climate change, land use change and CO2 to changes in the gross primary productivity of the Tibetan Plateau X. LUO et al. 10.1080/16742834.2020.1695515
- Fluxes all of the time? A primer on the temporal representativeness of FLUXNET H. Chu et al. 10.1002/2016JG003576
- Selected breakpoints of net forest carbon uptake at four eddy-covariance sites T. Foken et al. 10.1080/16000889.2021.1915648
- Carbon cycle: ESP and UAV data processing approaches for forest ecosystem monitoring examples M. Platonova et al. 10.18303/2619-1563-2023-4-45
- Reverse engineering model structures for soil and ecosystem respiration: the potential of gene expression programming I. Ilie et al. 10.5194/gmd-10-3519-2017
- Atmospheric dryness reduces photosynthesis along a large range of soil water deficits Z. Fu et al. 10.1038/s41467-022-28652-7
- A 1 km Global Carbon Flux Dataset Using In Situ Measurements and Deep Learning W. Shangguan et al. 10.3390/f14050913
- Estimating Global Anthropogenic CO2 Gridded Emissions Using a Data-Driven Stacked Random Forest Regression Model Y. Zhang et al. 10.3390/rs14163899
- Technical note: Uncertainties in eddy covariance CO<sub>2</sub> fluxes in a semiarid sagebrush ecosystem caused by gap-filling approaches J. Yao et al. 10.5194/acp-21-15589-2021
- Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation R. Oliver et al. 10.5194/gmd-15-5567-2022
- Estimation of Terrestrial Global Gross Primary Production (GPP) with Satellite Data-Driven Models and Eddy Covariance Flux Data J. Joiner et al. 10.3390/rs10091346
- Optimizing variables selection of random forest to predict radial growth of Larix gmelinii var. principis-rupprechtii in temperate regions Y. Zhang et al. 10.1016/j.foreco.2024.122159
- Increasing impact of warm droughts on northern ecosystem productivity over recent decades D. Gampe et al. 10.1038/s41558-021-01112-8
- Global Assimilation of Remotely Sensed Leaf Area Index: The Impact of Updating More State Variables Within a Land Surface Model A. Rahman et al. 10.3389/frwa.2021.789352
- A novel approach for retrieving GPP of evergreen forest regions of India using random forest regression D. Sarkar et al. 10.1016/j.rsase.2023.101116
- Climate‐Driven Variability and Trends in Plant Productivity Over Recent Decades Based on Three Global Products M. O'Sullivan et al. 10.1029/2020GB006613
- Advanced time-lagged effects of drought on global vegetation growth and its social risk in the 21st century T. Chen et al. 10.1016/j.jenvman.2023.119253
- Summarizing the state of the terrestrial biosphere in few dimensions G. Kraemer et al. 10.5194/bg-17-2397-2020
- Evaluation of remotely sensed global evapotranspiration data from inland river basins Z. Liu 10.1002/hyp.14774
- Spatiotemporal Modeling of Carbon Fluxes over Complex Underlying Surfaces along the North Shore of Hangzhou Bay K. Zhang et al. 10.3390/atmos15060727
- Increasing terrestrial ecosystem carbon release in response to autumn cooling and warming R. Tang et al. 10.1038/s41558-022-01304-w
- Prediction of global water use efficiency and its response to vapor pressure deficit and soil moisture coupling in the 21st century T. Chen et al. 10.1016/j.jhydrol.2024.131203
- Contrasting drought legacy effects on gross primary productivity in a mixed versus pure beech forest X. Yu et al. 10.5194/bg-19-4315-2022
- Investigating the ability of deep learning on actual evapotranspiration estimation in the scarcely observed region X. Wang et al. 10.1016/j.jhydrol.2022.127506
- Assimilation of Remotely Sensed Leaf Area Index into the Noah-MP Land Surface Model: Impacts on Water and Carbon Fluxes and States over the Continental United States S. Kumar et al. 10.1175/JHM-D-18-0237.1
- Using an object-based machine learning ensemble approach to upscale evapotranspiration measured from eddy covariance towers in a subtropical wetland C. Zhang et al. 10.1016/j.scitotenv.2022.154969
- The Spatio-Temporal Variations of GPP and Its Climatic Driving Factors in the Yangtze River Basin during 2000–2018 C. Nie et al. 10.3390/f14091898
- Long term variation of evapotranspiration and water balance based on upscaling eddy covariance observations over the temperate semi-arid grassland of China X. Pang et al. 10.1016/j.agrformet.2021.108566
- Early forecasting of corn yield and price variations using satellite vegetation products F. Teste et al. 10.1016/j.compag.2024.108962
- Evaluating global ecosystem water use efficiency response to drought based on multi-model analysis S. Yang et al. 10.1016/j.scitotenv.2021.146356
- Investigation of Carbon-Dioxide-Emissions from Underutilized Grassland between 2019 and 2020 K. Varga et al. 10.3390/agronomy12040931
- Concurrent and lagged effects of spring greening on seasonal carbon gain and water loss across the Northern Hemisphere J. Jin et al. 10.1007/s00484-020-01913-0
- A decreasing carbon allocation to belowground autotrophic respiration in global forest ecosystems X. Tang et al. 10.1016/j.scitotenv.2021.149273
- A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research D. Montero et al. 10.1038/s41597-023-02096-0
- Vegetation modulates the impact of climate extremes on gross primary production M. Flach et al. 10.5194/bg-18-39-2021
- Responses of vegetation greenness and carbon cycle to extreme droughts in China Y. Deng et al. 10.1016/j.agrformet.2020.108307
- Partitioning Net Ecosystem Exchange (NEE) of CO2 Using Solar‐Induced Chlorophyll Fluorescence (SIF) O. Kira et al. 10.1029/2020GL091247
- Constraining biospheric carbon dioxide fluxes by combined top-down and bottom-up approaches S. Upton et al. 10.5194/acp-24-2555-2024
- Characterizing satellite-derived freeze/thaw regimes through spatial and temporal clustering for the identification of growing season constraints on vegetation productivity R. Melser et al. 10.1016/j.rse.2024.114210
- Recent Changes in Global Photosynthesis and Terrestrial Ecosystem Respiration Constrained From Multiple Observations W. Li et al. 10.1002/2017GL076622
- Improving estimations of ecosystem respiration with asymmetric daytime and nighttime temperature sensitivity and relative humidity N. Li et al. 10.1016/j.agrformet.2021.108709
- Global estimates of L-band vegetation optical depth and soil permittivity of snow-covered boreal forests and permafrost landscape using SMAP satellite data D. Kumawat et al. 10.1016/j.rse.2024.114145
- P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production B. Stocker et al. 10.5194/gmd-13-1545-2020
- An Ecosystem-Scale Flux Measurement Strategy to Assess Natural Climate Solutions K. Hemes et al. 10.1021/acs.est.0c06421
- Forecasting CO2 emissions of fuel vehicles for an ecological world using ensemble learning, machine learning, and deep learning models F. Gurcan 10.7717/peerj-cs.2234
- Assessing the relationship between microwave vegetation optical depth and gross primary production I. Teubner et al. 10.1016/j.jag.2017.10.006
- Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask? S. Gallup et al. 10.1029/2021MS002555
- Cropland Carbon Uptake Delayed and Reduced by 2019 Midwest Floods Y. Yin et al. 10.1029/2019AV000140
- Seasonality of Tropical Photosynthesis: A Pantropical Map of Correlations With Precipitation and Radiation and Comparison to Model Outputs M. Uribe et al. 10.1029/2020JG006123
- Satellite-observed solar-induced chlorophyll fluorescence reveals higher sensitivity of alpine ecosystems to snow cover on the Tibetan Plateau B. Qiu et al. 10.1016/j.agrformet.2019.02.045
- Contrasting biosphere responses to hydrometeorological extremes: revisiting the 2010 western Russian heatwave M. Flach et al. 10.5194/bg-15-6067-2018
- Detecting impacts of extreme events with ecological in situ monitoring networks M. Mahecha et al. 10.5194/bg-14-4255-2017
- Mapping global forest age from forest inventories, biomass and climate data S. Besnard et al. 10.5194/essd-13-4881-2021
- BESSv2.0: A satellite-based and coupled-process model for quantifying long-term global land–atmosphere fluxes B. Li et al. 10.1016/j.rse.2023.113696
- Intercomparison of global terrestrial carbon fluxes estimated by MODIS and Earth system models Q. Hu et al. 10.1016/j.scitotenv.2021.152231
- The Global Land Carbon Cycle Simulated With ISBA‐CTRIP: Improvements Over the Last Decade C. Delire et al. 10.1029/2019MS001886
- Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands J. Irvin et al. 10.1016/j.agrformet.2021.108528
- Characterizing the effect of scaling errors on the spatial downscaling of mountain vegetation gross primary productivity X. Xie & A. Li 10.1080/10095020.2023.2265149
- Constraining modelled global vegetation dynamics and carbon turnover using multiple satellite observations M. Forkel et al. 10.1038/s41598-019-55187-7
- Sensitivity of atmospheric CO2 growth rate to observed changes in terrestrial water storage V. Humphrey et al. 10.1038/s41586-018-0424-4
- Evaluation of earth system model and atmospheric inversion using total column CO2 observations from GOSAT and OCO-2 P. Patra et al. 10.1186/s40645-021-00420-z
- Weather data-centric prediction of maize non-stressed canopy temperature in semi-arid climates for irrigation management H. Nakabuye et al. 10.1007/s00271-023-00863-w
- A machine learning method trained by radiative transfer model inversion for generating seven global land and atmospheric estimates from VIIRS top-of-atmosphere observations G. Zhang et al. 10.1016/j.rse.2022.113132
- Improving Estimates of Gross Primary Productivity by Assimilating Solar‐Induced Fluorescence Satellite Retrievals in a Terrestrial Biosphere Model Using a Process‐Based SIF Model C. Bacour et al. 10.1029/2019JG005040
- An end-to-end satellite-based GPP estimation model devoid of meteorological and land cover data W. Zhu et al. 10.1016/j.agrformet.2023.109337
- Numerical modeling of ozone damage to plants and its effects on atmospheric CO2 in China X. Xie et al. 10.1016/j.atmosenv.2019.116970
- Contrasting responses of relationship between solar-induced fluorescence and gross primary production to drought across aridity gradients R. Qiu et al. 10.1016/j.rse.2023.113984
- Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties J. Exbrayat et al. 10.5194/esd-9-153-2018
- Improving the ability of solar-induced chlorophyll fluorescence to track gross primary production through differentiating sunlit and shaded leaves Z. Zhang et al. 10.1016/j.agrformet.2023.109658
- Minimum carbon uptake controls the interannual variability of ecosystem productivity in tropical evergreen forests Z. Li et al. 10.1016/j.gloplacha.2020.103343
- Using SMAP Level-4 soil moisture to constrain MOD16 evapotranspiration over the contiguous USA C. Brust et al. 10.1016/j.rse.2020.112277
- Evaluating the Interplay Between Biophysical Processes and Leaf Area Changes in Land Surface Models G. Forzieri et al. 10.1002/2018MS001284
- Definitions and methods to estimate regional land carbon fluxes for the second phase of the REgional Carbon Cycle Assessment and Processes Project (RECCAP-2) P. Ciais et al. 10.5194/gmd-15-1289-2022
- Characterization and Evaluation of Global Solar-Induced Chlorophyll Fluorescence Products: Estimation of Gross Primary Productivity and Phenology X. Zheng et al. 10.34133/remotesensing.0173
- The fate and transit time of carbon in a tropical forest C. Sierra et al. 10.1111/1365-2745.13723
- Simulation of site‐scale water fluxes in desert and natural oasis ecosystems of the arid region in Northwest China M. Xie et al. 10.1002/hyp.14444
- Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global‐scale models J. Jian et al. 10.1111/gcb.15795
- Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations A. Wolanin et al. 10.1016/j.rse.2019.03.002
- Do State‐Of‐The‐Art Atmospheric CO2 Inverse Models Capture Drought Impacts on the European Land Carbon Uptake? W. He et al. 10.1029/2022MS003150
- Future reversal of warming-enhanced vegetation productivity in the Northern Hemisphere Y. Zhang et al. 10.1038/s41558-022-01374-w
- Comparison of Phenology Estimated From Monthly Vegetation Indices and Solar-Induced Chlorophyll Fluorescence in China X. Wang et al. 10.3389/feart.2022.802763
- Upscaled diurnal cycles of land–atmosphere fluxes: a new global half-hourly data product P. Bodesheim et al. 10.5194/essd-10-1327-2018
- Implementation of Groundwater Lateral Flow and Human Water Regulation in CAS‐FGOALS‐g3 L. Wang et al. 10.1029/2019JD032289
- Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks G. Tramontana et al. 10.1111/gcb.15203
- Upscaling GOME-2 SIF from clear-sky instantaneous observations to all-sky sums leading to an improved SIF–GPP correlation J. Hu et al. 10.1016/j.agrformet.2021.108439
- Contrasting Performance of the Remotely-Derived GPP Products over Different Climate Zones across China Y. Chen et al. 10.3390/rs11161855
- Comparative Analysis of Two Machine Learning Algorithms in Predicting Site-Level Net Ecosystem Exchange in Major Biomes J. Liu et al. 10.3390/rs13122242
- A Scalable Earth Observations‐Based Decision Support System for Hydropower Planning in Africa A. Koppa et al. 10.1111/1752-1688.12914
- Inverse Determination of the Influence of Fire on Vegetation Carbon Turnover in the Pantropics J. Exbrayat et al. 10.1029/2018GB005925
- What is global photosynthesis? History, uncertainties and opportunities Y. Ryu et al. 10.1016/j.rse.2019.01.016
- Memory effects of climate and vegetation affecting net ecosystem CO2 fluxes in global forests S. Besnard et al. 10.1371/journal.pone.0211510
- On what scales can GOSAT flux inversions constrain anomalies in terrestrial ecosystems? B. Byrne et al. 10.5194/acp-19-13017-2019
- Bioenergy Crops for Low Warming Targets Require Half of the Present Agricultural Fertilizer Use W. Li et al. 10.1021/acs.est.1c02238
- Machine learning-based investigation of forest evapotranspiration, net ecosystem productivity, water use efficiency and their climate controls at meteorological station level H. Shi et al. 10.1016/j.jhydrol.2024.131811
- Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East‐West Divide of Temperate North America B. Byrne et al. 10.1029/2020GB006598
- Machine learning estimates of eddy covariance carbon flux in a scrub in the Mexican highland A. Guevara-Escobar et al. 10.5194/bg-18-367-2021
- Spatial Predictions and Associated Uncertainty of Annual Soil Respiration at the Global Scale D. Warner et al. 10.1029/2019GB006264
- Carbon–water flux coupling under progressive drought S. Boese et al. 10.5194/bg-16-2557-2019
- Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale W. Li et al. 10.5194/essd-12-789-2020
- Improving the Gross Primary Production Estimate by Merging and Downscaling Based on Deep Learning J. Lu et al. 10.3390/f14061201
- Different Satellite Products Revealing Variable Trends in Global Gross Primary Production Y. Bai et al. 10.1029/2022JG006918
- Aridity‐Dependent Land Surface Skin Temperature Biases in CMIP5/6 W. Wu & Z. Yang 10.1029/2022GL098952
- An abrupt shift in gross primary productivity over Eastern China-Mongolia and its inter-model diversity in land surface models D. Lee et al. 10.1038/s41598-023-49763-1
- Multi-sensor remote sensing for drought characterization: current status, opportunities and a roadmap for the future W. Jiao et al. 10.1016/j.rse.2021.112313
- Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity A. Bastos et al. 10.1126/sciadv.aba2724
- Peak growing season patterns and climate extremes-driven responses of gross primary production estimated by satellite and process based models over North America W. He et al. 10.1016/j.agrformet.2020.108292
- Modeling and Predicting Carbon and Water Fluxes Using Data-Driven Techniques in a Forest Ecosystem X. Dou & Y. Yang 10.3390/f8120498
- Correction to a Simple Biosphere Model 2 (SiB2) Simulation of Energy and Carbon Dioxide Fluxes over a Wheat Cropland in East China Using the Random Forest Model S. Zhang et al. 10.3390/atmos13122080
- Evaluating photosynthetic activity across Arctic-Boreal land cover types using solar-induced fluorescence R. Cheng et al. 10.1088/1748-9326/ac9dae
- Partitioning eddy covariance CO2 fluxes into ecosystem respiration and gross primary productivity through a new hybrid four sub-deep neural network H. Chen et al. 10.1016/j.agee.2023.108810
- Varying performance of eight evapotranspiration products with aridity and vegetation greenness across the globe H. Wang et al. 10.3389/fenvs.2023.1079520
- Terrestrial gross primary production: Using NIRV to scale from site to globe G. Badgley et al. 10.1111/gcb.14729
- Linking the complementary evaporation relationship with the Budyko framework for ungauged areas in Australia D. Kim et al. 10.5194/hess-26-5955-2022
- Narrow but robust advantages in two-big-leaf light use efficiency models over big-leaf light use efficiency models at ecosystem level S. Bao et al. 10.1016/j.agrformet.2022.109185
- Quantifying the impacts of land cover change on gross primary productivity globally A. Krause et al. 10.1038/s41598-022-23120-0
- Environmental control of land-atmosphere CO<sub>2</sub> fluxes from temperate ecosystems: a statistical approach based on homogenized time series from five land-use types V. Moreaux et al. 10.1080/16000889.2020.1784689
- Asymmetric responses of ecosystem productivity to rainfall anomalies vary inversely with mean annual rainfall over the conterminous United States A. Al‐Yaari et al. 10.1111/gcb.15345
- Eco‐evolutionary optimality as a means to improve vegetation and land‐surface models S. Harrison et al. 10.1111/nph.17558
- Imprints of evaporative conditions and vegetation type in diurnal temperature variations A. Panwar et al. 10.5194/hess-24-4923-2020
- Barium stable isotopes as a fingerprint of biological cycling in the Amazon River basin Q. Charbonnier et al. 10.5194/bg-17-5989-2020
- Environmental response characteristics of the carbon and water fluxes above complex urban surfaces of a subtropical megacity in China Y. Zhan et al. 10.1016/j.pce.2024.103681
- Impact of temperature and water availability on microwave-derived gross primary production I. Teubner et al. 10.5194/bg-18-3285-2021
- ERA-5 and ERA-Interim driven ISBA land surface model simulations: which one performs better? C. Albergel et al. 10.5194/hess-22-3515-2018
- Comparison of Regional Simulation of Biospheric CO2 Flux from the Updated Version of CarbonTracker Asia with FLUXCOM and Other Inversions over Asia S. Kenea et al. 10.3390/rs12010145
- A boreal forest model benchmarking dataset for North America: a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) B. Qu et al. 10.1088/1748-9326/ace376
- Global distribution of groundwater‐vegetation spatial covariation S. Koirala et al. 10.1002/2017GL072885
- Joint improvement on absorbed photosynthetically active radiation and intrinsic quantum yield efficiency algorithms in the P model betters the estimate of terrestrial gross primary productivity Z. Zhang et al. 10.1016/j.agrformet.2023.109883
- A Neural Network Model for Estimating Carbon Fluxes in Forest Ecosystems from Remote Sensing Data A. Rozanov & K. Gribanov 10.1134/S1024856023040152
- How the CMIP6 climate models project the historical terrestrial GPP in China C. Zhang et al. 10.1002/joc.7834
- Toward Robust Parameterizations in Ecosystem‐Level Photosynthesis Models S. Bao et al. 10.1029/2022MS003464
- Constraining global terrestrial gross primary productivity in a global carbon assimilation system with OCO-2 chlorophyll fluorescence data J. Wang et al. 10.1016/j.agrformet.2021.108424
- Understanding terrestrial water storage variations in northern latitudes across scales T. Trautmann et al. 10.5194/hess-22-4061-2018
- Three Decades of Gross Primary Production (GPP) in China: Variations, Trends, Attributions, and Prediction Inferred from Multiple Datasets and Time Series Modeling Y. Bo et al. 10.3390/rs14112564
- Improving the Estimation of Gross Primary Productivity across Global Biomes by Modeling Light Use Efficiency through Machine Learning D. Kong et al. 10.3390/rs15082086
- The spatial heterogeneity of the relationship between gross primary production and sun-induced chlorophyll fluorescence regulated by climate conditions during 2007–2018 Y. Wang et al. 10.1016/j.gecco.2021.e01721
- An Artificial Intelligence Approach to Predict Gross Primary Productivity in the Forests of South Korea Using Satellite Remote Sensing Data B. Lee et al. 10.3390/f11091000
- Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites H. Chu et al. 10.1016/j.agrformet.2021.108350
- Time‐Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity N. Linscheid et al. 10.1029/2021GL093285
- How well do light-use efficiency models capture large-scale drought impacts on vegetation productivity compared with data-driven estimates? Y. Lv et al. 10.1016/j.ecolind.2022.109739
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- New data‐driven estimation of terrestrial CO2 fluxes in Asia using a standardized database of eddy covariance measurements, remote sensing data, and support vector regression K. Ichii et al. 10.1002/2016JG003640
- A methodology to derive global maps of leaf traits using remote sensing and climate data Á. Moreno-Martínez et al. 10.1016/j.rse.2018.09.006
- No Proportional Increase of Terrestrial Gross Carbon Sequestration From the Greening Earth Y. Zhang et al. 10.1029/2018JG004917
- Can we replace observed forcing with weather generator in land surface modeling? Insights from long-term simulations at two contrasting boreal sites M. Alves et al. 10.1007/s00704-021-03615-y
- Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange Z. Fu et al. 10.1111/gcb.14731
- Modelling sun-induced fluorescence for improved evaluation of forest carbon flux (GPP): Case study of tropical deciduous forest, India S. Sinha et al. 10.1016/j.ecolmodel.2021.109552
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Short summary
We have evaluated 11 machine learning (ML) methods and two complementary drivers' setup to estimate the carbon dioxide (CO2) and energy exchanges between land ecosystems and atmosphere. Obtained results have shown high consistency among ML and high capability to estimate the spatial and seasonal variability of the target fluxes. The results were good for all the ecosystems, with limitations to the ones in the extreme environments (cold, hot) or less represented in the training data (tropics).
We have evaluated 11 machine learning (ML) methods and two complementary drivers' setup to...
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