272 citations as recorded by crossref.

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2. Deep Learned Process Parameterizations Provide Better Representations of Turbulent Heat Fluxes in Hydrologic Models A. Bennett & B. Nijssen 10.1029/2020WR029328
3. 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
4. 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
5. Earth system data cubes unravel global multivariate dynamics M. Mahecha et al. 10.5194/esd-11-201-2020
6. 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
7. 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
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9. 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
10. Satellite Observations of the Contrasting Response of Trees and Grasses to Variations in Water Availability S. Walther et al. 10.1029/2018GL080535
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14. 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
15. Critical Soil Moisture Derived From Satellite Observations Over Europe J. Denissen et al. 10.1029/2019JD031672
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19. Rapid recovery of net ecosystem production in a semi-arid woodland after a wildfire Q. Sun et al. 10.1016/j.agrformet.2020.108099
20. 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
21. Response of vegetation carbon uptake to snow-induced phenological and physiological changes across temperate China S. Chen et al. 10.1016/j.scitotenv.2019.07.222
22. A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks Y. Zhang et al. 10.5194/bg-15-5779-2018
23. Estimation of Global Grassland Net Ecosystem Carbon Exchange Using a Model Tree Ensemble Approach W. Liang et al. 10.1029/2019JG005034
24. Carbon fluxes and environmental controls across different alpine grassland types on the Tibetan Plateau Y. Wang et al. 10.1016/j.agrformet.2021.108694
25. Studying the impact of biomass burning aerosol radiative and climate effects on the Amazon rainforest productivity with an Earth system model F. Malavelle et al. 10.5194/acp-19-1301-2019
26. Deep learning and process understanding for data-driven Earth system science M. Reichstein et al. 10.1038/s41586-019-0912-1
27. Global Estimates of Marine Gross Primary Production Based on Machine Learning Upscaling of Field Observations Y. Huang et al. 10.1029/2020GB006718
28. The influence of atmospheric intraseasonal oscillations on terrestrial biospheric CO2 fluxes in Southeast China Forest J. Li et al. 10.1007/s00382-021-05702-2
29. 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
30. Remote sensing of the terrestrial carbon cycle: A review of advances over 50 years J. Xiao et al. 10.1016/j.rse.2019.111383
31. Regional-scale data assimilation with the Spatially Explicit Individual-based Dynamic Global Vegetation Model (SEIB-DGVM) over Siberia H. Arakida et al. 10.1186/s40645-021-00443-6
32. 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
33. VODCA2GPP – a new, global, long-term (1988–2020) gross primary production dataset from microwave remote sensing B. Wild et al. 10.5194/essd-14-1063-2022
34. High‐Resolution Global Contiguous SIF of OCO‐2 L. Yu et al. 10.1029/2018GL081109
35. Coupled estimation of 500 m and 8-day resolution global evapotranspiration and gross primary production in 2002–2017 Y. Zhang et al. 10.1016/j.rse.2018.12.031
36. Impact of Aerosols From Urban and Shipping Emission Sources on Terrestrial Carbon Uptake and Evapotranspiration: A Case Study in East Asia M. Huang et al. 10.1029/2019JD030818
37. 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
38. Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020) J. Liu et al. 10.5194/essd-13-299-2021
39. From Canopy‐Leaving to Total Canopy Far‐Red Fluorescence Emission for Remote Sensing of Photosynthesis: First Results From TROPOMI Z. Zhang et al. 10.1029/2019GL084832
40. Responding time scales of vegetation production to extreme droughts over China Y. Deng et al. 10.1016/j.ecolind.2022.108630
41. Can we trust remote sensing evapotranspiration products over Africa? I. Weerasinghe et al. 10.5194/hess-24-1565-2020
42. Isolating the Impacts of Land Use/Cover Change and Climate Change on the GPP in the Heihe River Basin of China N. You et al. 10.1029/2020JG005734
43. 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
44. Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling M. Barnes et al. 10.1038/s43247-021-00308-2
45. Evaluating GPP and Respiration Estimates Over Northern Midlatitude Ecosystems Using Solar-Induced Fluorescence and Atmospheric CO2 Measurements B. Byrne et al. 10.1029/2018JG004472
46. Schätzung der Verdunstung mithilfe von Machine- und Deep Learning-Methoden C. Brenner et al. 10.1007/s00506-021-00768-y
47. Machine learning information fusion in Earth observation: A comprehensive review of methods, applications and data sources S. Salcedo-Sanz et al. 10.1016/j.inffus.2020.07.004
48. Evolution of light use efficiency models: Improvement, uncertainties, and implications Y. Pei et al. 10.1016/j.agrformet.2022.108905
49. Changes in productivity and carbon storage of grasslands in China under future global warming scenarios of 1.5°C and 2°C Z. Wang et al. 10.1093/jpe/rtz024
50. Predicting carbon and water vapor fluxes using machine learning and novel feature ranking algorithms X. Cui et al. 10.1016/j.scitotenv.2021.145130
51. Accounting for forest age in the tile-based dynamic global vegetation model JSBACH4 (4.20p7; git feature/forests) – a land surface model for the ICON-ESM J. Nabel et al. 10.5194/gmd-13-185-2020
52. 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
53. The impact of indicator selection on assessment of global greening B. Qiu et al. 10.1080/15481603.2021.1879494
54. A global moderate resolution dataset of gross primary production of vegetation for 2000–2016 Y. Zhang et al. 10.1038/sdata.2017.165
55. 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
56. Estimating Forest Carbon Fluxes Using Machine Learning Techniques Based on Eddy Covariance Measurements X. Dou et al. 10.3390/su10010203
57. 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
58. CO 2 exchange and evapotranspiration across dryland ecosystems of southwestern North America J. Biederman et al. 10.1111/gcb.13686
59. 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
60. Impacts of extreme summers on European ecosystems: a comparative analysis of 2003, 2010 and 2018 A. Bastos et al. 10.1098/rstb.2019.0507
61. Improving CLM5.0 Biomass and Carbon Exchange Across the Western United States Using a Data Assimilation System B. Raczka et al. 10.1029/2020MS002421
62. 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
63. Estimation of China’s terrestrial ecosystem carbon sink: Methods, progress and prospects S. Piao et al. 10.1007/s11430-021-9892-6
64. Validation of drought indices using environmental indicators: streamflow and carbon flux data U. Bhuyan-Erhardt et al. 10.1016/j.agrformet.2018.11.016
65. 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
66. 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
67. 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
68. Kernel methods and their derivatives: Concept and perspectives for the earth system sciences J. Johnson et al. 10.1371/journal.pone.0235885
69. Global sensitivities of forest carbon changes to environmental conditions S. Besnard et al. 10.1111/gcb.15877
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72. Gaussianizing the Earth: Multidimensional information measures for Earth data analysis J. Johnson et al. 10.1109/MGRS.2021.3066260
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74. Simulating Erosion‐Induced Soil and Carbon Delivery From Uplands to Rivers in a Global Land Surface Model H. Zhang et al. 10.1029/2020MS002121
75. Large loss of CO2 in winter observed across the northern permafrost region S. Natali et al. 10.1038/s41558-019-0592-8
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78. 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
79. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data G. Pastorello et al. 10.1038/s41597-020-0534-3
80. Quantifying the effect of forest age in annual net forest carbon balance S. Besnard et al. 10.1088/1748-9326/aaeaeb
81. Application of machine-learning methods in forest ecology: recent progress and future challenges Z. Liu et al. 10.1139/er-2018-0034
82. 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
83. 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
84. Observational Constraints on the Response of High‐Latitude Northern Forests to Warming J. Liu et al. 10.1029/2020AV000228
85. Contrasting and interacting changes in simulated spring and summer carbon cycle extremes in European ecosystems S. Sippel et al. 10.1088/1748-9326/aa7398
86. 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
87. The global contribution of roots to total soil respiration J. Jian et al. 10.1111/geb.13454
88. Assimilation of Earth Observation Data Over Cropland and Grassland Sites into a Simple GPP Model M. Meroni et al. 10.3390/rs11070749
89. 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
90. 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
91. 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
92. Upscaling Net Ecosystem Exchange Over Heterogeneous Landscapes With Machine Learning O. Reitz et al. 10.1029/2020JG005814
93. Validation of terrestrial biogeochemistry in CMIP6 Earth system models: a review L. Spafford & A. MacDougall 10.5194/gmd-14-5863-2021
94. Inferring causal relations from observational long-term carbon and water fluxes records E. Díaz et al. 10.1038/s41598-022-05377-7
95. 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
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97. Seasonal biological carryover dominates northern vegetation growth X. Lian et al. 10.1038/s41467-021-21223-2
98. Estimating the Net Ecosystem Exchange at Global FLUXNET Sites Using a Random Forest Model N. Huang et al. 10.1109/JSTARS.2021.3114190
99. Physics‐Constrained Machine Learning of Evapotranspiration W. Zhao et al. 10.1029/2019GL085291
100. Ground‐Based Multiangle Solar‐Induced Chlorophyll Fluorescence Observation and Angular Normalization for Assessing Crop Productivity Q. Zhang et al. 10.1029/2020JG006082
101. 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
102. Assimilation of vegetation optical depth retrievals from passive microwave radiometry S. Kumar et al. 10.5194/hess-24-3431-2020
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104. A Review of Machine Learning Applications in Land Surface Modeling S. Pal & P. Sharma 10.3390/earth2010011
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109. 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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114. 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
115. Revisiting the choice of the driving temperature for eddy covariance CO2 flux partitioning G. Wohlfahrt & M. Galvagno 10.1016/j.agrformet.2017.02.012
116. Increasing impact of warm droughts on northern ecosystem productivity over recent decades D. Gampe et al. 10.1038/s41558-021-01112-8
117. 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
118. 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
119. Climate‐Driven Variability and Trends in Plant Productivity Over Recent Decades Based on Three Global Products M. O'Sullivan et al. 10.1029/2020GB006613
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126. 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
127. Evaluating global ecosystem water use efficiency response to drought based on multi-model analysis S. Yang et al. 10.1016/j.scitotenv.2021.146356
128. Improved Constraints on Northern Extratropical CO 2 Fluxes Obtained by Combining Surface‐Based and Space‐Based Atmospheric CO 2 Measurements B. Byrne et al. 10.1029/2019JD032029
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130. The FLUXCOM ensemble of global land-atmosphere energy fluxes M. Jung et al. 10.1038/s41597-019-0076-8
131. A decreasing carbon allocation to belowground autotrophic respiration in global forest ecosystems X. Tang et al. 10.1016/j.scitotenv.2021.149273
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135. Partitioning Net Ecosystem Exchange (NEE) of CO 2 Using Solar‐Induced Chlorophyll Fluorescence (SIF) O. Kira et al. 10.1029/2020GL091247
136. Foliage Senescence as a Key Parameter for Modeling Gross Primary Productivity in a Mediterranean Shrubland A. Cueva et al. 10.1029/2020JG005839
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144. An Ecosystem-Scale Flux Measurement Strategy to Assess Natural Climate Solutions K. Hemes et al. 10.1021/acs.est.0c06421
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147. Cropland Carbon Uptake Delayed and Reduced by 2019 Midwest Floods Y. Yin et al. 10.1029/2019AV000140
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