46 citations as recorded by crossref.

1. Evaluation of leaf-level optical properties employed in land surface models T. Majasalmi & R. Bright https://doi.org/10.5194/gmd-12-3923-2019
2. Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes, CLM4.5(ED) R. Fisher et al. https://doi.org/10.5194/gmd-8-3593-2015
3. Canopy clumping index (CI): A review of methods, characteristics, and applications H. Fang https://doi.org/10.1016/j.agrformet.2021.108374
4. Glacial Amazonia at the canopy-scale: Using a biophysical model to understand forest robustness H. Sato & S. Cowling https://doi.org/10.1016/j.quascirev.2017.06.027
5. Climate change and disturbance interact to alter landscape reflectivity (albedo) in boreal forests across a large latitudinal gradient in Siberia E. Gustafson et al. https://doi.org/10.1016/j.scitotenv.2024.177043
6. Albedo climatology for European land surfaces retrieved from AVHRR data (1990–2014) and its spatial and temporal analysis from green‐up to vegetation senescence M. Sütterlin et al. https://doi.org/10.1002/2016JD024933
7. Reviews and syntheses: Flying the satellite into your model: on the role of observation operators in constraining models of the Earth system and the carbon cycle T. Kaminski & P. Mathieu https://doi.org/10.5194/bg-14-2343-2017
8. Influence of sun zenith angle on canopy clumping and the resulting impacts on photosynthesis R. Braghiere et al. https://doi.org/10.1016/j.agrformet.2020.108065
9. Accounting for canopy structure improves hyperspectral radiative transfer and sun-induced chlorophyll fluorescence representations in a new generation Earth System model R. Braghiere et al. https://doi.org/10.1016/j.rse.2021.112497
10. The role of remote sensing in process-scaling studies of managed forest ecosystems J. Masek et al. https://doi.org/10.1016/j.foreco.2015.05.032
11. Generating Long Time Series of High Spatiotemporal Resolution FPAR Images in the Remote Sensing Trend Surface Framework Y. Wang et al. https://doi.org/10.1109/TGRS.2021.3067913
12. Vegetation clumping modulates global photosynthesis through adjusting canopy light environment F. Li et al. https://doi.org/10.1111/gcb.16503
13. Assessment of JSBACHv4.30 as a land component of ICON-ESM-V1 in comparison to its predecessor JSBACHv3.2 of MPI-ESM1.2 R. Schneck et al. https://doi.org/10.5194/gmd-15-8581-2022
14. Multiparameter Estimation From Landsat Observations With Topographic Consideration H. Shi et al. https://doi.org/10.1109/TGRS.2021.3057377
15. The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America M. Longo et al. https://doi.org/10.5194/gmd-12-4347-2019
16. Underestimation of Global Photosynthesis in Earth System Models Due to Representation of Vegetation Structure R. Braghiere et al. https://doi.org/10.1029/2018GB006135
17. Estimation of FAPAR over Croplands Using MISR Data and the Earth Observation Land Data Assimilation System (EO-LDAS) M. Chernetskiy et al. https://doi.org/10.3390/rs9070656
18. Data-constrained modeling of terrestrial gross primary production over the Tibetan Plateau for 2003–2019 S. Chen et al. https://doi.org/10.1016/j.agrformet.2024.110129
19. An Optical–Thermal Surface–Atmosphere Radiative Transfer Model Coupling Framework With Topographic Effects H. Shi et al. https://doi.org/10.1109/TGRS.2020.3044061
20. The influence of 3D canopy structure on modelled photosynthesis M. Stretton et al. https://doi.org/10.1016/j.agrformet.2025.110437
21. Toward SI Traceability of a Monte Carlo Radiative Transfer Model in the Visible Range P. Jaanson et al. https://doi.org/10.1109/TGRS.2017.2761988
22. Fast matrix treatment of 3-D radiative transfer in vegetation canopies: SPARTACUS-Vegetation 1.1 R. Hogan et al. https://doi.org/10.5194/gmd-11-339-2018
23. Does day and night sampling reduce spurious correlation between canopy photosynthesis and ecosystem respiration? D. Baldocchi et al. https://doi.org/10.1016/j.agrformet.2015.03.010
24. Estimation of nadir clumping index (NCI) using airborne laser scanning data over global forest sites Y. Wu & H. Fang https://doi.org/10.1016/j.agrformet.2026.111369
25. Assessing Surface Solar Radiation Fluxes in the CMIP Ensembles A. Loew et al. https://doi.org/10.1175/JCLI-D-14-00503.1
26. Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance A. Shiklomanov et al. https://doi.org/10.5194/gmd-14-2603-2021
27. Seasonal variation of canopy vertical structural profiles measured at two temperate forests: intercomparison of tower, mast, crane, and UAV measurements H. Fang et al. https://doi.org/10.1007/s00468-024-02589-4
28. Forest summer albedo is sensitive to species and thinning: how should we account for this in Earth system models? J. Otto et al. https://doi.org/10.5194/bg-11-2411-2014
29. Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4 A. Martin et al. https://doi.org/10.5194/gmd-17-5705-2024
30. Drivers of shortwave radiation fluxes in Arctic tundra across scales I. Juszak et al. https://doi.org/10.1016/j.rse.2017.02.017
31. A Scaling-Based Method for the Rapid Retrieval of FPAR From Fine-Resolution Satellite Data in the Remote-Sensing Trend-Surface Framework Y. Wang et al. https://doi.org/10.1109/TGRS.2020.2978884
32. Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0 G. Schürmann et al. https://doi.org/10.5194/gmd-9-2999-2016
33. Mimicking biochar-albedo feedback in complex Mediterranean agricultural landscapes E. Bozzi et al. https://doi.org/10.1088/1748-9326/10/8/084014
34. A New Global fAPAR and LAI Dataset Derived from Optimal Albedo Estimates: Comparison with MODIS Products M. Disney et al. https://doi.org/10.3390/rs8040275
35. Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO2 T. Mauritsen et al. https://doi.org/10.1029/2018MS001400
36. Generalized Fine-Resolution FPAR Estimation Using Google Earth Engine: Random Forest or Multiple Linear Regression Y. Wang et al. https://doi.org/10.1109/JSTARS.2022.3230456
37. Efficient Emulation of Radiative Transfer Codes Using Gaussian Processes and Application to Land Surface Parameter Inferences J. Gómez-Dans et al. https://doi.org/10.3390/rs8020119
38. How does leaf functional diversity affect the light environment in forest canopies? An in-silico biodiversity experiment E. Plekhanova et al. https://doi.org/10.1016/j.ecolmodel.2020.109394
39. The PROLIB leaf radiative transfer model: Simulation of the dorsiventrality of leaves from visible to mid-wave infrared H. Shi et al. https://doi.org/10.1016/j.rse.2024.114140
40. Reexamination and further development of two‐stream canopy radiative transfer models for global land modeling H. Yuan et al. https://doi.org/10.1002/2016MS000773
41. The Importance of Hyperspectral Soil Albedo Information for Improving Earth System Model Projections R. Braghiere et al. https://doi.org/10.1029/2023AV000910
42. Solar-induced chlorophyll fluorescence from the Geostationary Carbon Cycle Observatory (GeoCarb): An extensive simulation study P. Somkuti et al. https://doi.org/10.1016/j.rse.2021.112565
43. An Overview of Global Leaf Area Index (LAI): Methods, Products, Validation, and Applications H. Fang et al. https://doi.org/10.1029/2018RG000608
44. Strong Local Evaporative Cooling Over Land Due to Atmospheric Aerosols T. Chakraborty et al. https://doi.org/10.1029/2021MS002491
45. Observation and integrated Earth-system science: A roadmap for 2016–2025 A. Simmons et al. https://doi.org/10.1016/j.asr.2016.03.008
46. Improved representation of plant physiology in the JULES-vn5.6 land surface model: photosynthesis, stomatal conductance and thermal acclimation R. Oliver et al. https://doi.org/10.5194/gmd-15-5567-2022