8 citations as recorded by crossref.

1. Unrecognised water limitation is a main source of uncertainty for models of terrestrial photosynthesis S. Biegel et al. https://doi.org/10.5194/bg-22-7455-2025
2. MCI GPP: ensembling a global model- and climate-independent gross primary productivity for 2001–2023 J. Pu et al. https://doi.org/10.1038/s41597-025-06218-8
3. Uncertainty Analysis of Gross Primary Production (GPP) Remote-Sensing Products and Its Influencing Factors in Southwest China Z. Ge et al. https://doi.org/10.3390/rs18050764
4. Constrained Carbon Partitioning: A Self‐Trained Physics‐Informed Machine Learning Model Refines GPP Estimates From Eddy Covariance Measurements S. Ranjbar et al. https://doi.org/10.1111/gcb.70886
5. Exploring the main driving factors of gross primary production in different climate zones of China using the XGBoost–SHAP model S. Na et al. https://doi.org/10.1016/j.jaridl.2026.06.001
6. Prithvi-EO-2.0: A Versatile Multitemporal Foundation Model for Earth Observation Applications D. Szwarcman et al. https://doi.org/10.1109/TGRS.2025.3642610
7. Flux Footprints: A Critical Link to Bridge Eddy‐Covariance Measurements With Models, Remote Sensing, and Other Observations H. Chu et al. https://doi.org/10.1111/gcb.70887
8. Comparison of Sentinel-2 and MODIS for estimating GPP along an ecosystem gradient in eastern Germany M. Sayeed et al. https://doi.org/10.1080/22797254.2026.2650340