67 citations as recorded by crossref.

1. A convolutional neural network for spatial downscaling of satellite-based solar-induced chlorophyll fluorescence (SIFnet) J. Gensheimer et al. 10.5194/bg-19-1777-2022
2. An empirical model for estimating daily atmospheric column-averaged CO2 concentration above São Paulo state, Brazil L. da Costa et al. 10.1186/s13021-022-00209-7
3. Generating high-resolution total canopy SIF emission from TROPOMI data: Algorithm and application Z. Zhang et al. 10.1016/j.rse.2023.113699
4. Global Analysis of the Relationship between Reconstructed Solar-Induced Chlorophyll Fluorescence (SIF) and Gross Primary Production (GPP) H. Gao et al. 10.3390/rs13142824
5. Effects of Low Temperature on the Relationship between Solar-Induced Chlorophyll Fluorescence and Gross Primary Productivity across Different Plant Function Types J. Chen et al. 10.3390/rs14153716
6. Uniform upscaling techniques for eddy covariance FLUXes (UFLUX) S. Zhu et al. 10.1080/01431161.2024.2312266
7. Downscaling Solar-Induced Chlorophyll Fluorescence Based on Convolutional Neural Network Method to Monitor Agricultural Drought Z. Zhang et al. 10.1109/TGRS.2020.2999371
8. A unified vegetation index for quantifying the terrestrial biosphere G. Camps-Valls et al. 10.1126/sciadv.abc7447
9. A Spatially Downscaled TROPOMI SIF Product at 0.005° Resolution With Bias Correction J. Hu et al. 10.1109/JSTARS.2024.3433371
10. A Machine Learning Approach for Mapping Chlorophyll Fluorescence at Inland Wetlands M. Bartold & M. Kluczek 10.3390/rs15092392
11. Estimation of global GPP from GOME-2 and OCO-2 SIF by considering the dynamic variations of GPP-SIF relationship J. Bai et al. 10.1016/j.agrformet.2022.109180
12. A Spatial Downscaling Method for Solar-Induced Chlorophyll Fluorescence Product Using Random Forest Regression and Drought Monitoring in Henan Province Z. Zhang et al. 10.3390/rs16060963
13. Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics X. Wang et al. 10.1016/j.rse.2021.112858
14. An evaluation of the response of vegetation greenness, moisture, fluorescence, and temperature-based remote sensing indicators to drought stress H. Sun et al. 10.1016/j.jhydrol.2023.130125
15. Exploring the Potential of Solar-Induced Chlorophyll Fluorescence Monitoring Drought-Induced Net Primary Productivity Dynamics in the Huang-Huai-Hai Plain Based on the SIF/NPP Ratio Y. Wang et al. 10.3390/rs15133276
16. Sensitivity of remote sensing-based vegetation proxies to climate and sea surface temperature variabilities in Australia and parts of Southeast Asia S. Arjasakusuma et al. 10.1080/01431161.2020.1782509
17. Assessing the contribution of understory sun-induced chlorophyll fluorescence through 3-D radiative transfer modelling and field data A. Hornero et al. 10.1016/j.rse.2020.112195
18. An improved spatially downscaled solar-induced chlorophyll fluorescence dataset from the TROPOMI product S. Chen et al. 10.1038/s41597-024-04325-6
19. An exploration of solar-induced chlorophyll fluorescence (SIF) factors simulated by SCOPE for capturing GPP across vegetation types S. Yang et al. 10.1016/j.ecolmodel.2022.110079
20. Contrasting responses of vegetation productivity to intraseasonal rainfall in Earth system models B. Harris et al. 10.5194/esd-15-1019-2024
21. A model for urban biogenic CO2 fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1) D. Wu et al. 10.5194/gmd-14-3633-2021
22. Modeling of winter wheat yield prediction based on solar-induced chlorophyll fluorescence by machine learning methods M. Zheng et al. 10.1080/22797254.2025.2455940
23. Long-term dynamics of peak photosynthesis timing and environmental controls in the Tibetan Plateau monitored by satellite solar-induced chlorophyll fluorescence Z. Tu et al. 10.1080/17538947.2023.2300311
24. UFLUX-GPP: A Cost-Effective Framework for Quantifying Daily Terrestrial Ecosystem Carbon Uptake Using Satellite Data S. Zhu et al. 10.1109/TGRS.2024.3439333
25. Full-coverage 250 m monthly aerosol optical depth dataset (2000–2019) amended with environmental covariates by an ensemble machine learning model over arid and semi-arid areas, NW China X. Chen et al. 10.5194/essd-14-5233-2022
26. Spatial Statistical Prediction of Solar-Induced Chlorophyll Fluorescence (SIF) from Multivariate OCO-2 Data J. Jacobson et al. 10.3390/rs15164038
27. Global patterns of water storage in the rooting zones of vegetation B. Stocker et al. 10.1038/s41561-023-01125-2
28. Satellite-Based Observations Reveal the Altitude-Dependent Patterns of SIFyield and Its Sensitivity to Ambient Temperature in Tibetan Meadows R. Chen et al. 10.3390/rs13071400
29. Ecophysiological variables retrieval and early stress detection: insights from a synthetic spatial scaling exercise J. Pacheco-Labrador et al. 10.1080/01431161.2024.2414435
30. Explainable Machine Learning Confirms the Global Terrestrial CO2 Fertilization Effect From Space S. Zhu et al. 10.1109/LGRS.2023.3298373
31. An improved downscaled sun-induced chlorophyll fluorescence (DSIF) product of GOME-2 dataset Y. Ma et al. 10.1080/22797254.2022.2028579
32. Using enhanced vegetation index and land surface temperature to reconstruct the solar-induced chlorophyll fluorescence of forests and grasslands across latitude and phenology P. Zhang et al. 10.3389/ffgc.2023.1257287
33. Solar-Induced Chlorophyll Fluorescence (SIF): Towards a Better Understanding of Vegetation Dynamics and Carbon Uptake in Arctic-Boreal Ecosystems R. Cheng 10.1007/s40641-024-00194-8
34. A long-term reconstructed TROPOMI solar-induced fluorescence dataset using machine learning algorithms X. Chen et al. 10.1038/s41597-022-01520-1
35. Estimating of chlorophyll fluorescence parameter Fv/Fm for plant stress detection at peatlands under Ramsar Convention with Sentinel-2 satellite imagery M. Bartold & M. Kluczek 10.1016/j.ecoinf.2024.102603
36. Increase in gross primary production of boreal forests balanced out by increase in ecosystem respiration J. Pulliainen et al. 10.1016/j.rse.2024.114376
37. A Comprehensive Review of Crop Yield Prediction Using Machine Learning Approaches With Special Emphasis on Palm Oil Yield Prediction M. Rashid et al. 10.1109/ACCESS.2021.3075159
38. Can upscaling ground nadir SIF to eddy covariance footprint improve the relationship between SIF and GPP in croplands? G. Wu et al. 10.1016/j.agrformet.2023.109532
39. Challenges for drought assessment in the Mediterranean region under future climate scenarios Y. Tramblay et al. 10.1016/j.earscirev.2020.103348
40. A Method to Weaken Cloud Interference in Solar-Induced Chlorophyll Fluorescence (SIF) Reconstruction by Using Satellite VOD Observations J. Ding et al. 10.1109/JSTARS.2025.3576504
41. A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band X. Liu et al. 10.1016/j.rse.2022.113341
42. A Geographically Random Machine Learning Model for GOME-2 Global Seamless Sun-Induced Chlorophyll Fluorescence Downscaling Products With High Spatiotemporal Resolution S. He et al. 10.1109/TGRS.2025.3552678
43. Flash drought early warning based on the trajectory of solar-induced chlorophyll fluorescence K. Mohammadi et al. 10.1073/pnas.2202767119
44. 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
45. Can the MODIS Data Achieve the Downscaling of GOME-2 SIF? Validation of Data from China H. Si et al. 10.3390/su15075920
46. 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
47. Downscaling Solar-Induced Chlorophyll Fluorescence to a 0.05° Monthly Product Using AVHRR Data in East Asia (1995–2003) Y. Jin et al. 10.1109/JSTARS.2024.3369332
48. The Negative Impact of Excessive Moisture Contributes to the Seasonal Dynamics of Photosynthesis in Amazon Moist Forests R. Chen et al. 10.1029/2021EF002306
49. Soil organic and inorganic carbon pools in the Loess Plateau: New estimation, change and trade-offs J. Wu et al. 10.1016/j.gloplacha.2025.104951
50. An Operational Downscaling Method of Solar-Induced Chlorophyll Fluorescence (SIF) for Regional Drought Monitoring Z. Hong et al. 10.3390/agriculture12040547
51. The reconstructed solar-induced chlorophyll fluorescence dataset reveals the almost ubiquitous close relationship between vegetation transpiration and solar-induced chlorophyll fluorescence R. Wang & J. Zheng 10.1016/j.jhydrol.2024.131883
52. Importance of the legacy effect for assessing spatiotemporal correspondence between interannual tree-ring width and remote sensing products in the Sierra Nevada C. Wong et al. 10.1016/j.rse.2021.112635
53. Exploring the Potential of Spatially Downscaled Solar-Induced Chlorophyll Fluorescence to Monitor Drought Effects on Gross Primary Production in Winter Wheat Q. Shen et al. 10.1109/JSTARS.2022.3148393
54. Spatial Downscaling of Vegetation Productivity in the Forest From Deep Learning T. Yu et al. 10.1109/ACCESS.2022.3210218
55. Downscaled Satellite Solar-Induced Chlorophyll Fluorescence Detects the Early Response of Sugarcane to Drought Stress in a Major Sugarcane-Planting Region of China N. Yang et al. 10.3390/rs15163937
56. Multi-Feature Driver Variable Fusion Downscaling TROPOMI Solar-Induced Chlorophyll Fluorescence Approach J. Fan et al. 10.3390/agronomy15010133
57. A Reconstructed Global Daily Seamless SIF Product at 0.05 Degree Resolution Based on TROPOMI, MODIS and ERA5 Data J. Hu et al. 10.3390/rs14061504
58. Sun-induced fluorescence as a proxy for primary productivity across vegetation types and climates M. Pickering et al. 10.5194/bg-19-4833-2022
59. 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
60. Stronger response of vegetation photosynthesis to climate change than greenness in pan-Arctic region: First evidence from SIF satellite observations M. Jiang et al. 10.1016/j.ecoinf.2025.103312
61. Downscaling solar-induced chlorophyll fluorescence for field-scale cotton yield estimation by a two-step convolutional neural network X. Kang et al. 10.1016/j.compag.2022.107260
62. Integrating multi-source datasets in exploring the covariation of gross primary productivity (GPP) and solar-induced chlorophyll fluorescence (SIF) at an Indian tropical forest flux site M. Hari et al. 10.1007/s12665-024-11528-y
63. Improved GPP upscaling from instantaneous measurements to daily sums using the light-use-efficiency-based model R. Chen et al. 10.1016/j.agrformet.2025.110529
64. Temporally corrected long-term satellite solar-induced fluorescence leads to improved estimation of global trends in vegetation photosynthesis during 1995–2018 S. Wang et al. 10.1016/j.isprsjprs.2022.10.018
65. Response of Vegetation Photosynthesis to the 2022 Drought in Yangtze River Basin by Diurnal Orbiting Carbon Observatory-2/3 Satellite Observations Z. Deng et al. 10.34133/remotesensing.0445
66. Forecasting of Fine-Grained SIF of OCO-2 Using Multi-source Data and AI-Based Techniques S. Pais et al. 10.1007/s12524-024-02097-5
67. Generation of a Global Spatially Continuous TanSat Solar-Induced Chlorophyll Fluorescence Product by Considering the Impact of the Solar Radiation Intensity Y. Ma et al. 10.3390/rs12132167