29 citations as recorded by crossref.

1. Global Unsupervised Assessment of Multifrequency Vegetation Optical Depth Sensitivity to Vegetation Cover C. Olivares-Cabello et al. 10.1109/JSTARS.2022.3226001
2. Exploring the use of satellite observations of soil moisture, solar-induced chlorophyll fluorescence and vegetation optical depth to monitor droughts across India M. Likith et al. 10.1007/s12040-022-01848-7
3. Global ecosystem-scale plant hydraulic traits retrieved using model–data fusion Y. Liu et al. 10.5194/hess-25-2399-2021
4. Optimizing a backscatter forward operator using Sentinel-1 data over irrigated land S. Modanesi et al. 10.5194/hess-25-6283-2021
5. Soil moisture estimation in South Asia via assimilation of SMAP retrievals J. Ahmad et al. 10.5194/hess-26-2221-2022
6. Joint assimilation of satellite-based surface soil moisture and vegetation conditions into the Noah-MP land surface model Z. Heyvaert et al. 10.1016/j.srs.2024.100129
7. Pixel-level parameter optimization of a terrestrial biosphere model for improving estimation of carbon fluxes with an efficient model–data fusion method and satellite-derived LAI and GPP data R. Ma et al. 10.5194/gmd-15-6637-2022
8. Using soil moisture information to better understand and predict wildfire danger: a review of recent developments and outstanding questions E. Krueger et al. 10.1071/WF22056
9. Assessing the sensitivity of multi-frequency passive microwave vegetation optical depth to vegetation properties L. Schmidt et al. 10.5194/bg-20-1027-2023
10. Assimilation of passive microwave vegetation optical depth in LDAS-Monde: a case study over the continental USA A. Mucia et al. 10.5194/bg-19-2557-2022
11. An Agenda for Land Data Assimilation Priorities: Realizing the Promise of Terrestrial Water, Energy, and Vegetation Observations From Space S. Kumar et al. 10.1029/2022MS003259
12. Interconnected hydrologic extreme drivers and impacts depicted by remote sensing data assimilation T. Lahmers et al. 10.1038/s41598-023-30484-4
13. Constraining Plant Hydraulics With Microwave Radiometry in a Land Surface Model: Impacts of Temporal Resolution N. Holtzman et al. 10.1029/2023WR035481
14. Impact of temperature and water availability on microwave-derived gross primary production I. Teubner et al. 10.5194/bg-18-3285-2021
15. A consistent record of vegetation optical depth retrieved from the AMSR-E and AMSR2 X-band observations M. Wang et al. 10.1016/j.jag.2021.102609
16. 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
17. Bias-blind and bias-aware assimilation of leaf area index into the Noah-MP land surface model over Europe S. Scherrer et al. 10.5194/hess-27-4087-2023
18. Changes in land use enhance the sensitivity of tropical ecosystems to fire-climate extremes S. Kumar et al. 10.1038/s41598-022-05130-0
19. The joint assimilation of satellite observed LAI and soil moisture for the global root zone soil moisture production and its impact on land surface and ecosystem variables Y. Xu et al. 10.1016/j.agrformet.2024.110299
20. Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF‐Hydro System T. Lahmers et al. 10.1029/2021WR029867
21. Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP S. Modanesi et al. 10.5194/hess-26-4685-2022
22. Assimilation of ASCAT Radar Backscatter Coefficients over Southwestern France T. Corchia et al. 10.3390/rs15174258
23. Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication G. De Lannoy et al. 10.3389/frwa.2022.981745
24. Assimilation of Remotely Sensed Leaf Area Index Enhances the Estimation of Anthropogenic Irrigation Water Use W. Nie et al. 10.1029/2022MS003040
25. Impacts of Fully Coupling Land Surface and Flood Models on the Simulation of Large Wetlands' Water Dynamics: The Case of the Inner Niger Delta A. Getirana et al. 10.1029/2021MS002463
26. Assimilating ASCAT normalized backscatter and slope into the land surface model ISBA-A-gs using a Deep Neural Network as the observation operator: Case studies at ISMN stations in western Europe X. Shan et al. 10.1016/j.rse.2024.114167
27. An alternative AMSR2 vegetation optical depth for monitoring vegetation at large scales M. Wang et al. 10.1016/j.rse.2021.112556
28. The 2019–2020 Australian Drought and Bushfires Altered the Partitioning of Hydrological Fluxes S. Kumar et al. 10.1029/2020GL091411
29. Improving Dynamic Vegetation Modeling in Noah‐MP by Parameter Optimization and Data Assimilation Over China's Loess Plateau Z. Shu et al. 10.1029/2022JD036703