97 citations as recorded by crossref.

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6. Uncovering Dryland Woody Dynamics Using Optical, Microwave, and Field Data—Prolonged Above-Average Rainfall Paradoxically Contributes to Woody Plant Die-Off in the Western Sahel P. Bernardino et al. 10.3390/rs12142332
7. Retrievals of soil moisture and vegetation optical depth using a multi-channel collaborative algorithm T. Zhao et al. 10.1016/j.rse.2021.112321
8. Reappraisal of SMAP inversion algorithms for soil moisture and vegetation optical depth L. Gao et al. 10.1016/j.rse.2021.112627
9. Large loss and rapid recovery of vegetation cover and aboveground biomass over forest areas in Australia during 2019–2020 Y. Qin et al. 10.1016/j.rse.2022.113087
10. Mapping global drought-induced forest mortality based on multiple satellite vegetation optical depth data X. Zhang et al. 10.1016/j.rse.2024.114406
11. 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
12. SMOS-IC data record of soil moisture and L-VOD: Historical development, applications and perspectives J. Wigneron et al. 10.1016/j.rse.2020.112238
13. Parameterization of Vegetation Scattering Albedo in the Tau-Omega Model for Soil Moisture Retrieval on Croplands C. Park et al. 10.3390/rs12182939
14. Surface‐driven amplification of Madden–Julian oscillation circulation anomalies across East Africa and its influence on the Turkana jet J. Talib et al. 10.1002/qj.4487
15. Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon Y. Qin et al. 10.1038/s41558-021-01026-5
16. Evaluation of the Sensitivity of SMOS L-VOD to Forest Above-Ground Biomass at Global Scale A. Mialon et al. 10.3390/rs12091450
17. A map of African humid tropical forest aboveground biomass derived from management inventories P. Ploton et al. 10.1038/s41597-020-0561-0
18. Assessing Model Predictions of Carbon Dynamics in Global Drylands D. Fawcett et al. 10.3389/fenvs.2022.790200
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20. Soil dielectric characterization during freeze–thaw transitions using L-band coaxial and soil moisture probes A. Mavrovic et al. 10.5194/hess-25-1117-2021
21. An alternative AMSR2 vegetation optical depth for monitoring vegetation at large scales M. Wang et al. 10.1016/j.rse.2021.112556
22. Sensitivity of L-band vegetation optical depth to carbon stocks in tropical forests: a comparison to higher frequencies and optical indices D. Chaparro et al. 10.1016/j.rse.2019.111303
23. Monitoring post-fire recovery of various vegetation biomes using multi-wavelength satellite remote sensing E. Bousquet et al. 10.5194/bg-19-3317-2022
24. A multi-temporal and multi-angular approach for systematically retrieving soil moisture and vegetation optical depth from SMOS data Y. Bai et al. 10.1016/j.rse.2022.113190
25. Estimating Aboveground Forest Biomass Using Radar Methods I. Babiy et al. 10.1134/S1995425522050031
26. Variations of carbon allocation and turnover time across tropical forests H. Yang et al. 10.1111/geb.13302
27. Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non‐forest ecosystems A. Cunliffe et al. 10.1002/rse2.228
28. Estimating leaf moisture content at global scale from passive microwave satellite observations of vegetation optical depth M. Forkel et al. 10.5194/hess-27-39-2023
29. Characterizing natural variability in complex hydrological systems using passive microwave-based climate data records: a case study for the Okavango Delta R. van der Schalie et al. 10.5194/hess-26-3611-2022
30. A new global C-band vegetation optical depth product from ASCAT: Description, evaluation, and inter-comparison X. Liu et al. 10.1016/j.rse.2023.113850
31. Mean European Carbon Sink Over 2010–2015 Estimated by Simultaneous Assimilation of Atmospheric CO2, Soil Moisture, and Vegetation Optical Depth M. Scholze et al. 10.1029/2019GL085725
32. Daily estimation of gross primary production under all sky using a light use efficiency model coupled with satellite passive microwave measurements Y. Wang et al. 10.1016/j.rse.2021.112721
33. Monitoring tropical forests under a functional perspective with satellite‐based vegetation optical depth G. Vaglio Laurin et al. 10.1111/gcb.15072
34. Above-Ground Biomass Retrieval over Tropical Forests: A Novel GNSS-R Approach with CyGNSS H. Carreno-Luengo et al. 10.3390/rs12091368
35. Evaluating pulse-reserve characteristics of Soil-Plant continuum in India using remote sensing S. Anoop et al. 10.1016/j.jhydrol.2024.130913
36. Global L-band equivalent AI-based vegetation optical depth dataset O. Skulovich et al. 10.1038/s41597-024-03810-2
37. Global increase in biomass carbon stock dominated by growth of northern young forests over past decade H. Yang et al. 10.1038/s41561-023-01274-4
38. Portable L-Band Radiometer (PoLRa): Design and Characterization D. Houtz et al. 10.3390/rs12172780
39. Estimating Aboveground Carbon Dynamic of China Using Optical and Microwave Remote-Sensing Datasets from 2013 to 2019 Z. Chang et al. 10.34133/remotesensing.0005
40. Changes in Biomass Turnover Times in Tropical Forests and Their Environmental Drivers From 2001 to 2012 J. Wang et al. 10.1029/2020EF001655
41. Soil Moisture and Sea Surface Salinity Derived from Satellite-Borne Sensors J. Boutin et al. 10.1007/s10712-023-09798-5
42. Evaluation of optical and microwave-derived vegetation indices for monitoring aboveground biomass over China Z. Chang et al. 10.1080/10095020.2024.2311858
43. Global estimates of L-band vegetation optical depth and soil permittivity of snow-covered boreal forests and permafrost landscape using SMAP satellite data D. Kumawat et al. 10.1016/j.rse.2024.114145
44. Recent divergence in the contributions of tropical and boreal forests to the terrestrial carbon sink T. Tagesson et al. 10.1038/s41559-019-1090-0
45. Influence of Vegetation Height, Plant Area Index, and Forest Intactness on SMOS L-VOD, for Different Seasons and Latitude Ranges C. Vittucci et al. 10.1109/TGRS.2023.3299529
46. Influence of surface water variations on VOD and biomass estimates from passive microwave sensors E. Bousquet et al. 10.1016/j.rse.2021.112345
47. The global long-term microwave Vegetation Optical Depth Climate Archive (VODCA) L. Moesinger et al. 10.5194/essd-12-177-2020
48. The first global soil moisture and vegetation optical depth product retrieved from fused SMOS and SMAP L-band observations X. Li et al. 10.1016/j.rse.2022.113272
49. Toward a More Robust Estimation of Forest Biomass Carbon Stock and Carbon Sink in Mountainous Region: A Case Study in Tibet, China G. Lyu et al. 10.3390/rs16091481
50. Analysis of Vegetation Optical Depth and Soil Moisture Retrieved by SMOS Over Tropical Forests C. Vittucci et al. 10.1109/LGRS.2018.2878359
51. Global-scale biomass estimation based on machine learning and deep learning methods S. Talebiesfandarani & A. Shamsoddini 10.1016/j.rsase.2022.100868
52. Reliability of using vegetation optical depth for estimating decadal and interannual carbon dynamics Y. Dou et al. 10.1016/j.rse.2022.113390
53. First mapping of polarization-dependent vegetation optical depth and soil moisture from SMAP L-band radiometry Z. Peng et al. 10.1016/j.rse.2023.113970
54. First assessment of optical and microwave remotely sensed vegetation proxies in monitoring aboveground carbon in tropical Asia T. Cui et al. 10.1016/j.rse.2023.113619
55. Global-scale assessment and inter-comparison of recently developed/reprocessed microwave satellite vegetation optical depth products X. Li et al. 10.1016/j.rse.2020.112208
56. 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
57. Asymmetric responses of ecosystem productivity to rainfall anomalies vary inversely with mean annual rainfall over the conterminous United States A. Al‐Yaari et al. 10.1111/gcb.15345
58. A UGV-Based Forest Vegetation Optical Depth Mapping Using GNSS Signals A. Ghosh et al. 10.1109/JSTARS.2024.3365798
59. Forest management in southern China generates short term extensive carbon sequestration X. Tong et al. 10.1038/s41467-019-13798-8
60. Integrating satellite-based passive microwave and optically sensed observations to evaluating the spatio-temporal dynamics of vegetation health in the red soil regions of southern China Q. Yang et al. 10.1080/15481603.2021.2023841
61. Satellite-observed pantropical carbon dynamics L. Fan et al. 10.1038/s41477-019-0478-9
62. Quantitative Assessment of Satellite L-Band Vegetation Optical Depth in the U.S. Corn Belt K. Togliatti et al. 10.1109/LGRS.2020.3034174
63. Vegetation optical depth at L-band and above ground biomass in the tropical range: Evaluating their relationships at continental and regional scales C. Vittucci et al. 10.1016/j.jag.2019.01.006
64. Above-Ground Biomass Estimation Based on Multi-Angular L-Band Measurements of Brightness Temperatures J. Salazar-Neira et al. 10.1109/JSTARS.2023.3285288
65. The potential of optical and SAR time-series data for the improvement of aboveground biomass carbon estimation in Southwestern China’s evergreen coniferous forests Y. Zhang et al. 10.1080/15481603.2024.2345438
66. L-Band Microwave Satellite Data and Model Simulations Over the Dry Chaco to Estimate Soil Moisture, Soil Temperature, Vegetation, and Soil Salinity F. Vincent et al. 10.1109/JSTARS.2022.3193636
67. Satellite‐Observed Vegetation Responses to Intraseasonal Precipitation Variability B. Harris et al. 10.1029/2022GL099635
68. A Global Bottom‐Up Approach to Estimate Fuel Consumed by Fires Using Above Ground Biomass Observations F. Di Giuseppe et al. 10.1029/2021GL095452
69. Comparative Evaluation of Microwave L-Band VOD and Optical NDVI for Agriculture Drought Detection over Central Europe M. Afshar et al. 10.3390/rs13071251
70. Temperature effects on L-band vegetation optical depth of a boreal forest M. Schwank et al. 10.1016/j.rse.2021.112542
71. A new SMAP soil moisture and vegetation optical depth product (SMAP-IB): Algorithm, assessment and inter-comparison X. Li et al. 10.1016/j.rse.2022.112921
72. Interannual Variations of Vegetation Optical Depth are Due to Both Water Stress and Biomass Changes A. Konings et al. 10.1029/2021GL095267
73. Performance of SMOS Soil Moisture Products Over Core Validation Sites A. Colliander et al. 10.1109/LGRS.2023.3272878
74. VODCA v2: multi-sensor, multi-frequency vegetation optical depth data for long-term canopy dynamics and biomass monitoring R. Zotta et al. 10.5194/essd-16-4573-2024
75. Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review F. Frappart et al. 10.3390/rs12182915
76. Continuous ground monitoring of vegetation optical depth and water content with GPS signals V. Humphrey & C. Frankenberg 10.5194/bg-20-1789-2023
77. Quantitative assessment of various proxies for downscaling coarse-resolution VOD products over the contiguous United States S. Zhong et al. 10.1016/j.jag.2024.103910
78. Global Unsupervised Assessment of Multifrequency Vegetation Optical Depth Sensitivity to Vegetation Cover C. Olivares-Cabello et al. 10.1109/JSTARS.2022.3226001
79. Design and performance of the Climate Change Initiative Biomass global retrieval algorithm M. Santoro et al. 10.1016/j.srs.2024.100169
80. Land cover and management effects on ecosystem resistance to drought stress C. Xiao et al. 10.5194/esd-14-1211-2023
81. Satellite L–band vegetation optical depth is directly proportional to crop water in the US Corn Belt K. Togliatti et al. 10.1016/j.rse.2019.111378
82. SMOS L-VOD Retrieved by Level 2 Algorithm and its Correlation With GEDI LIDAR Products C. Vittucci et al. 10.1109/JSTARS.2021.3128022
83. Retrieving global surface soil moisture from GRACE satellite gravity data M. Sadeghi et al. 10.1016/j.jhydrol.2020.124717
84. Accounting for fuel in fire danger forecasts: the fire occurrence probability index (FOPI) F. Di Giuseppe 10.1088/1748-9326/acd2ee
85. ASCAT IB: A radar-based vegetation optical depth retrieved from the ASCAT scatterometer satellite X. Liu et al. 10.1016/j.rse.2021.112587
86. Regularized Dual-Channel Algorithm for the Retrieval of Soil Moisture and Vegetation Optical Depth From SMAP Measurements J. Chaubell et al. 10.1109/JSTARS.2021.3123932
87. 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
88. Reviews and syntheses: Recent advances in microwave remote sensing in support of terrestrial carbon cycle science in Arctic–boreal regions A. Mavrovic et al. 10.5194/bg-20-2941-2023
89. Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review G. Balsamo et al. 10.3390/rs10122038
90. Compared performances of SMOS-IC soil moisture and vegetation optical depth retrievals based on Tau-Omega and Two-Stream microwave emission models X. Li et al. 10.1016/j.rse.2019.111502
91. 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
92. Vegetation moisture estimation in the Western United States using radiometer-radar-lidar synergy D. Chaparro et al. 10.1016/j.rse.2024.113993
93. Improvements to a Crucial Budyko-Fu Parameter and Evapotranspiration Estimates via Vegetation Optical Depth over the Yellow River Basin X. Wang & J. Jin 10.3390/rs16152777
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95. The Performance of Multiple Model-Simulated Soil Moisture Datasets Relative to ECV Satellite Data in China W. Bai et al. 10.3390/w10101384
96. Satellite‐Observed Major Greening and Biomass Increase in South China Karst During Recent Decade M. Brandt et al. 10.1029/2018EF000890
97. A carbon sink-driven approach to estimate gross primary production from microwave satellite observations I. Teubner et al. 10.1016/j.rse.2019.04.022