105 citations as recorded by crossref.

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2. Theoretical uncertainties for global satellite-derived burned area estimates J. Brennan et al. https://doi.org/10.5194/bg-16-3147-2019
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4. Assessment of Level-3 Gridded Global Precipitation Mission (GPM) Products Over Oceans S. Khan & V. Maggioni https://doi.org/10.3390/rs11030255
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7. Retrievals of aerosol optical depth over the western North Atlantic Ocean during ACTIVATE L. Siu et al. https://doi.org/10.5194/amt-17-2739-2024
8. Evaluation of the ESA CCI soil moisture product using ground-based observations W. Dorigo et al. https://doi.org/10.1016/j.rse.2014.07.023
9. Quantifying Uncertainties in the Partitioned Swell Heights Observed From CFOSAT SWIM and Sentinel-1 SAR via Triple Collocation H. Wang et al. https://doi.org/10.1109/TGRS.2022.3179511
10. The Impact of Quadratic Nonlinear Relations between Soil Moisture Products on Uncertainty Estimates from Triple Collocation Analysis and Two Quadratic Extensions S. Zwieback et al. https://doi.org/10.1175/JHM-D-15-0213.1
11. Spatial Representativeness Analysis for Snow Depth Measurements of Meteorological Stations in Northeast China Y. Wang & Z. Zheng https://doi.org/10.1175/JHM-D-19-0134.1
12. The performance of Metop Advanced SCATterometer soil moisture data as a complementary source for the estimation of crop-soil water balance in Central Europe S. Thaler et al. https://doi.org/10.1017/S0021859618000011
13. CYGNSS Soil Moisture Performance in Guinea Savanna Region: Extended and Quadruple Collocation Evidence from Benue State, Nigeria S. Ajoniloju et al. https://doi.org/10.3390/rs18193267
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15. Comparison of traditional method and triple collocation analysis for evaluation of multiple gridded precipitation products across Germany Z. Duan et al. https://doi.org/10.1175/JHM-D-21-0049.1
16. Evaluation and Fusion of MODIS Data to Enhance the Reliability of GK2A/GK2B Geostationary Satellite Vegetation Indices J. Baik et al. https://doi.org/10.9798/KOSHAM.2025.25.6.39
17. Mapping the permafrost stability on the Tibetan Plateau for 2005–2015 Y. Ran et al. https://doi.org/10.1007/s11430-020-9685-3
18. Enhancing Uncertainty Assessment of LAI Remote Sensing Products Through Multiple Collocation Methods and Error Separation Techniques P. Zhou et al. https://doi.org/10.1109/JSTARS.2025.3602863
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20. Advancing High-Mountain Precipitation Reconstruction Through Merging of Multiple Data Sources: Triple Collocation Versus Signal-to-Noise Ratio Optimization S. Shah et al. https://doi.org/10.1109/TGRS.2024.3494812
21. Triple Collocation of Ground-, Satellite- and Land Surface Model-Based Surface Soil Moisture Products in Oklahoma Part II: New Multi-Sensor Soil Moisture (MSSM) Product Z. Hong et al. https://doi.org/10.3390/rs15133450
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23. Multi-scale analysis of bias correction of soil moisture C. Su & D. Ryu https://doi.org/10.5194/hess-19-17-2015
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25. Uncertainty of Reference Pixel Soil Moisture Averages Sampled at SMAP Core Validation Sites F. Chen et al. https://doi.org/10.1175/JHM-D-19-0049.1
26. Decomposition of Random Errors Inherent to HOAPS-3.2 Near-Surface Humidity Estimates Using Multiple Triple Collocation Analysis J. Kinzel et al. https://doi.org/10.1175/JTECH-D-15-0122.1
27. Application of Triple Collocation in Ground-Based Validation of Soil Moisture Active/Passive (SMAP) Level 2 Data Products F. Chen et al. https://doi.org/10.1109/JSTARS.2016.2569998
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29. Summarizing multiple aspects of triple collocation analysis in a single diagram L. Siu et al. https://doi.org/10.3389/frsen.2024.1395442
30. Sea surface current estimation using optical satellite imagery of Kelvin wakes and AIS data K. Haakman et al. https://doi.org/10.1016/j.rse.2024.114400
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32. Adaptive stacked ensemble fusion: Bayesian porosity inference in alluvial aquifers when the errors are not independent D. Zeqiraj & A. Beqiraj https://doi.org/10.1016/j.jconhyd.2026.105086
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35. Accounting for seasonal retrieval errors in the merging of multi-sensor satellite soil moisture products P. Stradiotti et al. https://doi.org/10.1016/j.srs.2025.100242
36. Decadal Evaluation of Sea Surface Temperature Products from MWRI Onboard FY-3B/C/D Satellites Y. Zhao et al. https://doi.org/10.3390/jmse13112136
37. Characterization of Drought Development through Remote Sensing: A Case Study in Central Yunnan, China S. Abbas et al. https://doi.org/10.3390/rs6064998
38. Global-scale evaluation of SMAP, SMOS and ASCAT soil moisture products using triple collocation F. Chen et al. https://doi.org/10.1016/j.rse.2018.05.008
39. Evaluation and calibration of a high-resolution soil moisture product for wildfire prediction and management . Vinodkumar & I. Dharssi https://doi.org/10.1016/j.agrformet.2018.09.012
40. Triple Collocation Analysis of Soil Moisture From Metop-A ASCAT and SMOS Against JRA-55 and ERA-Interim K. Miyaoka et al. https://doi.org/10.1109/JSTARS.2016.2632306
41. Continental satellite soil moisture data assimilation improves root-zone moisture analysis for water resources assessment L. Renzullo et al. https://doi.org/10.1016/j.jhydrol.2014.08.008
42. Estimating time-dependent vegetation biases in the SMAP soil moisture product S. Zwieback et al. https://doi.org/10.5194/hess-22-4473-2018
43. An intercomparison of four gridded precipitation products over Europe using an extension of the three-cornered-hat method L. Lledó et al. https://doi.org/10.5194/hess-28-5149-2024
44. Triple collocation: Beyond three estimates and separation of structural/non-structural errors M. Pan et al. https://doi.org/10.1016/j.rse.2015.10.028
45. Evaluating a multi-step collocation approach for an ensemble climatological dataset of actual evapotranspiration over Italy C. Cammalleri et al. https://doi.org/10.1016/j.jhydrol.2024.132209
46. Theoretical uncertainty analysis of global MODIS, CYCLOPES, and GLOBCARBON LAI products using a triple collocation method H. Fang et al. https://doi.org/10.1016/j.rse.2012.06.013
47. A Monte Carlo based adaptive Kalman filtering framework for soil moisture data assimilation A. Gruber et al. https://doi.org/10.1016/j.rse.2019.04.003
48. Terrestrial Water Storage Change Retrieved by GRACE and Its Implication in the Tibetan Plateau: Estimating Areal Precipitation in Ungauged Region Y. Jia et al. https://doi.org/10.3390/rs12193129
49. Quality Assessment of Sea Surface Temperature from ATSRs of the Climate Change Initiative (Phase 1) C. Tsamalis & R. Saunders https://doi.org/10.3390/rs10040497
50. Cross-evaluation of ground-based, multi-satellite and reanalysis precipitation products: Applicability of the Triple Collocation method across Mainland China C. Li et al. https://doi.org/10.1016/j.jhydrol.2018.04.039
51. Advanced Calibration Framework for 3-D Scanning Doppler Wind Lidar: Enhancing Performance and Measurement Accuracy C. Zhang et al. https://doi.org/10.1109/TIM.2026.3731719
52. Inter-Comparison of SST Products from iQuam, AMSR2/GCOM-W1, and MWRI/FY-3D Y. Zhao et al. https://doi.org/10.3390/rs16112034
53. Characterizing Coarse‐Scale Representativeness of in situ Soil Moisture Measurements from the International Soil Moisture Network A. Gruber et al. https://doi.org/10.2136/vzj2012.0170
54. Addressing spatial gaps in ESA CCI soil moisture product: A hierarchical reconstruction approach using deep learning model T. Ding et al. https://doi.org/10.1016/j.jag.2024.104003
55. Assessing global passive microwave soil moisture retrievals in mountainous terrain: insights from in situ validation and extended triple collocation Y. Yang et al. https://doi.org/10.1016/j.geoderma.2026.117707
56. Building the vegetation drought response index for Canada (VegDRI-Canada) to monitor agricultural drought: first results T. Tadesse et al. https://doi.org/10.1080/15481603.2017.1286728
57. Comparing soil moisture anomalies from multiple independent sources over different regions across the globe C. Cammalleri et al. https://doi.org/10.5194/hess-21-6329-2017
58. Consistency and uncertainty of gridded terrestrial evapotranspiration estimations over China L. Guo et al. https://doi.org/10.1016/j.jhydrol.2022.128245
59. Determining Errors in Directional Buoy-Derived Swell Heights via the Joint Analysis of Space-Borne Radars and WaveWatch III Simulations H. Wang et al. https://doi.org/10.1109/LGRS.2022.3216667
60. Error Estimation of Pathfinder Version 5.3 Level-3C SST Using Extended Triple Collocation Analysis K. Saha et al. https://doi.org/10.3390/rs12040590
61. Multi‐Timescale Analysis of the Spatial Representativeness of In Situ Soil Moisture Data within Satellite Footprints B. Molero et al. https://doi.org/10.1002/2017JD027478
62. How far can the statistical error estimation problem be closed by collocated data? A. Vogel & R. Ménard https://doi.org/10.5194/npg-30-375-2023
63. Confidently Uncertain: Validating Satellite ECV Measurement Uncertainty Estimates T. Verhoelst et al. https://doi.org/10.1007/s10712-026-09939-6
64. Comparison of soil wetness from multiple models over Australia with observations . Vinodkumar et al. https://doi.org/10.1002/2015WR017738
65. Synergizing multi-collocation fusion and spatiotemporal deep learning to enhance global soil moisture memory characterization X. Min et al. https://doi.org/10.1080/15481603.2026.2666699
66. Triple Collocation of Ground-, Satellite- and Land Surface Model-Based Surface Soil Moisture Products in Oklahoma—Part I: Individual Product Assessment Z. Hong et al. https://doi.org/10.3390/rs14225641
67. Validation and trend analysis of ECV soil moisture data on cropland in North China Plain during 1981–2010 S. Wang et al. https://doi.org/10.1016/j.jag.2015.10.010
68. Best Linear Unbiased Estimators for Fusion of Multiple CYGNSS Soil Moisture Products M. Nabi et al. https://doi.org/10.1109/JSTARS.2024.3443100
69. Stand-alone error characterisation of microwave satellite soil moisture using a Fourier method C. Su et al. https://doi.org/10.1016/j.rse.2014.08.014
70. Error Analysis on ESA’s Envisat ASAR Wave Mode Significant Wave Height Retrievals Using Triple Collocation Model H. Wang et al. https://doi.org/10.3390/rs61212217
71. Error Decomposition of Remote Sensing Soil Moisture Products Based on the Triple-Collocation Method Introducing an Unbiased Reference Dataset: A Case Study on the Tibetan Plateau J. Kang et al. https://doi.org/10.3390/rs12183087
72. Validation of the ESA CCI soil moisture product in China R. An et al. https://doi.org/10.1016/j.jag.2015.09.009
73. Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology A. Gruber et al. https://doi.org/10.5194/essd-11-717-2019
74. The added utility of nonlinear methods compared to linear methods in rescaling soil moisture products M. Afshar & M. Yilmaz https://doi.org/10.1016/j.rse.2017.05.017
75. The potential of 2D Kalman filtering for soil moisture data assimilation A. Gruber et al. https://doi.org/10.1016/j.rse.2015.10.019
76. Recent advances in (soil moisture) triple collocation analysis A. Gruber et al. https://doi.org/10.1016/j.jag.2015.09.002
77. Uncertainty analysis of eleven multisource soil moisture products in the third pole environment based on the three-corned hat method J. Liu et al. https://doi.org/10.1016/j.rse.2020.112225
78. Clarifications on the equations and the sample number in triple collocation analysis using SST observations C. Tsamalis https://doi.org/10.1016/j.rse.2022.112936
79. Fusion and Analysis of Multi-Source Precipitation Data (2003–2021) in the Yangtze River Basin R. Sun et al. https://doi.org/10.3390/rs18081191
80. Quadruple Collocation Analysis for Soil Moisture Product Assessment N. Pierdicca et al. https://doi.org/10.1109/LGRS.2015.2414654
81. Sensitivity of Soil Moisture Analyses to Contrasting Background and Observation Error Scenarios J. Muñoz-Sabater et al. https://doi.org/10.3390/w10070890
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88. Synergistic Exploitation of Hyper- and Multi-Spectral Precursor Sentinel Measurements to Determine Phytoplankton Functional Types (SynSenPFT) S. Losa et al. https://doi.org/10.3389/fmars.2017.00203
89. Exploitation of error correlation in a large analysis validation: GlobCurrent case study R. Danielson et al. https://doi.org/10.1016/j.rse.2018.07.016
90. Cross-Examination of Similarity, Difference and Deficiency of Gauge, Radar and Satellite Precipitation Measuring Uncertainties for Extreme Events Using Conventional Metrics and Multiplicative Triple Collocation Z. Li et al. https://doi.org/10.3390/rs12081258
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93. Global Gross Primary Production Data Fusion by Triple Collocation Analysis From 1992 to 2018 Y. Zeng et al. https://doi.org/10.1109/JSTARS.2026.3707237
94. A Polarimetric First-Order Model of Soil Moisture Effects on the DInSAR Coherence S. Zwieback et al. https://doi.org/10.3390/rs70607571
95. Examining the performance of precipitation products in characterizing the Indian summer monsoon rainfall (ISMR) using triple collocation S. Paul & H. Alemohammad https://doi.org/10.1016/j.jhydrol.2025.133136
96. Estimating Random Errors of Scatterometer, Altimeter, and Model Wind Speed Data S. Abdalla & G. De Chiara https://doi.org/10.1109/JSTARS.2017.2659220
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100. Remote Sensing Measurements at a Rural Site in China: Implications for Satellite NO2 and HCHO Measurement Uncertainty and Emissions From Fires K. Chong et al. https://doi.org/10.1029/2023JD039310
101. An Enhanced Three-Cornered Hat Method for Uncertainty Analysis of Soil Moisture Products: Optimization Based on Error Model Improvement X. Wang et al. https://doi.org/10.1109/LGRS.2026.3709900
102. Enhanced Soil Moisture Retrieval through Integrating Satellite Data with Pedotransfer Functions in a Complex Landscape of Ethiopia E. Teferi et al. https://doi.org/10.3390/w15193396
103. A Comprehensive Evaluation of Gridded L-, C-, and X-Band Microwave Soil Moisture Product over the CZO in the Central Ganga Plains, India S. Dash & R. Sinha https://doi.org/10.3390/rs14071629
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105. Assessing and optimizing high-resolution global river streamflow estimates with triple collocation analysis M. Sun et al. https://doi.org/10.1016/j.jhydrol.2026.135122