{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T02:40:40Z","timestamp":1771209640927,"version":"3.50.1"},"reference-count":67,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T00:00:00Z","timestamp":1672099200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32171781"],"award-info":[{"award-number":["32171781"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42001201"],"award-info":[{"award-number":["42001201"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["21C00346"],"award-info":[{"award-number":["21C00346"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Chongqing Agricultural Industry Digital Map Project","award":["32171781"],"award-info":[{"award-number":["32171781"]}]},{"name":"Chongqing Agricultural Industry Digital Map Project","award":["42001201"],"award-info":[{"award-number":["42001201"]}]},{"name":"Chongqing Agricultural Industry Digital Map Project","award":["21C00346"],"award-info":[{"award-number":["21C00346"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High-spatiotemporal resolution soil moisture (SM) plays an essential role in optimized irrigation, agricultural droughts, and hydrometeorological model simulations. However, producing high-spatiotemporal seamless soil moisture products is challenging due to the inability of optical bands to penetrate clouds and the coarse spatiotemporal resolution of microwave and reanalysis products. To address these issues, this study proposed a framework for multi-source data merging based on the triple collocation (TC) method with an explicit physical mechanism, which was dedicated to generating seamless 1 km daily soil moisture products. Current merging techniques based on the TC method often lack seamless daily optical data input. To remedy this deficiency, our study performed a spatiotemporal reconstruction on MODIS LST and NDVI, and retrieved seamless daily optical soil moisture products. Then, the optical-derived sm1, microwave-retrieved sm2 (ESA CCI combined), and reanalysis sm3 (CLDAS) were matched by the cumulative distribution function (CDF) method to eliminate bias, and their weights were determined by the TC method. Finally, the least squares algorithm and the significance judgment were adopted to complete the merging. Although the CLDAS soil moisture presented anomalies over several stations, our proposed method can detect and reduce this impact by minimizing its weight, which shows the robustness of the method. This framework was implemented in the Naqu region, and the results showed that the merged products captured the temporal variability of the SM and depicted spatial information in detail; the validation with the in situ measurement obtained an average ubRMSE of 0.046 m\u00b3\/m\u00b3. Additionally, this framework is transferrable to any area with measured sites for better agricultural and hydrological applications.<\/jats:p>","DOI":"10.3390\/rs15010159","type":"journal-article","created":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T05:30:27Z","timestamp":1672205427000},"page":"159","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Merging Microwave, Optical, and Reanalysis Data for 1 Km Daily Soil Moisture by Triple Collocation"],"prefix":"10.3390","volume":"15","author":[{"given":"Luyao","family":"Zhu","sequence":"first","affiliation":[{"name":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Wenjie","family":"Li","sequence":"additional","affiliation":[{"name":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"},{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Qilu Aerospace Information Research Institute, Jinan 250100, China"}]},{"given":"Hongquan","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Xiaodong","family":"Deng","sequence":"additional","affiliation":[{"name":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}]},{"given":"Cheng","family":"Tong","sequence":"additional","affiliation":[{"name":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7554-9995","authenticated-orcid":false,"given":"Shan","family":"He","sequence":"additional","affiliation":[{"name":"College of Economics and Management, China Jiliang University, Hangzhou 310029, China"}]},{"given":"Ke","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1038\/ngeo2868","article-title":"The Global Distribution and Dynamics of Surface Soil Moisture","volume":"10","author":"McColl","year":"2017","journal-title":"Nat. Geosci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1038\/s41586-021-03325-5","article-title":"Soil Moisture\u2014Atmosphere Feedback Dominates Land Carbon Uptake Variability","volume":"592","author":"Humphrey","year":"2021","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"112222","DOI":"10.1016\/j.rse.2020.112222","article-title":"Assimilation of SMAP and ASCAT Soil Moisture Retrievals into the JULES Land Surface Model Using the Local Ensemble Transform Kalman Filter","volume":"253","author":"Seo","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"113161","DOI":"10.1016\/j.rse.2022.113161","article-title":"Improving Soil Moisture Assimilation Efficiency via Model Calibration Using SMAP Surface Soil Moisture Climatology Information","volume":"280","author":"Zhou","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1038\/s43017-022-00317-5","article-title":"Plant Phenology Changes and Drivers on the Qinghai\u2013Tibetan Plateau","volume":"3","author":"Shen","year":"2022","journal-title":"Nat. Rev. Earth Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2066","DOI":"10.1111\/gcb.16043","article-title":"Assessment of the Importance of Increasing Temperature and Decreasing Soil Moisture on Global Ecosystem Productivity Using Solar-Induced Chlorophyll Fluorescence","volume":"28","author":"Dang","year":"2022","journal-title":"Glob. Change Biol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"9338","DOI":"10.1002\/2014JD021454","article-title":"Influences of Soil Moisture and Vegetation on Convective Precipitation Forecasts over the United States Great Plains","volume":"119","author":"Collow","year":"2014","journal-title":"J. Geophys. Res. Atmos. Res."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.earscirev.2010.02.004","article-title":"Investigating Soil Moisture\u2013Climate Interactions in a Changing Climate: A Review","volume":"99","author":"Seneviratne","year":"2010","journal-title":"Earth-Sci. Rev."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2111","DOI":"10.1111\/gcb.16050","article-title":"Uncovering the Critical Soil Moisture Thresholds of Plant Water Stress for European Ecosystems","volume":"3","author":"Fu","year":"2022","journal-title":"Glob. Change Biol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4892","DOI":"10.1038\/s41467-020-18631-1","article-title":"Soil Moisture Dominates Dryness Stress on Ecosystem Production Globally","volume":"11","author":"Liu","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1675","DOI":"10.5194\/hess-15-1675-2011","article-title":"The International Soil Moisture Network: A Data Hosting Facility for Global in Situ Soil Moisture Measurements","volume":"15","author":"Dorigo","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"111680","DOI":"10.1016\/j.rse.2020.111680","article-title":"Soil Moisture Experiment in the Luan River Supporting New Satellite Mission Opportunities","volume":"240","author":"Zhao","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.rse.2018.02.049","article-title":"An Integrated Method for Validating Long-Term Leaf Area Index Products Using Global Networks of Site-Based Measurements","volume":"209","author":"Xu","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/S0034-4257(01)00274-7","article-title":"A Simple Interpretation of the Surface Temperature\/Vegetation Index Space for Assessment of Surface Moisture Status","volume":"79","author":"Sandholt","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.rse.2017.01.027","article-title":"High Spatio-Temporal Resolution Mapping of Soil Moisture by Integrating Wireless Sensor Network Observations and MODIS Apparent Thermal Inertia in the Babao River Basin, China","volume":"191","author":"Kang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_16","unstructured":"Ulaby, F.T., Moore, R.K., and Fung, A.K. (1981). Microwave Remote Sensing: Active and Passive. Volume I: Microwave Remote Sensing Fundamentals and Radiometry, Addison Wesley Publishing Company, World Science Division."},{"key":"ref_17","unstructured":"Ulaby, F.T., Moore, R.K., and Fung, A.K. (1982). Microwave Remote Sensing: Active and Passive, Volume II: Radar Remote Sensing and Surface Scattering and Emission Theory, Addison Wesley Publishing Company, World Science Division."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4125","DOI":"10.1109\/TGRS.2009.2022088","article-title":"A Change Detection Algorithm for Retrieving High-Resolution Soil Moisture from SMAP Radar and Radiometer Observations","volume":"47","author":"Piles","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","first-page":"1","article-title":"Soil Moisture Retrieval From Sentinel-1 Time-Series Data Over Croplands of Northeastern Thailand","volume":"19","author":"Fan","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1002\/hyp.3360070205","article-title":"Measuring Surface Soil Moisture Using Passive Microwave Remote Sensing","volume":"7","author":"Jackson","year":"1993","journal-title":"Hydrol. Process."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1384","DOI":"10.1109\/TGRS.2012.2184548","article-title":"The SMOS Soil Moisture Retrieval Algorithm","volume":"50","author":"Kerr","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","unstructured":"O\u2019neill, P., Bindlish, R., Chan, S., Chaubell, J., Colliander, A., Njoku, E., and Jackson, T. (2021). Soil Moisture Active Passive (SMAP) Algorithm Theoretical Basis Document Level 2 & 3 Soil Moisture (Passive) Data Products, Jet Propulsion Laboratory, California Institute of Technology."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.rse.2015.11.009","article-title":"Vegetation Optical Depth and Scattering Albedo Retrieval Using Time Series of Dual-Polarized L-Band Radiometer Observations","volume":"172","author":"Konings","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"112321","DOI":"10.1016\/j.rse.2021.112321","article-title":"Retrievals of Soil Moisture and Vegetation Optical Depth Using a Multi-Channel Collaborative Algorithm","volume":"257","author":"Zhao","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2007JF000769","article-title":"Multisensor Historical Climatology of Satellite-Derived Global Land Surface Moisture","volume":"113","author":"Owe","year":"2008","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_26","first-page":"198","article-title":"Recent Advances of L-Band Application in the Passive Microwave Remote Sensing of Soil Moisture and Its Prospects","volume":"37","author":"Zhao","year":"2018","journal-title":"Prog. Geogr."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.rse.2017.07.008","article-title":"Comparison of Different Polarimetric Decompositions for Soil Moisture Retrieval over Vegetation Covered Agricultural Area","volume":"199","author":"Wang","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"111740","DOI":"10.1016\/j.rse.2020.111740","article-title":"Combining Hyper-Resolution Land Surface Modeling with SMAP Brightness Temperatures to Obtain 30-m Soil Moisture Estimates","volume":"242","author":"Vergopolan","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/frwa.2020.00001","article-title":"Triple Collocation Based Multi-Source Precipitation Merging","volume":"2","author":"Dong","year":"2020","journal-title":"Front. Water"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"127197","DOI":"10.1016\/j.jhydrol.2021.127197","article-title":"The Use of Triple Collocation Approach to Merge Satellite- and Model-Based Terrestrial Water Storage for Flood Potential Analysis","volume":"603","author":"Yin","year":"2021","journal-title":"J. Hydrol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zeng, Y., Su, Z., Van Der Velde, R., Wang, L., Xu, K., Wang, X., and Wen, J. (2016). Blending Satellite Observed, Model Simulated, and in Situ Measured Soil Moisture over Tibetan Plateau. Remote Sens., 8.","DOI":"10.3390\/rs8030268"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"112610","DOI":"10.1016\/j.rse.2021.112610","article-title":"Estimation and Evaluation of High-Resolution Soil Moisture from Merged Model and Earth Observation Data in the Great Britain","volume":"264","author":"Peng","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"717","DOI":"10.5194\/essd-11-717-2019","article-title":"Evolution of the ESA CCI Soil Moisture Climate Data Records and Their Underlying Merging Methodology","volume":"11","author":"Gruber","year":"2019","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2845","DOI":"10.1109\/TGRS.2020.3012896","article-title":"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record","volume":"59","author":"Preimesberger","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2011JD015633","article-title":"An Intercomparison of Available Soil Moisture Estimates from Thermal Infrared and Passive Microwave Remote Sensing and Land Surface Modeling","volume":"116","author":"Hain","year":"2011","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.agrformet.2019.05.022","article-title":"An Improved Surface Soil Moisture Downscaling Approach over Cloudy Areas Based on Geographically Weighted Regression","volume":"275","author":"Song","year":"2019","journal-title":"Agric. For. Meteorol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1907","DOI":"10.1175\/BAMS-D-12-00203.1","article-title":"A Multiscale Soil Moisture and Freeze\u2013Thaw Monitoring Network on The Third Pole","volume":"94","author":"Yang","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Kang, J., Jin, R., Li, X., and Zhang, Y. (2020). 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. Remote Sens., 12.","DOI":"10.3390\/rs12183087"},{"key":"ref_39","first-page":"1","article-title":"Assessment and Error Analysis of Satellite Soil Moisture Products Over the Third Pole","volume":"60","author":"Zeng","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.rse.2017.07.001","article-title":"ESA CCI Soil Moisture for Improved Earth System Understanding: State-of-the Art and Future Directions","volume":"203","author":"Dorigo","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Zhu, L., Wang, H., Tong, C., Liu, W., and Du, B. (2019). Evaluation of ESA Active, Passive and Combined Soil Moisture Products Using Upscaled Ground Measurements. Sensors, 19.","DOI":"10.3390\/s19122718"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"5749","DOI":"10.5194\/hess-25-5749-2021","article-title":"The International Soil Moisture Network: Serving Earth System Science for over a Decade","volume":"25","author":"Dorigo","year":"2021","journal-title":"Hydrol. Earth Syst. Sci. Discuss."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1430","DOI":"10.1007\/s11430-010-4160-3","article-title":"China Land Soil Moisture EnKF Data Assimilation Based on Satellite Remote Sensing Data","volume":"54","author":"Shi","year":"2011","journal-title":"Sci. China Earth Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4647","DOI":"10.1002\/hyp.11383","article-title":"Assessment of Reanalysis Soil Moisture Products in the Permafrost Regions of the Central of the Qinghai\u2013Tibet Plateau","volume":"31","author":"Qin","year":"2017","journal-title":"Hydrol. Process."},{"key":"ref_45","unstructured":"Jarvis, A., Rubiano, J., Nelson, A., Farrow, A., and Mulligan, M. (2004). Practical Use of SRTM Data in the Tropics\u2013Comparisons with Digital Elevation Models Generated from Cartographic Data, International Centre for Tropical Agriculture."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1021\/ac60214a047","article-title":"Smoothing and Differentiation of Data by Simplified Least Squares Procedures","volume":"36","author":"Savitzky","year":"1964","journal-title":"Anal. Chem."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"112100","DOI":"10.1016\/j.rse.2020.112100","article-title":"Soil Moisture Retrievals Using ALOS2-ScanSAR and MODIS Synergy over Tibetan Plateau","volume":"251","author":"Wang","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Li, W., Huang, J., Yang, L., Chen, Y., Fang, Y., Jin, H., Sun, H., and Huang, R. (2021). A Practical Remote Sensing Monitoring Framework for Late Frost Damage in Wine Grapes Using Multi-Source Satellite Data. Remote Sens., 13.","DOI":"10.3390\/rs13163231"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"4539","DOI":"10.1109\/JSTARS.2015.2464094","article-title":"An Effective Interpolation Method for MODIS Land Surface Temperature on the Qinghai-Tibet Plateau","volume":"8","author":"Yu","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_50","first-page":"934","article-title":"The Potential of Multitemporal Aqua and Terra MODIS Apparent Thermal Inertia as a Soil Moisture Indicator","volume":"13","author":"Peters","year":"2011","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1080\/02757259409532220","article-title":"A Method to Make Use of Thermal Infrared Temperature and NDVI Measurements to Infer Surface Soil Water Content and Fractional Vegetation Cover","volume":"9","author":"Carlson","year":"1994","journal-title":"Remote Sens. Rev."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1029\/2004GL020938","article-title":"Bias Reduction in Short Records of Satellite Soil Moisture","volume":"31","author":"Reichle","year":"2004","journal-title":"Geophys. Res. Lett."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.rse.2017.05.017","article-title":"The Added Utility of Nonlinear Methods Compared to Linear Methods in Rescaling Soil Moisture Products","volume":"196","author":"Afshar","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"7804","DOI":"10.1029\/2019WR025111","article-title":"Impact of Rescaling Approaches in Simple Fusion of Soil Moisture Products","volume":"55","author":"Afshar","year":"2019","journal-title":"Water Resour. Res."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"111215","DOI":"10.1016\/j.rse.2019.111215","article-title":"Satellite Surface Soil Moisture from SMAP, SMOS, AMSR2 and ESA CCI: A Comprehensive Assessment Using Global Ground-Based Observations","volume":"231","author":"Ma","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_56","first-page":"28","article-title":"Validation of the ESA CCI Soil Moisture Product in China","volume":"48","author":"An","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"7755","DOI":"10.1029\/97JC03180","article-title":"Toward the True Near-Surface Wind Speed: Error Modeling and Calibration Using Triple Collocation","volume":"103","author":"Stoffelen","year":"1998","journal-title":"J. Geophys. Res. C Ocean."},{"key":"ref_58","first-page":"4426","article-title":"Triple Collocation\u2014A New Tool to Determine the Error Structure of Global Soil Moisture Products","volume":"3","author":"Scipal","year":"2010","journal-title":"Int. Geosci. Remote Sens. Symp."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2011WR011682","article-title":"An Objective Methodology for Merging Satellite- and Model-Based Soil Moisture Products","volume":"48","author":"Yilmaz","year":"2012","journal-title":"Water Resour. Res."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"6780","DOI":"10.1109\/TGRS.2017.2734070","article-title":"Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals","volume":"55","author":"Gruber","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_61","first-page":"62","article-title":"The Trough-and-Ridge Diagram","volume":"1","year":"1949","journal-title":"Tellus"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"4466","DOI":"10.1002\/jgrd.50301","article-title":"Evaluation of AMSR-E Retrievals and GLDAS Simulations against Observations of a Soil Moisture Network on the Central Tibetan Plateau","volume":"118","author":"Chen","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2013.07.003","article-title":"Spatial Upscaling of In-Situ Soil Moisture Measurements Based on MODIS-Derived Apparent Thermal Inertia","volume":"138","author":"Qin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1175\/2010JHM1223.1","article-title":"Performance Metrics for Soil Moisture Retrievals and Application Requirements","volume":"11","author":"Entekhabi","year":"2010","journal-title":"J. Hydrometeorol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"112324","DOI":"10.1016\/j.rse.2021.112324","article-title":"Time-Variant Error Characterization of SMAP and ASCAT Soil Moisture Using Triple Collocation Analysis","volume":"256","author":"Wu","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2005GL024889","article-title":"Relevance of Time-Varying and Time-Invariant Retrieval Error Sources on the Utility of Spaceborne Soil Moisture Products","volume":"32","author":"Crow","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"113387","DOI":"10.1016\/j.rse.2022.113387","article-title":"Remote Sensing of Environment A Global-Scale Intercomparison of Triple Collocation Analysis- and Ground-Based Soil Moisture Time-Variant Errors Derived from Different Rescaling Techniques","volume":"285","author":"Wu","year":"2023","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/1\/159\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:53:11Z","timestamp":1760147591000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/1\/159"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,27]]},"references-count":67,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["rs15010159"],"URL":"https:\/\/doi.org\/10.3390\/rs15010159","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,27]]}}}