{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T20:12:02Z","timestamp":1782504722012,"version":"3.54.5"},"reference-count":51,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2016,1,7]],"date-time":"2016-01-07T00:00:00Z","timestamp":1452124800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Multiple soil moisture products have been generated from data acquired by satellite. However, these satellite soil moisture products are not spatially or temporally complete, primarily due to track changes, radio-frequency interference, dense vegetation, and frozen soil. These deficiencies limit the application of soil moisture in land surface process simulation, climatic modeling, and global change research. To fill the gaps and generate spatially and temporally complete soil moisture data, a data assimilation algorithm is proposed in this study. A soil moisture model is used to simulate soil moisture over time, and the shuffled complex evolution optimization method, developed at the University of Arizona, is used to estimate the control variables of the soil moisture model from good-quality satellite soil moisture data covering one year, so that the temporal behavior of the modeled soil moisture reaches the best agreement with the good-quality satellite soil moisture data. Soil moisture time series were then reconstructed by the soil moisture model according to the optimal values of the control variables. To analyze its performance, the data assimilation algorithm was applied to a daily soil moisture product derived from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Microwave Radiometer Imager (MWRI), and the Advanced Microwave Scanning Radiometer 2 (AMSR2). Preliminary analysis using soil moisture data simulated by the Global Land Data Assimilation System (GLDAS) Noah model and soil moisture measurements at a multi-scale Soil Moisture and Temperature Monitoring Network on the central Tibetan Plateau (CTP-SMTMN) was performed to validate this method. The results show that the data assimilation algorithm can efficiently reconstruct spatially and temporally complete soil moisture time series. The reconstructed soil moisture data are consistent with the spatial precipitation distribution and have strong positive correlations with the values simulated by the GLDAS Noah model over large areas of the region. Compared to the soil moisture measurements at the medium and large networks, the reconstructed soil moisture data have almost the same accuracy as the soil moisture product derived from AMSR-E\/MWRI\/AMSR2 for ascending and descending orbits.<\/jats:p>","DOI":"10.3390\/rs8010049","type":"journal-article","created":{"date-parts":[[2016,1,7]],"date-time":"2016-01-07T11:11:51Z","timestamp":1452165111000},"page":"49","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Spatially and Temporally Complete Satellite Soil Moisture Data Based on a Data Assimilation Method"],"prefix":"10.3390","volume":"8","author":[{"given":"Zhiqiang","family":"Xiao","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9847-9034","authenticated-orcid":false,"given":"Lingmei","family":"Jiang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongli","family":"Zhu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4962-4888","authenticated-orcid":false,"given":"Jindi","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinyang","family":"Du","sequence":"additional","affiliation":[{"name":"Numerical Terradynamic Simulation Group, College of Forestry and Conservation, The University of Montana, Missoula, MT 59812, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2016,1,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1729","DOI":"10.1109\/36.942551","article-title":"Soil moisture retrieval from space: The Soil Moisture and Ocean Salinity (SMOS) mission","volume":"39","author":"Kerr","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Bartalis, Z., Wagner, W., Naeimi, V., Hasenauer, S., Scipal, K., Bonekamp, H., Figa, J., and Anderson, C. (2007). Initial soil moisture retrievals from the METOPA Advanced Scatterometer (ASCAT). Geophys. Res. Lett., 34.","DOI":"10.1029\/2007GL031088"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1109\/TGRS.2002.808331","article-title":"The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), NASDA\u2019s contribution to the EOS for global energy and water cycle studies","volume":"41","author":"Kawanishi","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_4","first-page":"217","article-title":"Development of an Advanced Microwave Scanning Radiometer (AMSR-E) algorithm of soil moisture and vegetation water content","volume":"48","author":"Koike","year":"2004","journal-title":"Annu. J. Hydraul. Eng. Jpn. Soc. Civil Eng."},{"key":"ref_5","first-page":"1903","article-title":"Analysis of surface and root soil moisture dynamics with ERS scatterometer and the hydrometeorological model SAFRAN-ISBA-MODCOU at Grand Morin watershed (France)","volume":"5","author":"Zribi","year":"2008","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2630","DOI":"10.1109\/TGRS.2012.2186458","article-title":"Analysis of ASCAT-C band scatterometer estimations derived over a semi-arid region","volume":"50","author":"Amri","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wagner, W., Scipal, K., Pathe, C., Gerten, D., Lucht, W., and Rudolf, B. (2003). Evaluation of the agreement between the first global remotely sensed soil moisture data with model and precipitation data. J. Geophys. Res., 108.","DOI":"10.1029\/2003JD003663"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1175\/2008JHM997.1","article-title":"An intercomparison of ERS-Scat and AMSR-E soil moisture observations with model simulations over France","volume":"10","author":"Calvet","year":"2009","journal-title":"J. Hydrometeorol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1007\/s10712-008-9044-0","article-title":"Global soil moisture patterns observed by space borne microwave radiometers and scatterometers","volume":"29","author":"Wagner","year":"2008","journal-title":"Surv. Geophys."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"4256","DOI":"10.1109\/TGRS.2010.2051035","article-title":"Validation of advanced microwave scanning radiometer soil moisture products","volume":"48","author":"Jackson","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1530","DOI":"10.1109\/TGRS.2011.2168533","article-title":"Validation of Soil Moisture and Ocean Salinity (SMOS) soil moisture over watershed networks in the U.S","volume":"50","author":"Jackson","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1572","DOI":"10.1109\/TGRS.2012.2186581","article-title":"Evaluation of SMOS soil moisture products over continental U.S. using the SCAN\/SNOTEL network","volume":"50","author":"Bitar","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3390","DOI":"10.1016\/j.rse.2011.08.003","article-title":"Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe","volume":"115","author":"Brocca","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1016\/j.rse.2008.11.011","article-title":"An evaluation of AMSR-E derived soil moisture over Australia","volume":"113","author":"Draper","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2303","DOI":"10.5194\/hess-15-2303-2011","article-title":"The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) for quantifying uncertainties in coarse resolution satellite and model products","volume":"15","author":"Su","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.envsoft.2011.10.015","article-title":"A three-dimensional gap filling method for large geophysical datasets: Application to global satellite soil moisture observations","volume":"30","author":"Wang","year":"2012","journal-title":"Environ. Model. Softw."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/j.envsoft.2009.09.012","article-title":"Global sensitivity analysis measures the quality of parameter estimation: The case of soil parameters and a crop model","volume":"25","author":"Varella","year":"2010","journal-title":"Environ. Model. Softw."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1080\/01431169208904212","article-title":"The Best Index Slope Extraction (BISE)\u2014A method for reducing noise in NDVI time-series","volume":"13","author":"Viovy","year":"1992","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2801","DOI":"10.1080\/01431160600967128","article-title":"Stabilizing high-order, non-classical harmonic analysis of NDVI data for average annual models by damping model roughness","volume":"28","author":"Hermance","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.rse.2006.03.011","article-title":"Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999","volume":"103","author":"Julien","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"9844","DOI":"10.3390\/rs70809844","article-title":"Reconstruction of satellite-retrieved land-surface reflectance based on temporally-continuous vegetation indices","volume":"7","author":"Xiao","year":"2015","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1824","DOI":"10.1109\/TGRS.2002.802519","article-title":"Seasonality extraction by function fitting to time\u2014Series of satellite sensor data","volume":"40","author":"Eklundh","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3519","DOI":"10.1080\/01431169408954343","article-title":"A global 1 by 1 NDVI data set for climate studies. Part 2: The generation of global fields of terrestrial biophysical parameters from the NDVI","volume":"15","author":"Sellers","year":"1994","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1016\/j.cageo.2004.05.006","article-title":"TIMESAT\u2014A program for analyzing time-series of satellite sensor data","volume":"30","author":"Eklundh","year":"2004","journal-title":"Comput. Geosci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1911","DOI":"10.1080\/014311600209814","article-title":"Reconstructing cloud free NDVI composites using Fourier analysis of time series","volume":"21","author":"Roerink","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.rse.2006.07.026","article-title":"Spatially and temporally continuous LAI data sets based on an integrated filtering method: Examples from North America","volume":"112","author":"Fang","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1109\/TGRS.2004.838359","article-title":"Spatially complete global spectral surface albedos: Value-add datasets derived from Terra MODIS land products","volume":"43","author":"Moody","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1175\/BAMS-85-3-381","article-title":"The global land data assimilation system","volume":"85","author":"Rodell","year":"2004","journal-title":"Bull. Am. Meteor. Soc."},{"key":"ref_29","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_30","doi-asserted-by":"crossref","unstructured":"Hain, C.R., Crow, W.T., Anderson, M.C., and Mecikalski, J.R. (2012). An ensemble Kalman filter dual assimilation of thermal infrared and microwave satellite observations of soil moisture into the Noah land surface model. Water Resour. Res., 48.","DOI":"10.1029\/2011WR011268"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/S0309-1708(02)00088-X","article-title":"The assimilation of remotely sensed soil brightness temperature imagery into a land surface model using ensemble Kalman filtering: A case study based on ESTAR measurements during SGP97","volume":"26","author":"Crow","year":"2003","journal-title":"Adv. Water Resour."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Reichle, R.H., and Koster, R.D. (2005). Global assimilation of satellite surface soilmoisture retrievals into the NASA catchment land surface model. Geophys. Res. Lett., 32.","DOI":"10.1029\/2004GL021700"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1007\/s12040-011-0076-3","article-title":"Modelling soil moisture under different land covers in a sub-humid environment of Western Ghats","volume":"120","author":"Venkatesh","year":"2011","journal-title":"India J. Earth Syst. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1002\/hyp.6629","article-title":"On the estimation of antecedent wetness conditions in rainfall-runoff modelling","volume":"22","author":"Brocca","year":"2008","journal-title":"Hydrol. Process."},{"key":"ref_35","first-page":"13","article-title":"Evaluation des besoins en eau d\u2019irrigation, \u00e9vapotranspiration potentielle","volume":"12","author":"Turc","year":"1961","journal-title":"Ann. Agron."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1061\/JRCEA4.0001390","article-title":"Estimating potential evapotranspiration","volume":"108","author":"Hargreaves","year":"1982","journal-title":"J. Irrig. Drain. E-Asce"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"96","DOI":"10.13031\/2013.26773","article-title":"Reference crop evapotranspiration from temperature","volume":"1","author":"Hargreaves","year":"1985","journal-title":"Appl. Eng. Agric."},{"key":"ref_38","unstructured":"Allen, R., Pereira, L.S., Raes, D., and Smith, M. (1998). Guidelines for Computing Crop Water Requirements, Food and Agriculture Organization of the United Nations. Irrigation Drainage Paper No.56."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1029\/91WR02985","article-title":"Effective and efficient global optimization for conceptual rainfall-runoff models","volume":"28","author":"Duan","year":"1992","journal-title":"Water Resour. Res."},{"key":"ref_40","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_41","unstructured":"Sheng, P., Mao, J., Li, J., Zhang, A., Sang, J., and Pan, N. (2003). Atmospheric Physics, Peking University Press."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2831","DOI":"10.1109\/TGRS.2005.857902","article-title":"A parameterized multifrequency-polarization surface emission model","volume":"43","author":"Shi","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2173","DOI":"10.1007\/s11430-013-4700-8","article-title":"Analysis of spatial distribution and multi-year trend of the remotely sensed soil moisture on the Tibetan Plateau","volume":"56","author":"Liu","year":"2013","journal-title":"Sci. China Earth Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"8594","DOI":"10.3390\/rs6098594","article-title":"Inter-calibration of satellite passive microwave land observations from AMSR-E and AMSR2 using overlapping FY3B-MWRI sensor measurements","volume":"6","author":"Du","year":"2014","journal-title":"Remote Sens."},{"key":"ref_45","unstructured":"Jiang, L., Lu, L., Qi, Y., Du, J., and Tao, J. (2015). Comparison of satellite soil moisture products with field observations and model simulation in the Tibetan Plateau. Remote Sens. Environ., submitted."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1016\/j.rse.2005.10.017","article-title":"Vegetation and surface roughness effects on AMSR-E land observations","volume":"100","author":"Njoku","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"F01002","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."},{"key":"ref_48","unstructured":"Goddard Earth Sciences Data and Information Services Center, Available online: http:\/\/disc.sci.gsfc.nasa.gov\/hydrology\/data-holdings."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1907","DOI":"10.1175\/BAMS-D-12-00203.1","article-title":"A multi-scale soil moisture and freeze-thaw monitoring network on the Third Pole","volume":"94","author":"Yang","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Xiao, Z., Wang, T., Liang, S., and Sun, R. (2015). Estimating the fractional vegetation cover from GLASS leaf area index product. Remote Sens., under review.","DOI":"10.3390\/rs8040337"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1061\/(ASCE)0733-9437(2006)132:3(238)","article-title":"Performance evaluation of reference evapotranspiration equations across a range of Indian climates","volume":"132","author":"Nandagiri","year":"2006","journal-title":"J. Irrig. Drain. Eng."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/1\/49\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:17:24Z","timestamp":1760210244000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/1\/49"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,1,7]]},"references-count":51,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,1]]}},"alternative-id":["rs8010049"],"URL":"https:\/\/doi.org\/10.3390\/rs8010049","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,1,7]]}}}