{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T02:24:33Z","timestamp":1769826273009,"version":"3.49.0"},"reference-count":64,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2020,7,15]],"date-time":"2020-07-15T00:00:00Z","timestamp":1594771200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2019B10214"],"award-info":[{"award-number":["2019B10214"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>With the increasing utilization of satellite-based soil moisture products, a primary challenge is knowing their accuracy and robustness. This study presents a comprehensive assessment over China of three widely used global satellite soil moisture products, i.e., Soil Moisture Active Passive (SMAP), European Space Agency (ESA) Climate Change Initiative (CCI) Soil Moisture, Soil Moisture and Ocean Salinity (SMOS). In situ soil moisture from 1682 stations and Variable Infiltration Capacity (VIC) model are used to evaluate the performance of SMAP_L3, ESA_CCI_SM_COMBINED, SMOS_CATDS_L3 from 31 March 2015 to 3 June 2018. The Triple Collocation (TC) approach is used to minimize the uncertainty (e.g., scale issue) during the validation process. The TC analysis is conducted using three triplets, i.e., [SMAP-Insitu-VIC], [CCI-Insitu-VIC], [SMOS-Insitu-VIC]. In general, SMAP is the most reliable product, reflecting the main spatiotemporal characteristics of soil moisture, while SMOS has the lowest accuracy. The results demonstrate that the overall root mean square error of SMAP, CCI, SMOS is 0.040, 0.028, 0.107 m3m\u22123, respectively. The overall temporal correlation coefficient of SMAP, CCI, SMOS is 0.68, 0.65, 0.38, respectively. The overall fractional root mean square error of SMAP, CCI, SMOS is 0.707, 0.750, 0.897, respectively. In irrigated areas, the accuracy of CCI is reduced due to the land surface model (which does not consider irrigation) used for the rescaling of the CCI_COMBINED soil moisture product during the merging process, while SMAP and SMOS preserve the irrigation signal. The quality of SMOS is most strongly impacted by land surface temperature, vegetation, and soil texture, while the quality of CCI is the least affected by these factors. With the increase of Radio Frequency Interference, the accuracy of SMOS decreases dramatically, followed by SMAP and CCI. Higher representativeness error of in situ stations is noted in regions with higher topographic complexity. This study helps to provide a guideline for the application of satellite soil moisture products in scientific research and gives some references (e.g., modify data algorithm according to the main error sources) for improving the data quality.<\/jats:p>","DOI":"10.3390\/rs12142275","type":"journal-article","created":{"date-parts":[[2020,7,16]],"date-time":"2020-07-16T10:54:46Z","timestamp":1594896886000},"page":"2275","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Triple Collocation-Based Assessment of Satellite Soil Moisture Products with In Situ Measurements in China: Understanding the Error Sources"],"prefix":"10.3390","volume":"12","author":[{"given":"Xiaotao","family":"Wu","sequence":"first","affiliation":[{"name":"College of Hydrology and Water Resources, No. 1 Xikang Road, Hohai University, Nanjing 210098, China"},{"name":"Department of Geodesy and Geo-Information, Wiedner Hauptstra\u00dfe 8\/E120, Vienna University of Technology, A-1040 Vienna, Austria"}]},{"given":"Guihua","family":"Lu","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, No. 1 Xikang Road, Hohai University, Nanjing 210098, China"}]},{"given":"Zhiyong","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, No. 1 Xikang Road, Hohai University, Nanjing 210098, China"}]},{"given":"Hai","family":"He","sequence":"additional","affiliation":[{"name":"College of Hydrology and Water Resources, No. 1 Xikang Road, Hohai University, Nanjing 210098, China"}]},{"given":"Tracy","family":"Scanlon","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geo-Information, Wiedner Hauptstra\u00dfe 8\/E120, Vienna University of Technology, A-1040 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8054-7572","authenticated-orcid":false,"given":"Wouter","family":"Dorigo","sequence":"additional","affiliation":[{"name":"Department of Geodesy and Geo-Information, Wiedner Hauptstra\u00dfe 8\/E120, Vienna University of Technology, A-1040 Vienna, Austria"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,15]]},"reference":[{"key":"ref_1","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_2","doi-asserted-by":"crossref","unstructured":"Zhang, X., Zhang, T., Zhou, P., Shao, Y., and Gao, S. (2017). Validation Analysis of SMAP and AMSR2 Soil Moisture Products over the United States Using Ground-Based Measurements. Remote Sens., 9.","DOI":"10.3390\/rs9020104"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1016\/j.rse.2014.07.005","article-title":"The scale-dependence of SMOS soil moisture accuracy and its improvement through land data assimilation in the central Tibetan Plateau","volume":"152","author":"Zhao","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.rse.2016.02.042","article-title":"Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation","volume":"180","author":"Kerr","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"897","DOI":"10.5194\/hess-23-897-2019","article-title":"Estimating irrigation water use over the contiguous United States by combining satellite and reanalysis soil moisture data","volume":"23","author":"Zaussinger","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.rse.2016.05.008","article-title":"Error decomposition of nine passive and active microwave satellite soil moisture data sets over Australia","volume":"182","author":"Su","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.rse.2016.02.058","article-title":"Simultaneous assimilation of SMOS soil moisture and atmospheric CO2 in-situ observations to constrain the global terrestrial carbon cycle","volume":"180","author":"Scholze","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.rse.2018.02.010","article-title":"CCI soil moisture assessment with SMOS soil moisture and in situ data under different environmental conditions and spatial scales in Spain","volume":"225","author":"Sanchez","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_9","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_10","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.jhydrol.2016.02.037","article-title":"Multi-objective calibration of a hydrologic model using spatially distributed remotely sensed\/in-situ soil moisture","volume":"536","author":"Rajib","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1016\/j.rse.2017.01.021","article-title":"Validation of SMAP surface soil moisture products with core validation sites","volume":"191","author":"Colliander","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"9273","DOI":"10.1002\/2015WR016944","article-title":"Optimal averaging of soil moisture predictions from ensemble land surface model simulations","volume":"51","author":"Crow","year":"2015","journal-title":"Water Resour. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2959","DOI":"10.1109\/TGRS.2017.2656859","article-title":"A Comparative Study of the SMAP Passive Soil Moisture Product with Existing Satellite-Based Soil Moisture Products","volume":"55","author":"Burgin","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/j.rse.2019.02.008","article-title":"Assessment and inter-comparison of recently developed\/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements","volume":"224","author":"Wigneron","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2015.11.011","article-title":"Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy. Part 1: Satellite data analysis","volume":"173","author":"Kolassa","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.pce.2015.02.009","article-title":"Surface soil moisture retrievals from remote sensing: Current status, products & future trends","volume":"83","author":"Petropoulos","year":"2015","journal-title":"Phys. Chem. Earth Parts A\/B\/C"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.rse.2017.01.024","article-title":"Modelling the passive microwave signature from land surfaces: A review of recent results and application to the L-band SMOS & SMAP soil moisture retrieval algorithms","volume":"192","author":"Wigneron","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_18","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_19","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.rse.2016.10.050","article-title":"Does AMSR2 produce better soil moisture retrievals than AMSR-E over Australia?","volume":"188","author":"Cho","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.rse.2015.02.002","article-title":"A global comparison of alternate AMSR2 soil moisture products: Why do they differ?","volume":"161","author":"Kim","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_21","unstructured":"Entekhabi, D., Yueh, S., O\u2019Neill, P.E., Kellogg, K.H., Allen, A., Bindlish, R., Brown, M., Chan, S., Colliander, A., and Crow, W.T. (2014). SMAP Handbook\u2014Soil Moisture Active Passive: Mapping Soil Moisture and Freeze\/Thaw from Space, JPL Publication."},{"key":"ref_22","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_23","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.jhydrol.2016.03.060","article-title":"On the identification of representative in situ soil moisture monitoring stations for the validation of SMAP soil moisture products in Australia","volume":"537","author":"Yee","year":"2016","journal-title":"J. Hydrol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4994","DOI":"10.1109\/TGRS.2016.2561938","article-title":"Assessment of the SMAP Passive Soil Moisture Product","volume":"54","author":"Chan","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/j.rse.2014.07.023","article-title":"Evaluation of the ESA CCI soil moisture product using ground-based observations","volume":"162","author":"Dorigo","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.rse.2015.05.011","article-title":"Comparison of in-situ, aircraft, and satellite land surface temperature measurements over a NOAA Climate Reference Network site","volume":"165","author":"Krishnan","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2018.05.008","article-title":"Global-scale evaluation of SMAP, SMOS and ASCAT soil moisture products using triple collocation","volume":"214","author":"Chen","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_28","first-page":"96","article-title":"Evaluating ESA CCI soil moisture in East Africa","volume":"48","author":"McNally","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_29","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_30","doi-asserted-by":"crossref","unstructured":"Crow, W.T., Berg, A.A., Cosh, M.H., Loew, A., Mohanty, B.P., Panciera, R., De Rosnay, P., Ryu, D., and Walker, J.P. (2012). Upscaling sparse ground-based soil moisture observations for the validation of coarse-resolution satellite soil moisture products. Rev. Geophys., 50.","DOI":"10.1029\/2011RG000372"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1423","DOI":"10.1175\/2010JHM1285.1","article-title":"Estimating Spatial Sampling Errors in Coarse-Scale Soil Moisture Estimates Derived from Point-Scale Observations","volume":"11","author":"MirallesiD","year":"2010","journal-title":"J. Hydrometeorol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.rse.2015.10.028","article-title":"Triple collocation: Beyond three estimates and separation of structural\/non-structural errors","volume":"171","author":"Pan","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"6229","DOI":"10.1002\/2014GL061322","article-title":"Extended triple collocation: Estimating errors and correlation coefficients with respect to an unknown target","volume":"41","author":"McColl","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1109\/JSTARS.2016.2569998","article-title":"Application of Triple Collocation in Ground-Based Validation of Soil Moisture Active\/Passive (SMAP) Level 2 Data Products","volume":"10","author":"Chen","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2605","DOI":"10.5194\/hess-14-2605-2010","article-title":"Error characterisation of global active and passive microwave soil moisture datasets","volume":"14","author":"Dorigo","year":"2010","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1002\/2017GL075733","article-title":"Irrigation Signals Detected From SMAP Soil Moisture Retrievals","volume":"44","author":"Lawston","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4463","DOI":"10.5194\/hess-19-4463-2015","article-title":"Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled processes","volume":"19","author":"Kumar","year":"2015","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"752","DOI":"10.1016\/j.scitotenv.2016.10.116","article-title":"Spatio-temporal analysis of drought in a typical plain region based on the soil moisture anomaly percentage index","volume":"576","author":"Mao","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.jhydrol.2018.09.018","article-title":"An advanced error correction methodology for merging in-situ observed and model-based soil moisture","volume":"566","author":"Wu","year":"2018","journal-title":"J. Hydrol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"293","DOI":"10.5194\/essd-9-293-2017","article-title":"The global SMOS Level 3 daily soil moisture and brightness temperature maps","volume":"9","author":"Mialon","year":"2017","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.rse.2017.03.010","article-title":"Evaluating soil moisture retrievals from ESA\u2019s SMOS and NASA\u2019s SMAP brightness temperature datasets","volume":"193","author":"Wigneron","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_42","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_43","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.rse.2016.04.006","article-title":"Global-scale surface roughness effects at L-band as estimated from SMOS observations","volume":"181","author":"Parrens","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"614","DOI":"10.1016\/j.rse.2014.07.013","article-title":"Global-scale comparison of passive (SMOS) and active (ASCAT) satellite based microwave soil moisture retrievals with soil moisture simulations (MERRA-Land)","volume":"152","author":"Wigneron","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.rse.2016.02.045","article-title":"SMOS disaggregated soil moisture product at 1 km resolution: Processor overview and first validation results","volume":"180","author":"Molero","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1016\/j.rse.2015.10.033","article-title":"Assimilation of SMOS soil moisture and brightness temperature products into a land surface model","volume":"180","author":"Lievens","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"15388","DOI":"10.3390\/rs71115388","article-title":"Quality Assessment of the CCI ECV Soil Moisture Product Using ENVISAT ASAR Wide Swath Data over Spain, Ireland and Finland","volume":"7","author":"Pratola","year":"2015","journal-title":"Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"14415","DOI":"10.1029\/94JD00483","article-title":"A simple hydrologically based model of land surface water and energy fluxes for general circulation models","volume":"99","author":"Liang","year":"1994","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.jhydrol.2014.02.027","article-title":"Evaluation of multi-model simulated soil moisture in NLDAS-2","volume":"512","author":"Xia","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.rse.2013.02.023","article-title":"Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data","volume":"134","author":"Zhang","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"111380","DOI":"10.1016\/j.rse.2019.111380","article-title":"The SMAP and Copernicus Sentinel 1A\/B microwave active-passive high resolution surface soil moisture product","volume":"233","author":"Das","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.rse.2016.01.010","article-title":"Triple collocation for binary and categorical variables: Application to validating landscape freeze\/thaw retrievals","volume":"176","author":"McColl","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_53","first-page":"200","article-title":"Recent advances in (soil moisture) triple collocation analysis","volume":"45","author":"Gruber","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.rse.2013.06.013","article-title":"Estimating root mean square errors in remotely sensed soil moisture over continental scale domains","volume":"137","author":"Draper","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Draper, C., Reichle, R.H., De Lannoy, G.J.M., and Liu, Q. (2012). Assimilation of passive and active microwave soil moisture retrievals. Geophys. Res. Lett., 39.","DOI":"10.1029\/2011GL050655"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"750","DOI":"10.1175\/JHM-D-10-05000.1","article-title":"The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates in a land data assimilation system","volume":"12","author":"Liu","year":"2011","journal-title":"J. Hydrometeorol."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.rse.2016.01.013","article-title":"Status of Radio Frequency Interference (RFI) in the 1400\u20131427 MHz passive band based on six years of SMOS mission","volume":"180","author":"Oliva","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.rse.2019.01.015","article-title":"A comprehensive validation of the SMAP Enhanced Level-3 Soil Moisture product using ground measurements over varied climates and landscapes","volume":"223","author":"Zhang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_59","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":"Leroux","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/JSTARS.2015.2417832","article-title":"The Impact of National Land Cover and Soils Data on SMOS Soil Moisture Retrieval Over Canadian Agricultural Landscapes","volume":"8","author":"Pacheco","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_61","first-page":"17","article-title":"Comparison of temporal trends from multiple soil moisture data sets and precipitation: The implication of irrigation on regional soil moisture trend","volume":"48","author":"Qiu","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"4490","DOI":"10.1109\/JSTARS.2013.2296899","article-title":"Mapping Irrigated Areas in China From Remote Sensing and Statistical Data","volume":"7","author":"Zhu","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_63","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_64","unstructured":"Jackson, T., O\u2019Neill, P., Chan, S., Bindlish, R., Colliander, A., Chen, F., Dunbar, S., Piepmeier, J., Misra, S., and Cosh, M. (2019). Calibration and Validation for the L2\/3_SM_P Version 6 and L2\/3_SM_P_E Version 3 Data Products, Jet Propulsion Laboratory. SMAP Project, JPL D-56297."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/14\/2275\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:48:47Z","timestamp":1760176127000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/14\/2275"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,15]]},"references-count":64,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2020,7]]}},"alternative-id":["rs12142275"],"URL":"https:\/\/doi.org\/10.3390\/rs12142275","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,15]]}}}