{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:44:25Z","timestamp":1760240665897,"version":"build-2065373602"},"reference-count":67,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2019,7,31]],"date-time":"2019-07-31T00:00:00Z","timestamp":1564531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Strategic Priority Research Program of the Chinese Academy of Sciences","award":["No. XDA20100101"],"award-info":[{"award-number":["No. XDA20100101"]}]},{"name":"the Natural Science Fund of China","award":["No. 41671331"],"award-info":[{"award-number":["No. 41671331"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>An accurate and spatially continuous estimation of terrestrial latent heat flux (LE) is crucial to the management and planning of water resources for arid and semi-arid areas, for which LE estimations from different satellite sensors unfortunately often contain data gaps and are inconsistent. Many integration approaches have been implemented to overcome these limitations; however, most suffer from either the persistent bias of relying on datasets at only one resolution or the spatiotemporal inconsistency of LE products. In this study, we exhibit an integration case in the midstream of the Heihe River Basin of northwest China by using a multi-resolution Kalman filter (MKF) method to develop continuous and consistent LE maps from satellite LE datasets across different resolutions. The Moderate Resolution Imaging Spectroradiometer (MODIS) LE product (MOD16), the Landsat-based LE product derived from the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor, and ground observations of eddy covariance flux tower from June to September 2012 are used. The integrated results illustrate that data gaps of MOD16 dropped to less than 0.4% from the original 27\u201352%, and the root-mean-square error (RMSE) between the LE products decreased by 50.7% on average. Our findings indicate that the MKF method has excellent capacity to fill data gaps, reduce uncertainty, and improve the consistency of multiple LE datasets at different resolutions.<\/jats:p>","DOI":"10.3390\/rs11151787","type":"journal-article","created":{"date-parts":[[2019,7,31]],"date-time":"2019-07-31T11:37:07Z","timestamp":1564573027000},"page":"1787","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Integrating Latent Heat Flux Products from MODIS and Landsat Data Using Multi-Resolution Kalman Filter Method in the Midstream of Heihe River Basin of Northwest China"],"prefix":"10.3390","volume":"11","author":[{"given":"Jia","family":"Xu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3803-8170","authenticated-orcid":false,"given":"Yunjun","family":"Yao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Kanran","family":"Tan","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21218, USA"}]},{"given":"Yufu","family":"Li","sequence":"additional","affiliation":[{"name":"Jincheng Meteorological Administration, Jincheng 048026, China"}]},{"given":"Shaomin","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7564-6509","authenticated-orcid":false,"given":"Ke","family":"Shang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8586-4243","authenticated-orcid":false,"given":"Kun","family":"Jia","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Xiaotong","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Xiaowei","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1910-4286","authenticated-orcid":false,"given":"Xiangyi","family":"Bei","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1109\/JSTARS.2010.2048556","article-title":"Review on Estimation of Land Surface Radiation and Energy Budgets From Ground Measurement, Remote Sensing and Model Simulations","volume":"3","author":"Liang","year":"2010","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"5211","DOI":"10.1002\/2016JD026370","article-title":"A simple temperature domain two-source model for estimating agricultural field surface energy fluxes from Landsat images","volume":"122","author":"Yao","year":"2017","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1029\/2006JD008010","article-title":"Trend of estimated actual evapotranspiration over China during 1960\u20132002","volume":"112","author":"Gao","year":"2007","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"RG2005","DOI":"10.1029\/2011RG000373","article-title":"A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability","volume":"50","author":"Wang","year":"2012","journal-title":"Rev. Geophys."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.13031\/2013.23965","article-title":"Evapotranspiration: Progress in Measurement and Modeling in Agriculture","volume":"50","author":"Farahani","year":"2007","journal-title":"Trans. ASABE"},{"doi-asserted-by":"crossref","unstructured":"Cheng, J., and Kustas, W.P. (2019). Using Very High Resolution Thermal Infrared Imagery for More Accurate Determination of the Impact of Land Cover Differences on Evapotranspiration in an Irrigated Agricultural Area. Remote Sens., 11.","key":"ref_6","DOI":"10.3390\/rs11060613"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1061\/(ASCE)0733-9437(2005)131:1(85)","article-title":"SEBAL Model with Remotely Sensed Data to Improve Water-Resources Management under Actual Field Conditions","volume":"131","author":"Bastiaanssen","year":"2005","journal-title":"J. Irrig. Drain. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.agrformet.2013.09.003","article-title":"A review of approaches for evapotranspiration partitioning","volume":"184","author":"Kool","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1416","DOI":"10.1016\/j.rse.2010.01.022","article-title":"Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data","volume":"114","author":"Yuan","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1646","DOI":"10.1016\/j.agrformet.2009.05.006","article-title":"Latent heat flux estimation in clear sky days over Indian agroecosystems using noontime satellite remote sensing data","volume":"149","author":"Mallick","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.agrformet.2016.04.008","article-title":"Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces","volume":"230\u2013231","author":"Liu","year":"2016","journal-title":"Agric. For. Meteorol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"13113","DOI":"10.1029\/2011JD017037","article-title":"Validation of remotely sensed evapotranspiration over the Hai River Basin, China","volume":"117","author":"Jia","year":"2012","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.agrformet.2017.04.011","article-title":"Improving global terrestrial evapotranspiration estimation using support vector machine by integrating three process-based algorithms","volume":"242","author":"Yao","year":"2017","journal-title":"Agric. For. Meteorol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4953","DOI":"10.1080\/01431161.2015.1040136","article-title":"Integrating two layers of soil moisture parameters into the MOD16 algorithm to improve evapotranspiration estimations","volume":"36","author":"Di","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3026","DOI":"10.1002\/grl.50450","article-title":"Remote estimation of terrestrial evapotranspiration without using meteorological data","volume":"40","author":"Yang","year":"2013","journal-title":"Geophys. Res. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1016\/j.jhydrol.2015.09.050","article-title":"An evapotranspiration product for arid regions based on the three-temperature model and thermal remote sensing","volume":"530","author":"Xiong","year":"2015","journal-title":"J. Hydrol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"8674","DOI":"10.1029\/2018JD028447","article-title":"Evaluating Different Machine Learning Methods for Upscaling Evapotranspiration from Flux Towers to the Regional Scale","volume":"123","author":"Tongren","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1016\/j.rse.2018.07.019","article-title":"Estimation of daily evapotranspiration and irrigation water efficiency at a Landsat-like scale for an arid irrigation area using multi-source remote sensing data","volume":"216","author":"Ma","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1093\/nsr\/nwu017","article-title":"Integrated study of the water\u2013ecosystem\u2013economy in the Heihe River Basin","volume":"1","author":"Cheng","year":"2014","journal-title":"Natl. Sci. Rev."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"890","DOI":"10.1002\/2017JD027889","article-title":"Hydrological Cycle in the Heihe River Basin and Its Implication for Water Resource Management in Endorheic Basins","volume":"123","author":"Li","year":"2018","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4521","DOI":"10.1002\/2013JD020864","article-title":"Bayesian multimodel estimation of global terrestrial latent heat flux from eddy covariance, meteorological, and satellite observations","volume":"119","author":"Yao","year":"2014","journal-title":"J. Geophys. Res. Atmos."},{"doi-asserted-by":"crossref","unstructured":"Feng, F., Li, X., Yao, Y., Liang, S., Chen, J., Zhao, X., Jia, K., Pint\u00e9r, K., and Mccaughey, J.H. (2016). An Empirical Orthogonal Function-Based Algorithm for Estimating Terrestrial Latent Heat Flux from Eddy Covariance, Meteorological and Satellite Observations. PLoS ONE, 11.","key":"ref_22","DOI":"10.1371\/journal.pone.0160150"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1016\/j.rse.2007.06.025","article-title":"Global estimates of the land\u2013atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites","volume":"112","author":"Fisher","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1109\/9.280747","article-title":"Multiscale systems, Kalman filters, and Riccati equations","volume":"39","author":"Chou","year":"1992","journal-title":"Autom. Control. IEEE Trans."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"3428","DOI":"10.1109\/TGRS.2013.2272935","article-title":"Fusion of Satellite Land Surface Albedo Products Across Scales Using a Multiresolution Tree Method in the North Central United States","volume":"52","author":"He","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","first-page":"1027","article-title":"Using multiresolution tree to integrate MODIS and MISR-L3 LAI products","volume":"38","author":"Wang","year":"2010","journal-title":"IEEE Int. Geosci. Remote Sens. Symp."},{"key":"ref_27","first-page":"406","article-title":"Water Issue and Its Countermeasure in the Inland River Basins of Northwest China\u2014A Case Study in Heihe River Basin","volume":"28","author":"Cheng","year":"2006","journal-title":"J. Glaciol. Geocryol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.jhydrol.2011.10.024","article-title":"Global review and synthesis of trends in observed terrestrial near-surface wind speeds: Implications for evaporation","volume":"416","author":"Mcvicar","year":"2012","journal-title":"J. Hydrol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"170083","DOI":"10.1038\/sdata.2017.83","article-title":"A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system","volume":"4","author":"Li","year":"2017","journal-title":"Sci. Data"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"13140","DOI":"10.1002\/2013JD020260","article-title":"Intercomparison of surface energy flux measurement systems used during the HiWATER-MUSOEXE","volume":"118","author":"Xu","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1175\/BAMS-D-12-00154.1","article-title":"Heihe watershed allied telemetry experimental research (HiWater) scientific objectives and experimental design (EI)","volume":"94","author":"Li","year":"2013","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/S0168-1923(00)00123-4","article-title":"Correcting eddy-covariance flux underestimates over a grassland","volume":"103","author":"Twine","year":"2000","journal-title":"Agric. For. Meteorol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.jhydrol.2013.02.025","article-title":"Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China","volume":"487","author":"Liu","year":"2013","journal-title":"J. Hydrol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"180072","DOI":"10.2136\/vzj2018.04.0072","article-title":"The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China","volume":"17","author":"Liu","year":"2018","journal-title":"Vadose Zone J."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1016\/j.rse.2007.04.015","article-title":"Development of a global evapotranspiration algorithm based on MODIS and global meteorology data","volume":"111","author":"Mu","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1016\/j.rse.2011.02.019","article-title":"Improvements to a MODIS global terrestrial evapotranspiration algorithm","volume":"115","author":"Mu","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_37","first-page":"205","article-title":"Evaporation and environment","volume":"19","author":"Monteith","year":"1965","journal-title":"Symp. Soc. Exp. Biol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.rse.2006.07.007","article-title":"Regional evaporation estimates from flux tower and MODIS satellite data","volume":"106","author":"Cleugh","year":"2007","journal-title":"Remote Sens. Environ."},{"unstructured":"Running, S., Mu, Q., and Zhao, M. (2017). MOD16A2 MODIS\/Terra Net Evapotranspiration 8-Day L4 Global 500m SIN Grid V006. NASA EOSDIS Land Process. DAAC.","key":"ref_39"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/LGRS.2005.857030","article-title":"A Landsat surface reflectance dataset for North America, 1990\u20132000","volume":"3","author":"Masek","year":"2006","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.agrformet.2012.11.016","article-title":"MODIS-driven estimation of terrestrial latent heat flux in China based on a modified Priestley\u2013Taylor algorithm","volume":"171\u2013172","author":"Yao","year":"2013","journal-title":"Agric. For. Meteorol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.agrformet.2009.08.004","article-title":"On downward shortwave and longwave radiations over high altitude regions: Observation and modeling in the Tibetan Plateau","volume":"150","author":"Yang","year":"2010","journal-title":"Agric. For. Meteorol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"D20104","DOI":"10.1029\/2011JD015921","article-title":"Improving land surface temperature modeling for dry land of China","volume":"116","author":"Chen","year":"2011","journal-title":"J. Geophys. Res. Atmos."},{"doi-asserted-by":"crossref","unstructured":"Zhang, L., Yao, Y., Wang, Z., Jia, K., and Chen, X. (2017). Satellite-Derived Spatiotemporal Variations in Evapotranspiration over Northeast China during 1982\u20132010. Remote Sens., 9.","key":"ref_44","DOI":"10.3390\/rs9111140"},{"key":"ref_45","first-page":"D08104","article-title":"Scale-recursive estimation for merging precipitation data from radar and microwave cross-track scanners","volume":"114","author":"Vyver","year":"2009","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_46","first-page":"D02102","article-title":"A methodology for merging multisensor precipitation estimates based on expectation-maximization and scale-recursive estimation","volume":"111","author":"Gupta","year":"2015","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1109\/83.342185","article-title":"Likelihood calculation for a class of multiscale stochastic models, with application to texture discrimination","volume":"4","author":"Luettgen","year":"1995","journal-title":"IEEE Trans. Image Process."},{"unstructured":"Chou, C.K. (1991). A Stochastic Modeling Approach to Multiscale Signal Processing. Mass. Inst. Technol., Available online: https:\/\/pdfs.semanticscholar.org\/6350\/caa3c42a2c12b0342706fe53197820d58ade.pdf.","key":"ref_48"},{"doi-asserted-by":"crossref","unstructured":"Tustison, B., Foufoula-Georgiou, E., and Harris, D. (2002). Scale-recursive estimation for multisensor Quantitative Precipitation Forecast verification: A preliminary assessment. J. Geophys. Res. Atmos., 107, CIP-1-CIP 2\u201314.","key":"ref_49","DOI":"10.1029\/2001JD001073"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1016\/S0309-1708(01)00033-1","article-title":"Scale-recursive assimilation of precipitation data","volume":"24","author":"Gorenburg","year":"2001","journal-title":"Adv. Water Resour."},{"key":"ref_51","first-page":"981","article-title":"On estimation and prediction for multivariate multiresolution tree-structured spatial linear models","volume":"16","author":"Yue","year":"2006","journal-title":"Stat. Sin."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1098","DOI":"10.1080\/17538947.2016.1170897","article-title":"Integrating ASTER and GLASS broadband emissivity products using a multi-resolution Kalman filter","volume":"9","author":"Shi","year":"2016","journal-title":"Int. J. Digit. Earth"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1071\/BT07151","article-title":"Breathing of the terrestrial biosphere: Lessons learned from a global network of carbon dioxide flux measurement systems","volume":"56","author":"Baldocchi","year":"2008","journal-title":"Aust. J. Bot."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"880","DOI":"10.3390\/rs6010880","article-title":"Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping Terrestrial Evapotranspiration","volume":"6","author":"Yao","year":"2014","journal-title":"Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.rse.2015.05.013","article-title":"A satellite-based hybrid algorithm to determine the Priestley-Taylor parameter for global terrestrial latent heat flux estimation across multiple biomes","volume":"165","author":"Yao","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"4227","DOI":"10.1016\/j.rse.2008.07.009","article-title":"A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales","volume":"112","author":"Anderson","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"3056","DOI":"10.3390\/rs70303056","article-title":"Monitoring of Evapotranspiration in a Semi-Arid Inland River Basin by Combining Microwave and Optical Remote Sensing Observations","volume":"7","author":"Hu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"135","DOI":"10.3390\/rs70100135","article-title":"The Performances of MODIS-GPP and -ET Products in China and Their Sensitivity to Input Data (FPAR\/LAI)","volume":"7","author":"Liu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.rse.2013.07.013","article-title":"A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: Using point and gridded FLUXNET and water balance ET","volume":"139","author":"Velpuri","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1007\/s12205-012-0006-1","article-title":"Validation of MODIS 16 global terrestrial evapotranspiration products in various climates and land cover types in Asia","volume":"16","author":"Kim","year":"2012","journal-title":"Ksce J. Civ. Eng."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1658","DOI":"10.1080\/02626667.2013.837578","article-title":"Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin","volume":"58","author":"Ruhoff","year":"2013","journal-title":"Int. Assoc. Sci. Hydrol. Bull."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1109\/LGRS.2014.2334703","article-title":"Assessment of uncertainties in eddy covariance flux measurement based on intensive flux matrix of HiWATER-MUSOEXE","volume":"12","author":"Wang","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/S0168-1923(02)00109-0","article-title":"Energy balance closure at FLUXNET sites","volume":"113","author":"Wilson","year":"2002","journal-title":"Agric. For. Meteorol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1023\/A:1021554900225","article-title":"A Re-Evaluation of Long-Term Flux Measurement Techniques Part I: Averaging and Coordinate Rotation","volume":"107","author":"Finnigan","year":"2003","journal-title":"Bound. Layer Meteorol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1109\/TGRS.1995.8746009","article-title":"Multiresolution optimal interpolation and statistical analysis of TOPEX\/POSEIDON satellite altimetry","volume":"33","author":"Fieguth","year":"1995","journal-title":"Geosci. Remote Sens. IEEE Trans."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1836","DOI":"10.1109\/78.845950","article-title":"ML parameter estimation of a multiscale stochastic process using the EM algorithm","volume":"48","author":"Kannan","year":"2002","journal-title":"IEEE Trans. Signal. Process."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.jhydrol.2009.09.047","article-title":"Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005","volume":"379","author":"Zhang","year":"2009","journal-title":"J. Hydrol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/15\/1787\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:11:27Z","timestamp":1760188287000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/15\/1787"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,31]]},"references-count":67,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2019,8]]}},"alternative-id":["rs11151787"],"URL":"https:\/\/doi.org\/10.3390\/rs11151787","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2019,7,31]]}}}