{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T20:15:17Z","timestamp":1771272917572,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2016,1,29]],"date-time":"2016-01-29T00:00:00Z","timestamp":1454025600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"publisher","award":["2013CB733406"],"award-info":[{"award-number":["2013CB733406"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"publisher","award":["2013CB733403"],"award-info":[{"award-number":["2013CB733403"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41171260"],"award-info":[{"award-number":["41171260"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Land surface temperature (LST) plays a major role in the study of surface energy balances. Remote sensing techniques provide ways to monitor LST at large scales. However, due to atmospheric influences, significant missing data exist in LST products retrieved from satellite thermal infrared (TIR) remotely sensed data. Although passive microwaves (PMWs) are able to overcome these atmospheric influences while estimating LST, the data are constrained by low spatial resolution. In this study, to obtain complete and high-quality LST data, the Bayesian Maximum Entropy (BME) method was introduced to merge 0.01\u00b0 and 0.25\u00b0 LSTs inversed from MODIS and AMSR-E data, respectively. The result showed that the missing LSTs in cloudy pixels were filled completely, and the availability of merged LSTs reaches 100%. Because the depths of LST and soil temperature measurements are different, before validating the merged LST, the station measurements were calibrated with an empirical equation between MODIS LST and 0~5 cm soil temperatures. The results showed that the accuracy of merged LSTs increased with the increasing quantity of utilized data, and as the availability of utilized data increased from 25.2% to 91.4%, the RMSEs of the merged data decreased from 4.53 \u00b0C to 2.31 \u00b0C. In addition, compared with the filling gap method in which MODIS LST gaps were filled with AMSR-E LST directly, the merged LSTs from the BME method showed better spatial continuity. The different penetration depths of TIR and PMWs may influence fusion performance and still require further studies.<\/jats:p>","DOI":"10.3390\/rs8020105","type":"journal-article","created":{"date-parts":[[2016,1,29]],"date-time":"2016-01-29T09:58:48Z","timestamp":1454061528000},"page":"105","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":81,"title":["Estimation of Land Surface Temperature through Blending MODIS and AMSR-E Data with the Bayesian Maximum Entropy Method"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1685-3166","authenticated-orcid":false,"given":"Xiaokang","family":"Kou","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Research Center for Remote Sensing and GIS, and School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"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, Research Center for Remote Sensing and GIS, and School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanchen","family":"Bo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Research Center for Remote Sensing and GIS, and School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuang","family":"Yan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Research Center for Remote Sensing and GIS, and School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8295-8973","authenticated-orcid":false,"given":"Linna","family":"Chai","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Research Center for Remote Sensing and GIS, and School of Geography, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,1,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/S0034-4257(96)00216-7","article-title":"Estimation of air temperature from remotely sensed surface observations","volume":"60","author":"Prihodko","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_2","unstructured":"Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M., and Miller, H.L. (2007). Climate Change 2007: The Physical Science Basis, Cambridge University Press."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1559","DOI":"10.1002\/(SICI)1097-0088(19971130)17:14<1559::AID-JOC211>3.0.CO;2-5","article-title":"Mapping regional air temperature fields using satellite-derived surface skin temperatures","volume":"17","author":"Vogt","year":"1997","journal-title":"Int. J. Climatol."},{"key":"ref_4","first-page":"96","article-title":"Progress in land surface temperature retrieval from passive microwave remotely sensed data","volume":"25","author":"Jia","year":"2006","journal-title":"Prog. Geogr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1109\/JSTARS.2010.2070871","article-title":"Maximum nighttime urban heat island (UHI) intensity simulation by integrating remotely sensed data and meteorological observations","volume":"4","author":"Zhou","year":"2011","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0022-1694(02)00110-5","article-title":"Estimation models for precipitation in mountainous regions: The use of GIS and multivariate analysis","volume":"270","author":"Lastra","year":"2003","journal-title":"J. Hydrol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.rse.2012.12.008","article-title":"Satellite-derived land surface temperature: Current status and perspectives","volume":"131","author":"Li","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1080\/01431160050505900","article-title":"Land surface air temperature mapping using TOVS and AVHRR","volume":"22","author":"Lakshmi","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1109\/TGRS.2002.808356","article-title":"AIRS\/AMSU\/HSB on the Aqua mission: Design, science objectives, data products, and processing systems","volume":"41","author":"Aumann","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2582","DOI":"10.1080\/01431161.2011.617396","article-title":"Intercomparison of methods for estimating land surface temperature from a Landsat-5 TM image in an arid region with low water vapour in the atmosphere","volume":"33","author":"Zhou","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.rse.2007.02.025","article-title":"Estimation of diurnal air temperature using MSG SEVIRI data in West Africa","volume":"110","author":"Stisen","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1016\/j.rse.2009.10.002","article-title":"Evaluation of MODIS land surface temperature data to estimate air temperature in different ecosystems over Africa","volume":"114","author":"Vancutsem","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"4541","DOI":"10.1080\/01431160310001657533","article-title":"Neural network estimation of air temperatures from AVHRR data","volume":"25","author":"Jang","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3892","DOI":"10.1080\/01431161.2014.919674","article-title":"Near-surface air temperature retrieval from Chinese Geostationary FengYun Meteorological Satellite (FY-2C) data","volume":"35","author":"Guo","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2563","DOI":"10.1080\/01431160110115041","article-title":"Land surface temperature and emissivity estimation from passive sensor data: Theory and practice\u2014Current trends","volume":"23","author":"Dash","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"892","DOI":"10.1109\/36.508406","article-title":"A generalized split-window algorithm for retrieving land-surface temperature from space","volume":"34","author":"Wan","year":"1996","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1109\/36.700995","article-title":"Temperature emissivity separation from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images","volume":"36","author":"Gillespie","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3719","DOI":"10.1080\/01431160010006971","article-title":"A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel\u2013Egypt border region","volume":"22","author":"Qin","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"61","DOI":"10.3724\/SP.J.1010.2011.00061","article-title":"A modified single channel algorithm for land surface temperature retrieval from HJ-1B satellite data","volume":"30","author":"Zhou","year":"2011","journal-title":"J. Infrared Millim. Waves"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1080\/01431169008955028","article-title":"Towards a local split window method over land surfaces","volume":"11","author":"Becker","year":"1990","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3521","DOI":"10.1080\/01431160110063788","article-title":"On the relationship between thermodynamic surface temperature and high-frequency (37 GHz) vertically polarized bright-ness temperature under semi-arid conditions","volume":"22","author":"Owe","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1109\/36.58971","article-title":"Land surface temperature derived from the SSM\/I passive microwave brightness temperatures","volume":"28","author":"Mcfarland","year":"1990","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Holmes, T.R.H., de Jeu, R.A.M., Owe, M., and Dolman, A.J. (2009). Land surface temperature from Ka band (37 GHz) passive microwave observations. J. Geophys. Res., 114.","DOI":"10.1029\/2008JD010257"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Royer, A., and Poirier, S. (2010). Surface temperature spatial and temporal variations in North America from homogenized satellite SMMR-SSM\/I microwave measurements and reanalysis for 1979\u20132008. J. Geophys. Res., 115.","DOI":"10.1029\/2009JD012760"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/S0034-4257(01)00308-X","article-title":"Using microwave brightness temperature to detect short-term surface air temperature changes in Antarctica: An analytical approach","volume":"80","author":"Surdyk","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1175\/1520-0450(1998)037<0888:UTSSMI>2.0.CO;2","article-title":"Using the Special Sensor Microwave\/Imager to monitor land surface temperatures, wetness, and snow cover","volume":"37","author":"Basist","year":"1998","journal-title":"J. Appl. Meteorol."},{"key":"ref_27","unstructured":"Seemann, S.W., Borbas, E.E., Li, J., Menzel, W.P., and Gumley, L.E. (2006). MODIS Atmospheric Profile Retrieval Algorithm Theoretical Basis Document, NASA."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1109\/JSTARS.2010.2041530","article-title":"Satellite microwave remote sensing of daily land surface air temperature minima and maxima from AMSR-E","volume":"3","author":"Jones","year":"2010","journal-title":"IEEE J. Sel. Top. Appl. Earth Obser. Remote Sens."},{"key":"ref_29","first-page":"140","article-title":"A simple retrieval method of land surface temperature from AMSR-E passive microwave data\u2014A case study over Southern China during the strong snow disaster of 2008","volume":"13","author":"Chen","year":"2011","journal-title":"Int. J. Appl. Earth Observ. Geoinf."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.rse.2005.03.014","article-title":"Estimation of the net radiation using MODIS (moderate resolution imaging spectroradiometer) data for clear sky days","volume":"97","author":"Bisht","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2006.02.019","article-title":"Estimation and comparison of evapotranspiration from MODIS and AVHRR sensors for clear sky days over the Southern Great Plains","volume":"103","author":"Batra","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_32","first-page":"35","article-title":"Developing a temporally land cover-based look-up table (TL-LUT) method for estimating land surface temperature based on AMSR-E data over the Chinese landmass","volume":"34","author":"Zhou","year":"2015","journal-title":"Int. J. Appl. Earth Observ. Geoinf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1002\/ppp.672","article-title":"Using the MODIS land surface temperature product for mapping permafrost: An application to Northern Quebec and Labrador, Canada","volume":"20","author":"Hachem","year":"2009","journal-title":"Permafr. Periglac. Processes"},{"key":"ref_34","unstructured":"Ran, Y.H., Li, X., and Jin, R. (2012, January 25\u201329). Estimation of the mean annual surface temperature and surface frost number using the MODIS land surface temperature products for mapping permafrost in China. Proceedings of the Tenth International Conference on Permafrost (TICOP), Salekhard, Russia."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"GB4017","DOI":"10.1029\/2011GB004053","article-title":"Integration of MODIS land and atmosphere products with a coupled process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales","volume":"25","author":"Ryu","year":"2011","journal-title":"Glob. Biogeochem. Cycle"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1522","DOI":"10.1016\/j.rse.2010.02.007","article-title":"Estimation of net radiation from the MODIS data under all sky conditions: Southern Great Plains case study","volume":"114","author":"Bisht","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1002\/2013JD020639","article-title":"Monitoring daily evapotranspiration in Northeast Asia using MODIS and a regional Land Data Assimilation System","volume":"118","author":"Jang","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"8387","DOI":"10.3390\/rs6098387","article-title":"Retrievals of all-weather daily air temperature using MODIS and AMSR-E data","volume":"6","author":"Jang","year":"2014","journal-title":"Remote Sens."},{"key":"ref_39","unstructured":"Christakos, G. (2000). Modern Spatiotemporal Geostatistics, Oxford University Press."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3393","DOI":"10.1016\/S1352-2310(00)00080-7","article-title":"BME analysis of spatiotemporal particulate matter distributions in North Carolina","volume":"34","author":"Christakos","year":"2000","journal-title":"Atmos. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2471","DOI":"10.1016\/j.atmosenv.2009.01.049","article-title":"Spatiotemporal modelling of ozone distribution in the State of California","volume":"43","author":"Bogaert","year":"2009","journal-title":"Atmos. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1109\/TGRS.2003.822751","article-title":"Total ozone mapping by integrating databases from remote sensing instruments and empirical models","volume":"42","author":"Christakos","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s004770000057","article-title":"Application of the BME approach to soil texture mapping","volume":"15","author":"Bogaert","year":"2001","journal-title":"Stoch. Environ. Res. Risk Assess."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1629","DOI":"10.2136\/sssaj2006.0083","article-title":"Statistical methods for evaluating soil salinity spatial and temporal variability","volume":"71","author":"Douaik","year":"2007","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1080\/00045600701851184","article-title":"Bayesian maximum entropy mapping and the soft data problem in urban climate research","volume":"98","author":"Lee","year":"2008","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.rse.2013.03.021","article-title":"Blending multi-resolution satellite sea surface temperature (SST) products using Bayesian maximum entropy method","volume":"135","author":"Li","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1175\/JHM609.1","article-title":"The influence of mechanical and thermal forcing by the Tibetan Plateau on Asian climate","volume":"8","author":"Wu","year":"2007","journal-title":"J. Hydrometeorol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1525","DOI":"10.1175\/2010JCLI3848.1","article-title":"On the climatology and trend of the atmospheric heat source over the Tibetan Plateau: An experiments-supported revisit","volume":"24","author":"Yang","year":"2011","journal-title":"J. Clim."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.rse.2006.06.026","article-title":"New refinements and validation of the MODIS land-surface temperature\/emissivity products","volume":"112","author":"Wan","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_50","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_51","unstructured":"Christakos, G. (1992). Random Field Models in Earth Sciences, Academic Press."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1105","DOI":"10.1016\/j.agrformet.2009.01.008","article-title":"Can spatio-temporal geostatistical methods improve high resolution regionalisation of meteorological variables?","volume":"149","author":"Spadavecchia","year":"2009","journal-title":"Agric. For. Meteorol."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Olea, R.A. (1999). Geostatistics for Engineers and Earth Scientists, Springer Science+Business Media.","DOI":"10.1007\/978-1-4615-5001-3"},{"key":"ref_54","first-page":"637","article-title":"A RANSAC-based approach to model fitting and its application to finding cylinders in range data","volume":"1981","author":"Bolles","year":"1981","journal-title":"IJCAI"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/2\/105\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:18:32Z","timestamp":1760210312000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/2\/105"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,1,29]]},"references-count":54,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2016,2]]}},"alternative-id":["rs8020105"],"URL":"https:\/\/doi.org\/10.3390\/rs8020105","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,1,29]]}}}