{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:46:54Z","timestamp":1760147214397,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,15]],"date-time":"2023-01-15T00:00:00Z","timestamp":1673740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"CNES funding"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The coming years will see the launch of several missions (TRISHNA, LSTM, SBG), which will acquire images in four or more spectral bands in thermal infrared (TIR) at high spatial resolution (~50\u201360 m) and with high temporal revisit (~2\u20133 days). The derivation of surface temperature and emissivity values from top-of-atmosphere radiances is not straightforward, as it is a non-deterministic process requiring additional information. In this paper, we propose the algorithm DirecTES to efficiently separate surface temperature and emissivity. This algorithm is based on the use of a comprehensive spectral database of emissivity, resulting in a well-posed deterministic problem while not assuming strong hypotheses. The algorithm can also benefit from non-TIR information, such as the acquisitions from the same satellite but in the visible and near-infrared domains, or exogenous data\u2014land\/sea mask or soil-occupation map. These would help identify the nature of the surface and therefore improve the temperature and emissivity retrievals. After the complete description of the method, we evaluate the performances of DirecTES on theoretical landscapes in TRISHNA\u2019s context under a large range of atmospheric conditions. The retrievals of surface temperature reach RMSEs of 0.8 K over vegetation and 0.5 K over water, including both sensor and atmospheric uncertainties. We then evaluate DirecTES on ECOSTRESS images on sites where the ECOSTRESS Land Surface Temperature (LST) performance has been documented; DirecTES surface temperature retrievals are consistent with the ECOSTRESS LST product and the in-situ data.<\/jats:p>","DOI":"10.3390\/rs15020517","type":"journal-article","created":{"date-parts":[[2023,1,16]],"date-time":"2023-01-16T04:31:32Z","timestamp":1673843492000},"page":"517","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["DirecTES: A Direct Method for Land and Sea Surface Temperature and Emissivity Separation for Thermal Infrared Sensors\u2014Application to TRISHNA and ECOSTRESS"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8460-9398","authenticated-orcid":false,"given":"S\u00e9bastien","family":"Marcq","sequence":"first","affiliation":[{"name":"Centre National d\u2019Etudes Spatiales (CNES), Department of Physics of Optical Measurement, 31400 Toulouse, France"}]},{"given":"Emilie","family":"Delogu","sequence":"additional","affiliation":[{"name":"Centre National d\u2019Etudes Spatiales (CNES), Department of Physics of Optical Measurement, 31400 Toulouse, France"}]},{"given":"Morgane","family":"Chapelier","sequence":"additional","affiliation":[{"name":"Centre National d\u2019Etudes Spatiales (CNES), Department of Physics of Optical Measurement, 31400 Toulouse, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9570-7583","authenticated-orcid":false,"given":"Thomas H. G.","family":"Vidal","sequence":"additional","affiliation":[{"name":"ACRI-ST, Sophia-Antipolis, 06904 Valbonne, France"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,15]]},"reference":[{"key":"ref_1","unstructured":"Belward, A. (2022, June 01). The Global Observing System for Climate: Implementation Needs, GCOS Steering Committee, Guayaquil, Ecuador. Available online: https:\/\/library.wmo.int\/doc_num.php?explnum_id=3417."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"4795","DOI":"10.1029\/2003JD004083","article-title":"A sensitivity study of climate and energy balance simulations with use of satellite-derived emissivity data over Northern Africa and the Arabian Peninsula","volume":"108","author":"Zhou","year":"2003","journal-title":"J. Geophys. Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.rse.2011.08.025","article-title":"Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources","volume":"122","author":"Anderson","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/0034-4257(92)90092-X","article-title":"Emissivity of terrestrial materials in the 8\u201314 \u03bcm atmospheric window","volume":"42","author":"Salisbury","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_5","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_6","doi-asserted-by":"crossref","unstructured":"Jacob, F., Schmugge, T., Olioso, A., French, A., Courault, D., Ogawa, K., Petitcolin, F., Chehbouni, G., Pinheiro, A., and Privette, J. (2008). Modeling and inversion in thermal infrared remote sensing over vegetated land surfaces. Advances in Land Remote Sensing, Springer.","DOI":"10.1007\/978-1-4020-6450-0_10"},{"key":"ref_7","unstructured":"Brown, O.B., Minnett, P.J., Evans, R., Kearns, E., Kilpatrick, K., Kumar, A., Sikorski, R., and Z\u00e1vody, A. (2022, June 01). MODIS Infrared Sea Surface Temperature Algorithm Algorithm Theoretical Basis Document Version 2.0, Available online: https:\/\/modis.gsfc.nasa.gov\/data\/atbd\/atbd_mod25.pdf."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1016\/0034-4257(88)90032-6","article-title":"Emissivity of pure and sea waters for the model sea surface in the infrared window regions","volume":"24","author":"Masuda","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1109\/36.700995","article-title":"A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images","volume":"36","author":"Gillespie","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Gillespie, A., Matsunaga, T., Rokugawa, S., and Hook, S.J. (1996, January 5\u20139). Temperature and Emissivity Separation from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Images. Proceedings of the SPIE\u2019s 1996 International Symposium on Optical Science, Engineering, and Instrumentation, Infrared Spaceborne Remote Sensing IV, Denver, CO, USA.","DOI":"10.1117\/12.255172"},{"key":"ref_11","first-page":"364","article-title":"Temperature and emissivity separation for multi-band radiometer and validation ASTER TES algorithm","volume":"23","author":"Sawabe","year":"2003","journal-title":"J. Remote Sens. Soc. Jpn."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.rse.2007.02.008","article-title":"Temperature and emissivity separation from ASTER data for low spectral contrast surfaces","volume":"110","author":"Coll","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3681","DOI":"10.1016\/j.rse.2011.09.007","article-title":"Residual errors in ASTER temperature and emissivity standard products AST08 and AST05","volume":"115","author":"Gillespie","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1967","DOI":"10.1016\/j.rse.2009.05.005","article-title":"The North American ASTER Land Surface Emissivity Database (NAALSED) Version 2.0","volume":"113","author":"Hulley","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1304","DOI":"10.1109\/TGRS.2010.2063034","article-title":"Generating consistent land surface temperature and emissivity products between ASTER and MODIS data for earth science research","volume":"49","author":"Hulley","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Berk, A., Conforti, P., Kennett, R., Perkins, T., Hawes, F., and van den Bosch, J. (2014, January 24\u201327). MODTRAN6: A major upgrade of the MODTRAN radiative transfer code. Proceedings of the 2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), Lausanne, Switzerland.","DOI":"10.1109\/WHISPERS.2014.8077573"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2717","DOI":"10.5194\/gmd-11-2717-2018","article-title":"An update on the RTTOV fast radiative transfer model (currently at version 12)","volume":"11","author":"Saunders","year":"2018","journal-title":"Geosci. Model. Dev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1002\/qj.3803","article-title":"The ERA5 global reanalysis, Q.J.R","volume":"146","author":"Hersbach","year":"2020","journal-title":"Meteorol. Soc."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"111196","DOI":"10.1016\/j.rse.2019.05.015","article-title":"The ECOSTRESS Spectral library version 1.0","volume":"1230","author":"Meerdink","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2668","DOI":"10.3390\/rs70302668","article-title":"A Multi-Temporal and Multi-Spectral Method to Estimate Aerosol Optical Thickness over Land, for the Atmospheric Correction of FormoSat-2, LandSat, VEN\u03bcS and Sentinel-2 Images","volume":"7","author":"Hagolle","year":"2015","journal-title":"Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/S0034-4257(02)00089-5","article-title":"Atmospheric correction of MODIS data in the visible to middle infrared: First results","volume":"83","author":"Vermote","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Lagouarde, J.P., Bhattacharya, B.K., Cr\u00e9bassol, P., Gamet, P., Babu, S.S., Boulet, G., Briottet, X., Buddhiraju, K.M., Cherchali, S., and Dadou, I. (2018, January 22\u201327). The Indian-French Trishna Mission: Earth Observation in the Thermal Infrared with High Spatio-Temporal Resolution. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518720"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"9","DOI":"10.5194\/isprs-annals-V-1-2021-9-2021","article-title":"Sentinel2 surface reflectance products generated by CNES and DLR: Methods, Validation and Applications","volume":"51","author":"Hagolle","year":"2021","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Colin, J., Hagolle, O., Landier, L., Coustance, S., Kettig, P., Marcq, S., Meygret, A., Ossman, J., and Vermote, E. (2023). Assessment of the performance of the atmospheric correction algorithm MAJA for Sentinel-2 surface reflectance estimates.","DOI":"10.3390\/rs15102665"},{"key":"ref_25","unstructured":"Charvet, D., Gnata, X., Toulemont, A., Rizzolo, S., Cl\u00e9net, A., Litouban, C., Gossant, A., Chassat, F., Buffet, L., and Salcedo, C. (2022, January 3\u20137). TRISHNA TIR instrument development and performance status. Proceedings of the International Conference on Space Optics\u2014ICSO, Nice, France."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3211","DOI":"10.1080\/01431169508954625","article-title":"Simulating the relationship between thermal emissivity and the normalized difference vegetation index","volume":"16","author":"Olioso","year":"1995","journal-title":"Int. J. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Olioso, A., Jacob, F., and Weiss, M. (2018, January 22\u201327). First evaluation of land surface emissivity spectra simulated with the sail-thermique model. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8519436"},{"key":"ref_28","unstructured":"Neyret, A. (2021). Evaluation de diff\u00e9rentes approaches visant \u00e0 estimer l\u2019\u00e9missivit\u00e9 de surface \u00e0 partir d\u2019informations du domaine visible, internal internship report. ISAE-CESBIO, unpublished."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Michel, A., Roupioz, L., Granero-Belinchon, C., and Briottet, X. (2019, January 22\u201324). Land Surface Temperature Retrieval over Urban areas from simulated TRISHNA data. Proceedings of the 2019 Joint Urban Remote Sensing Event (JURSE), Vannes, France.","DOI":"10.1109\/JURSE.2019.8808979"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"112518","DOI":"10.1016\/j.rse.2021.112518","article-title":"Geometry and adjacency effects in urban land surface temperature retrieval from high-spatial-resolution thermal infrared images","volume":"262","author":"Chen","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_31","first-page":"777","article-title":"TIGR-like atmospheric-profile databases for accurate radiative-flux computation, Q.J.R","volume":"126","author":"Chevallier","year":"2000","journal-title":"Meteorol. Soc."},{"key":"ref_32","unstructured":"Barsi, J.A., Barker, J.L., and Schott, J.R. (2003, January 21\u201325). An atmospheric correction parameter calculator for a single thermal band earth-sensing instrument. Proceedings of the IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), Toulouse, France."},{"key":"ref_33","unstructured":"Palluconi, F., Hoover, G., Alley, R., Jentoft-Nilsen, M., and Thompson, T. (2022, June 01). An Atmospheric Correction Method for ASTER Thermal Radiometry Over Land, Algorithm Theoretical Basis Document, Available online: https:\/\/lpdaac.usgs.gov\/documents\/1153\/AST_09T_User_Guide_V4.pdf."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3501","DOI":"10.1109\/TGRS.2017.2675623","article-title":"The Influence of Increasing Water Turbidity on Sea Surface Emissivity","volume":"55","author":"Wei","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1294","DOI":"10.1109\/TGRS.2019.2945701","article-title":"In-flight validation of the ECOSTRESS, Landsats 7 and 8 thermal infrared spectral channels using the Lake Tahoe CA\/NV and Salton Sea CA automated validation sites","volume":"58","author":"Hook","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2021.3079879","article-title":"Validation and Quality Assessment of the ECOSTRESS Level-2 Land Surface Temperature and Emissivity Product","volume":"60","author":"Hulley","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","unstructured":"Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Hor\u00e1nyi, A., Mu\u00f1oz Sabater, J., Nicolas, J., Peubey, C., Radu, R., and Rozum, I. (2022, June 01). ERA5 Hourly Data on Pressure Levels from 1959 to Present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS). Available online: https:\/\/cds.climate.copernicus.eu\/cdsapp#!\/dataset\/10.24381\/cds.bd0915c6?tab=overview."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1603","DOI":"10.1080\/01431160802541523","article-title":"A simple equation for determining sea surface emissivity in the 3\u201315 \u03bcm region","volume":"30","author":"Caselles","year":"2009","journal-title":"Int. J. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/2\/517\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:06:41Z","timestamp":1760119601000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/2\/517"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,15]]},"references-count":38,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["rs15020517"],"URL":"https:\/\/doi.org\/10.3390\/rs15020517","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,1,15]]}}}