{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:45:07Z","timestamp":1760237107106,"version":"build-2065373602"},"reference-count":30,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T00:00:00Z","timestamp":1583452800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100007049","name":"Korea Institute of Ocean Science and Technology","doi-asserted-by":"publisher","award":["20150356"],"award-info":[{"award-number":["20150356"]}],"id":[{"id":"10.13039\/501100007049","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper presents a single-channel atmospheric correction method for remotely sensed infrared (wavelength of 3\u201315 \u03bcm) images with various observation angles. The method is based on basic radiative transfer equations with a simple absorption-focused regression model to calculate the optical thickness of each atmospheric layer. By employing a simple regression model and re-organization of atmospheric profiles by considering viewing geometry, the proposed method conducts atmospheric correction at every pixel of a numerical weather prediction model in a single step calculation. The Visible Infrared Imaging Radiometer Suite (VIIRS) imaging channel (375 m) I4 (3.55~3.93 \u03bcm) and I5 (10.50~12.40 \u03bcm) bands were used as mid-wavelength and thermal infrared images to demonstrate the effectiveness of the proposed single-channel atmospheric correction method. The estimated sea surface temperatures (SSTs) obtained by the proposed method with high resolution numerical weather prediction models were compared with sea-truth temperature data from ocean buoys, multichannel-based SST products from VIIRS\/MODIS, and results from MODerate resolution atmospheric TRANsmission 5 (MODTRAN 5), for validation. High resolution (1.5 km and 12 km) numerical weather prediction (NWP) models distributed by the Korea Meteorological Administration (KMA) were employed as input atmospheric data. Nighttime SST estimations with the I4 band showed a root mean squared error (RMSE) of 0.95 \u00b0C, similar to that of the VIIRS product (RMSE: 0.92 \u00b0C) and lower than that of the MODIS product (RMSE: 1.74 \u00b0C), while estimations with the I5 band showed an RMSE of 1.81 \u00b0C. RMSEs from MODTRAN simulations were similar (within 0.2 \u00b0C) to those of the proposed method (I4: 0.81 \u00b0C, I5: 1.67 \u00b0C). These results demonstrated the competitive performance of a regression-based method using high-resolution numerical weather prediction (NWP) models for atmospheric correction of single-channel infrared imaging sensors.<\/jats:p>","DOI":"10.3390\/rs12050853","type":"journal-article","created":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T09:26:41Z","timestamp":1583486801000},"page":"853","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An Atmospheric Correction Using High Resolution Numerical Weather Prediction Models for Satellite-Borne Single-Channel Mid-Wavelength and Thermal Infrared Imaging Sensors"],"prefix":"10.3390","volume":"12","author":[{"given":"Hongtak","family":"Lee","sequence":"first","affiliation":[{"name":"Satellite Application Division, Satellite Operation and Application Center, Korea Aerospace Research Institute, Daejeon 34133, Korea"},{"name":"Department of Earth System Science, Yonsei University, Seoul 03722, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9255-9407","authenticated-orcid":false,"given":"Joong-Sun","family":"Won","sequence":"additional","affiliation":[{"name":"Department of Earth System Science, Yonsei University, Seoul 03722, Korea"}]},{"given":"Wook","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Earth System Science, Yonsei University, Seoul 03722, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,6]]},"reference":[{"key":"ref_1","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_2","first-page":"4688","article-title":"A generalized single-channel method for retrieving land surface temperature from remote sensing data","volume":"108","author":"Sobrino","year":"2003","journal-title":"J. Geophys. Res.: Atmos."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1016\/j.rse.2004.02.018","article-title":"Deriving land surface temperature from Landsat 5 and 7 during SMEX02\/SMACEX","volume":"92","author":"Li","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1109\/TGRS.2008.2007125","article-title":"Revision of the single-channel algorithm for land surface temperature retrieval from Landsat thermal-infrared data","volume":"47","author":"Sobrino","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Tang, H., and Li, Z.L. (2013). Quantitative Remote Sensing in Thermal Infrared: Theory and Applications, Springer Science & Business Media.","DOI":"10.1007\/978-3-642-42027-6"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/0273-1177(94)90193-7","article-title":"A split window algorithm for estimating land surface temperature from satellites","volume":"14","author":"Ulivieri","year":"1994","journal-title":"Adv. Space Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"9829","DOI":"10.3390\/rs6109829","article-title":"Land surface temperature retrieval from Landsat 8 TIRS\u2014Comparison between radiative transfer equation-based method, split window algorithm and single channel method","volume":"6","author":"Yu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"111216","DOI":"10.1016\/j.rse.2019.111216","article-title":"A new thermal infrared channel configuration for accurate land surface temperature retrieval from satellite data","volume":"231","author":"Zheng","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zhang, S., Duan, S.B., Li, Z.L., Huang, C., Wu, H., Han, X.J., and Gao, M. (2019). Improvement of Split-Window Algorithm for Land Surface Temperature Retrieval from Sentinel-3A SLSTR Data Over Barren Surfaces Using ASTER GED Product. Remote Sens., 11.","DOI":"10.3390\/rs11243025"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"141","DOI":"10.5589\/m02-087","article-title":"Landsat TM and ETM+ thermal band calibration","volume":"29","author":"Barsi","year":"2003","journal-title":"Can. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1029\/2018JD029330","article-title":"A practical single-channel algorithm for land surface temperature retrieval: Application to Landsat series data","volume":"124","author":"Wang","year":"2019","journal-title":"J. Geophys. Res.: Atmos."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1109\/LGRS.2009.2029534","article-title":"A single-channel algorithm for land-surface temperature retrieval from ASTER data","volume":"7","author":"Sobrino","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Crist\u00f3bal, J., Jim\u00e9nez-Mu\u00f1oz, J.C., Prakash, A., Mattar, C., Skokovi\u0107, D., and Sobrino, J.A. (2018). An Improved Single-Channel Method to Retrieve Land Surface Temperature from the Landsat-8 Thermal Band. Remote Sens., 10.","DOI":"10.3390\/rs10030431"},{"key":"ref_14","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, Toulouse, France. IEEE Cat. No. 03CH37477."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"5183","DOI":"10.1007\/s12665-014-3388-1","article-title":"Estimation of land surface temperature from atmospherically corrected LANDSAT TM image using 6S and NCEP global reanalysis product","volume":"72","author":"Srivastava","year":"2014","journal-title":"Environ. Earth Sci."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Tardy, B., Rivalland, V., Huc, M., Hagolle, O., Marcq, S., and Boulet, G. (2016). A software tool for atmospheric correction and surface temperature estimation of Landsat infrared thermal data. Remote Sens., 8.","DOI":"10.3390\/rs8090696"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1109\/TGRS.2016.2611566","article-title":"A physics-based algorithm for the simultaneous retrieval of land surface temperature and emissivity from VIIRS thermal infrared data","volume":"55","author":"Islam","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1002\/2013JD020418","article-title":"Suomi NPP VIIRS sensor data record verification, validation, and long-term performance monitoring","volume":"118","author":"Cao","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_19","unstructured":"Korea Meteorological Administration (KMA) (2013). Application Manual of Numerical Forecast Data, Korea Meteorological Administration (KMA)."},{"key":"ref_20","unstructured":"Liou, K.N. (2002). An Introduction to Atmospheric Radiation, Elsevier. [2nd ed.]."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"630","DOI":"10.1175\/1520-0469(1980)037<0630:TSATRT>2.0.CO;2","article-title":"Two-stream approximations to radiative transfer in planetary atmospheres: A unified description of existing methods and a new improvement","volume":"37","author":"Meador","year":"1980","journal-title":"J. Atmos. Sci."},{"key":"ref_22","unstructured":"Lee, K.M. (2000). Atmospheric Radiation, Sigma Press. [1st ed.]."},{"key":"ref_23","first-page":"348","article-title":"Understanding radiative transfer in the midwave infrared: A precursor to full-spectrum atmospheric compensation. In Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X","volume":"5425","author":"Griffin","year":"2004","journal-title":"Int. Soc. Opt. Photonics"},{"key":"ref_24","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_25","unstructured":"Carmichael, R. (2003). Geopotential and Geometric Altitude, Public Domain of Aeronautical Software (PDA)."},{"key":"ref_26","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 \u00b5 m region","volume":"30","author":"Caselles","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1016\/j.rse.2008.11.007","article-title":"The ASTER Spectral Library Version 2.0","volume":"113","author":"Baldridge","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_28","unstructured":"Korea Meteorological Administration (KMA) (2015). Explanation Document of Meteorological Data; Marine Weather Buoys, Wave Height Buoys, Marine Light Beacons, Korea Meteorological Administration (KMA)."},{"key":"ref_29","unstructured":"NOAA Office of Satellite and Product Operations (OSPO) (2015). GHRSST GDS2 Level 2P Global Skin Sea Surface Temperature from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite created by the NOAA Advanced Clear-Sky Processor for Ocean (ACSPO), PO.DAAC. Ver. 2.4."},{"key":"ref_30","unstructured":"JPL\/OBPG\/RSMAS (2016). GHRSST Level 2P Global Skin Sea Surface Temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Aqua satellite, PO.DAAC. Ver. 2014.0."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/5\/853\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:04:50Z","timestamp":1760173490000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/5\/853"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,6]]},"references-count":30,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2020,3]]}},"alternative-id":["rs12050853"],"URL":"https:\/\/doi.org\/10.3390\/rs12050853","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2020,3,6]]}}}