{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T10:47:26Z","timestamp":1764240446116,"version":"build-2065373602"},"reference-count":20,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T00:00:00Z","timestamp":1620345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In this work, we propose simple and robust technique for the retrieval of underlying surface spectral reflectance using spaceborne observations. It can be used to process both multispectral moderate resolution satellite data and also multi-zone high spatial resolution data. The technique can work automatically for different types of land surfaces without using huge databases accumulated in advance. The new cloud discrimination and retrieval of the water vapor content in atmosphere procedures are presented. The key point of the proposed atmospheric correction technique is the suggested single-wavelength method for determining the atmospheric aerosol optical thickness without reference to a specific type of underlying surface spectrum. The retrievals of spectral reflectance for various land surfaces with developed technique, performed using computer simulation and experimental data, have demonstrated a high retrieval accuracy.<\/jats:p>","DOI":"10.3390\/rs13091831","type":"journal-article","created":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T22:36:24Z","timestamp":1620426984000},"page":"1831","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Robust Atmospheric Correction Procedure for Determination of Spectral Reflectance of Terrestrial Surfaces from Satellite Spectral Measurements"],"prefix":"10.3390","volume":"13","author":[{"given":"Iosif L.","family":"Katsev","sequence":"first","affiliation":[{"name":"B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Pr. Nezavisimosti 68, 220072 Minsk, Belarus"}]},{"given":"Alexander S.","family":"Prikhach","sequence":"additional","affiliation":[{"name":"B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Pr. Nezavisimosti 68, 220072 Minsk, Belarus"}]},{"given":"Eleonora P.","family":"Zege","sequence":"additional","affiliation":[{"name":"B.I. Stepanov Institute of Physics, National Academy of Sciences of Belarus, Pr. Nezavisimosti 68, 220072 Minsk, Belarus"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7110-223X","authenticated-orcid":false,"given":"Alexander A.","family":"Kokhanovsky","sequence":"additional","affiliation":[{"name":"VITROCISET Belgium, A Leonardo Company, Bratustrasse 7, D-64293 Darmstadt, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1529","DOI":"10.5194\/amt-11-1529-2018","article-title":"Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land","volume":"11","author":"Lipponen","year":"2018","journal-title":"Atmos. Meas. Tech."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1109\/TGRS.2004.824067","article-title":"Aerosol Properties Over Bright-Reflecting Source Regions","volume":"42","author":"Hsu","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"9296","DOI":"10.1002\/jgrd.50712","article-title":"Enhanced Deep Blue aerosol retrieval algorithm: The second generation","volume":"118","author":"Hsu","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"unstructured":"(2016). Atmospherc Compensation in Satellite Imagery. (9,396,528 B2), U.S. Patent.","key":"ref_4"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"704","DOI":"10.1002\/jame.20035","article-title":"MAC-v1: A new global aerosol climatology for climate studies","volume":"5","author":"Kinne","year":"2013","journal-title":"J. Adv. Model. Earth Syst."},{"doi-asserted-by":"crossref","unstructured":"Kokhanovsky, A.A., and de Leeuw, G. (2009). Iterative procedure for retrieval of spectral aerosol optical thickness and surface reflectance from satellite data using fast radiative transfer code and its application to MERIS onboard ENVISAT measurements. Satellite Aerosol Remote Sensing over Land, Springer.","key":"ref_6","DOI":"10.1007\/978-3-540-69397-0"},{"key":"ref_7","first-page":"4260","article-title":"Retrieval of aerosol optical thickness over land surfaces from top-of-atmosphere radiance","volume":"108","author":"Freitag","year":"2003","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1403","DOI":"10.5194\/amt-3-1403-2010","article-title":"Speeding up the aerosol optical thickness retrieval using analytical solutions of radiative transfer theory","volume":"3","author":"Katsev","year":"2010","journal-title":"Atmos. Meas. Tech."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1364\/AO.40.000400","article-title":"Monte Carlo and multicomponent ap-proximation methods for vector radiative transfer by use of effective Mueller matrix calculations","volume":"40","author":"Tynes","year":"2001","journal-title":"Appl. Opt."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/S0022-4073(03)00192-4","article-title":"Reflection of light from nonabsorbing semi-infinite cloudy media. A simple approximation","volume":"85","author":"Kokhanovsky","year":"2004","journal-title":"J. Quant. Spectrosc. Radiat. Transf."},{"unstructured":"LANDSAT 8 (L8) (2016). Data Users Handbook, EROS. Version 2.0.","key":"ref_11"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"15231","DOI":"10.1029\/2000JD900191","article-title":"A near-infrared optimized DOAS method for the fast global retrieval of atmospheric CH4, CO, CO2, H2O, and N2O total column amounts from SCIAMACHY Envisat-1 nadir radiances","volume":"105","author":"Buchwitz","year":"2000","journal-title":"J. Geophys. Res. Space Phys."},{"doi-asserted-by":"crossref","unstructured":"Buchwitz, M., and Burrows, J.P. (2003, January 9\u201312). Retrieval of CH 4, CO, and CO 2 total column amounts from SCIAMACHY near-infrared nadir spectra: Retrieval algorithm and first results. Proceedings of the Remote Sensing of Clouds and the Atmosphere VIII, Barcelona, Spain.","key":"ref_13","DOI":"10.1117\/12.514219"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"111","DOI":"10.5194\/acp-4-111-2004","article-title":"First retrieval of global water vapour column amounts from SCIAMACHY meas-urements","volume":"4","author":"Noel","year":"2004","journal-title":"Atmos. Chem. Phys."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3145","DOI":"10.5194\/amt-11-3145-2018","article-title":"Validation of MODIS 3 km land aerosol optical depth from NASA\u2019s EOS Terra and Aqua missions","volume":"11","author":"Gupta","year":"2018","journal-title":"Atmos. Meas. Tech."},{"unstructured":"AFGL-TR-86-0110 (1986). Atmospheric Constituent Profiles (0\u2013120 km).","key":"ref_16"},{"unstructured":"Lenoble, J. (1986). A Preliminary Cloudless Standard Atmosphere for Radiation Computation, World Climate Programme, World Meteorological Organization.","key":"ref_17"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"111707","DOI":"10.1117\/1.OE.51.11.111707","article-title":"Speed and accuracy improvements in FLAASH atmospheric correction of hyperspectral imagery","volume":"51","author":"Perkins","year":"2012","journal-title":"Opt. Eng."},{"unstructured":"Smith, M.J. (2016, June 24). A Comparison of DG AComp, FLAASH and QUAC Atmospheric Compensation Algorithms Using WorldView-2 Imagery\/University of Colorado. Available online: https:\/\/digitalglobe-marketing.s3.amazonaws.com\/files\/blog\/.","key":"ref_19"},{"doi-asserted-by":"crossref","unstructured":"Bouvet, M., Thome, K., Berthelot, B., Bialek, A., Czapla-Myers, J., Fox, N.P., Goryl, P., Henry, P., Ma, L., and Marcq, S. (2019). RadCalNet: A Radiometric Calibration Network for Earth Observing Imagers Operating in the Visible to Shortwave Infrared Spectral Range. 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