{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T02:23:51Z","timestamp":1769912631810,"version":"3.49.0"},"reference-count":67,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2015,11,5]],"date-time":"2015-11-05T00:00:00Z","timestamp":1446681600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41001205, 41325004, and 41471308"],"award-info":[{"award-number":["41001205, 41325004, and 41471308"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China\u2019s 863 program","award":["2013AA12A302"],"award-info":[{"award-number":["2013AA12A302"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Determining the dominant optically active substances in water bodies via classification can improve the accuracy of bio-optical and water quality parameters estimated by remote sensing. This study provides four robust centroid sets from in situ remote sensing reflectance (Rrs (\u03bb)) data presenting typical optical types obtained by plugging different similarity measures into fuzzy c-means (FCM) clustering. Four typical types of waters were studied: (1) highly mixed eutrophic waters, with the proportion of absorption of colored dissolved organic matter (CDOM), phytoplankton, and non-living particulate matter at approximately 20%, 20%, and 60% respectively; (2) CDOM-dominated relatively clear waters, with approximately 45% by proportion of CDOM absorption;  (3) nonliving solids-dominated waters, with approximately 88% by proportion of absorption of nonliving particulate matter; and (4) cyanobacteria-composed scum. We also simulated spectra from seven ocean color satellite sensors to assess their classification ability. POLarization and Directionality of the Earth's Reflectances (POLDER), Sentinel-2A, and MEdium Resolution Imaging Spectrometer (MERIS) were found to perform better than the rest. Further, a classification tree for MERIS, in which the characteristics of Rrs (709)\/Rrs (681), Rrs (560)\/Rrs (709), Rrs (560)\/Rrs (620), and Rrs (709)\/Rrs (761) are integrated, is also proposed in this paper. The overall accuracy and Kappa coefficient of the proposed classification tree are 76.2% and 0.632, respectively.<\/jats:p>","DOI":"10.3390\/rs71114731","type":"journal-article","created":{"date-parts":[[2015,11,5]],"date-time":"2015-11-05T10:56:04Z","timestamp":1446720964000},"page":"14731-14756","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance"],"prefix":"10.3390","volume":"7","author":[{"given":"Qian","family":"Shen","sequence":"first","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences,  No. 9 Dengzhuang South Road, Haidian District, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8590-9736","authenticated-orcid":false,"given":"Junsheng","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences,  No. 9 Dengzhuang South Road, Haidian District, Beijing 100094, China"}]},{"given":"Fangfang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences,  No. 9 Dengzhuang South Road, Haidian District, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5389-7251","authenticated-orcid":false,"given":"Xu","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences,  No. 9 Dengzhuang South Road, Haidian District, Beijing 100094, China"}]},{"given":"Jun","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geography, Planning of Sun Yat-Sen University, No. 135 Xingang Xi Road,  Guangzhou 510275, China"}]},{"given":"Wei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Beijing University of Chemical Technology,  No. 15 North Third Ring Road, Chaoyang District, Beijing 100029, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0319-7753","authenticated-orcid":false,"given":"Bing","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences,  No. 9 Dengzhuang South Road, Haidian District, Beijing 100094, China"}]}],"member":"1968","published-online":{"date-parts":[[2015,11,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.rse.2013.11.021","article-title":"An optical water type framework for selecting and blending retrievals from bio-optical algorithms in lakes and coastal waters","volume":"143","author":"Moore","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/j.rse.2012.03.004","article-title":"Optical classification of contrasted coastal waters","volume":"123","author":"Vantrepotte","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.rse.2015.01.023","article-title":"How optically diverse is the coastal ocean?","volume":"160","author":"Vantrepotte","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1093\/plankt\/fbq039","article-title":"Seasonal\u2013spatial variation and remote sensing of phytoplankton absorption in Lake Taihu, a large eutrophic and shallow lake in China","volume":"32","author":"Zhang","year":"2010","journal-title":"J. Plankton. Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4635","DOI":"10.1080\/01431161.2010.485216","article-title":"Medium resolution imaging spectrometer (MERIS) estimation of chlorophyll-a concentration in the turbid sediment-laden waters of the Changjiang (Yangtze) Estuary","volume":"31","author":"Shen","year":"2010","journal-title":"Int. J. Remote. Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"4277","DOI":"10.1080\/01431160600851835","article-title":"Absorption and scattering properties of water body in Taihu Lake, China: Absorption","volume":"27","author":"Ma","year":"2006","journal-title":"Int. J. Remote. Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2014.02.011","article-title":"A three-band semi-analytical model for deriving total suspended sediment concentration from HJ-1A\/CCD data in turbid coastal waters","volume":"93","author":"Chen","year":"2014","journal-title":"ISPRS J. Photogramm."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1175","DOI":"10.1016\/j.rse.2009.02.005","article-title":"A four-band semi-analytical model for estimating chlorophyll a in highly turbid lakes: The case of Taihu Lake, China","volume":"113","author":"Le","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.rse.2012.08.011","article-title":"Evaluation of remote sensing algorithms for cyanobacterial pigment retrievals during spring bloom formation in several lakes of East China","volume":"126","author":"Duan","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.isprsjprs.2013.08.009","article-title":"An approach for developing Landsat-5 TM-based retrieval models of suspended particulate matter concentration with the assistance of MODIS","volume":"85","author":"Wu","year":"2013","journal-title":"ISPRS J. Photogramm."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.scitotenv.2012.11.058","article-title":"Remote chlorophyll-a estimates for inland waters based on a cluster-based classification","volume":"444","author":"Shi","year":"2013","journal-title":"Sci. Total. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"709","DOI":"10.4319\/lo.1977.22.4.0709","article-title":"Analysis of variations in ocean color","volume":"22","author":"Morel","year":"1977","journal-title":"Limnol. Oceanogr."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"847","DOI":"10.4319\/lo.1998.43.5.0847","article-title":"Light scattering and chlorophyll concentration in case 1 waters: A reexamination","volume":"43","author":"Loisel","year":"1998","journal-title":"Limnol. Oceanogr."},{"key":"ref_14","unstructured":"Jerlov, N.G. (1976). Marine optics, Elsevier Science Publishing Company. [2nd ed.]."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.rse.2005.12.002","article-title":"Estimating chlorophyll a concentrations from remote-sensing reflectance in optically shallow waters","volume":"101","author":"Cannizzaro","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6329","DOI":"10.1364\/AO.37.006329","article-title":"Hyperspectral remote sensing for shallow waters. I. A semianalytical model","volume":"37","author":"Lee","year":"1998","journal-title":"Appl. Optics."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1007\/BF03025905","article-title":"Optical classification of waters in the eastern Arabian Sea","volume":"25","author":"Sasmal","year":"1997","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"91","DOI":"10.4319\/lo.1991.36.1.0091","article-title":"Secchi disk and photometer estimates of light regimes in Alaskan lakes: Effects of yellow color and turbidity","volume":"36","author":"Koenings","year":"1991","journal-title":"Limnol. Oceanogr."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/S0034-4257(01)00238-3","article-title":"Lake water quality classification with airborne hyperspectral spectrometer and simulated MERIS data","volume":"79","author":"Koponen","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"671","DOI":"10.4319\/lo.1981.26.4.0671","article-title":"An optical classification of coastal and oceanic waters based on the specific spectral absorption curves of phytoplankton pigments, dissolved organic matter, and other particulate materials","volume":"26","author":"Prieur","year":"1981","journal-title":"Limnol. Oceanogr."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"500","DOI":"10.4319\/lo.1982.27.3.0500","article-title":"Bio-optical classification and model of natural waters. 2","volume":"27","author":"Baker","year":"1982","journal-title":"Limnol. Oceanogr."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1039\/c2pp25061f","article-title":"Specific inherent optical quantities of complex turbid inland waters, from the perspective of water classification","volume":"11","author":"Sun","year":"2012","journal-title":"Photochem. Photobiol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/S1385-1101(03)00019-4","article-title":"Preliminary optical classification of lakes and coastal waters in Estonia and south Finland","volume":"49","author":"Reinart","year":"2003","journal-title":"J. Sea. Res."},{"key":"ref_24","first-page":"3422","article-title":"Reference spectra to classify Amazon water types","volume":"33","author":"Novo","year":"2011","journal-title":"Int. J. Remote. Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.rse.2007.02.012","article-title":"Variability and classification of remote sensing reflectance spectra in the eastern English Channel and southern North Sea","volume":"110","author":"Lubac","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1016\/j.rse.2010.10.014","article-title":"Remote estimation of chlorophyll a in optically complex waters based on optical classification","volume":"115","author":"Le","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2424","DOI":"10.1016\/j.rse.2009.07.016","article-title":"A class-based approach to characterizing and mapping the uncertainty of the MODIS ocean chlorophyll product","volume":"113","author":"Moore","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"988","DOI":"10.1109\/TGRS.2011.2163199","article-title":"Estimation of chlorophyll a concentration using NIR\/RED bands of MERIS and classification procedure in inland turbid water","volume":"50","author":"Li","year":"2012","journal-title":"IEEE. Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1007\/s10750-013-1462-4","article-title":"Pre-classification improves relationships between water clarity, light attenuation, and suspended particulates in turbid inland waters","volume":"711","author":"Liu","year":"2013","journal-title":"Hydrobiologia"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1827","DOI":"10.1016\/j.csr.2004.06.010","article-title":"Integration of multi-source data for water quality classification in the Pearl River estuary and its adjacent coastal waters of Hong Kong","volume":"24","author":"Chen","year":"2004","journal-title":"Cont. Shelf. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.rse.2006.02.013","article-title":"Comparison of different satellite sensors in detecting cyanobacterial bloom events in the Baltic Sea","volume":"102","author":"Reinart","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_32","first-page":"232","article-title":"Modeling spectral reflectance of optically complex waters using bio-optical measurements from Tokyo Bay","volume":"99","author":"Feng","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1764","DOI":"10.1109\/36.942555","article-title":"A fuzzy logic classification scheme for selecting and blending satellite ocean color algorithms","volume":"39","author":"Moore","year":"2001","journal-title":"IEEE. Trans. Geosci. Remote Sens."},{"key":"ref_34","unstructured":"MacQueen, J. Some methods for classification and analysis of multivariate observations. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, CA, USA."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1645","DOI":"10.1109\/36.763281","article-title":"Radiance spectra classification from the ocean color and temperature scanner on ADEOS","volume":"37","author":"Ainsworth","year":"1999","journal-title":"IEEE. Trans. Geosci. Remote Sens."},{"key":"ref_36","first-page":"C5","article-title":"Feature-based classification of optical water types in the northwest Atlantic based on satellite ocean color data","volume":"108","author":"Sosik","year":"2003","journal-title":"J. Geophys. Res."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3871","DOI":"10.1109\/TGRS.2012.2227976","article-title":"Hyperspectral remote sensing of the pigment c-phycocyanin in turbid inland waters, based on optical classification","volume":"51","author":"Sun","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1080\/01621459.1963.10500845","article-title":"Hierarchical grouping to optimize an objective function","volume":"58","author":"Ward","year":"1963","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1007\/s10750-007-0724-4","article-title":"A study of absorption characteristics of chromophoric dissolved organic matter and particles in Lake Taihu, China","volume":"592","author":"Zhang","year":"2007","journal-title":"Hydrobiologia"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1007\/s10661-007-0043-2","article-title":"A bio-optical model based method of estimating total suspended matter of Lake Taihu from near-infrared remote sensing reflectance","volume":"145","author":"Zhang","year":"2008","journal-title":"Environ. Monit. Assess."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1007\/s10750-011-0652-1","article-title":"Development of optical criteria to discriminate various types of highly turbid lake waters","volume":"669","author":"Sun","year":"2011","journal-title":"Hydrobiologia"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.rse.2013.09.033","article-title":"Suspended sediment monitoring and assessment for Yellow River estuary from Landsat TM and ETM+ imagery","volume":"146","author":"Zhang","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_43","unstructured":"Mueller, J.L., Fargion, G.S., McClain, C.R., Mueller, J., Brown, S., Clark, D., Johnson, B., Yoon, H., Lykke, K., and Flora, S. (2003). Special topics in ocean optics protocols, Ocean Optics Protocols for Satellite Ocean Color Sensor Validation."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"343","DOI":"10.4319\/lo.1967.12.2.0343","article-title":"Determination of chlorophyll and pheo-pigments: Spectrophotometric equations","volume":"12","author":"Lorenzen","year":"1967","journal-title":"Limnol. Oceanogr."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"237","DOI":"10.4319\/lo.2005.50.1.0237","article-title":"Remote sensing of the cyanobacterial pigment phycocyanin in turbid inland water","volume":"50","author":"Simis","year":"2005","journal-title":"Limnol. Oceanogr."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1117\/12.21440","article-title":"Algorithms for determining the absorption coefficient for aquatic particulates using the quantitative filter technique","volume":"1302","author":"Mitchell","year":"1990","journal-title":"Proc. SPIE"},{"key":"ref_47","unstructured":"Matlab Fuzzy Logic Toolbox. Available online: http:\/\/www.mathworks.cn\/cn\/help\/fuzzy\/data-clustering.html."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1007\/978-3-540-88458-3_60","article-title":"Knee point detection in BIC for detecting the number of clusters","volume":"Volume 5259","author":"BlancTalon","year":"2008","journal-title":"Proceedings of Advanced Concepts for Intelligent Vision Systems"},{"key":"ref_49","first-page":"32","article-title":"A fuzzy relative of the ISO data process and its use in detecting compact well-separated clusters","volume":"3","author":"Dunn","year":"1973","journal-title":"Cybernet. Syst."},{"key":"ref_50","first-page":"387","article-title":"A physical interpretation of fuzzy ISODATA","volume":"6","author":"Bezdek","year":"1976","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"111715-1","DOI":"10.1117\/1.OE.51.11.111715","article-title":"Semi-supervised dimensionality reduction using orthogonal projection divergence-based clustering for hyperspectral imagery","volume":"51","author":"Su","year":"2012","journal-title":"Opt. Eng."},{"key":"ref_52","unstructured":"Swain, P.H., and Davis, S.M. (1978). Remote Sensing: The Quantitative Approach, McGraw-Hill International Book Co."},{"key":"ref_53","unstructured":"Cureton, E.E., and D\u2019Agostino, R.B. (1983). Factor Analysis: An Applied Approach, Lawrence Erlbaum Associates Inc."},{"key":"ref_54","unstructured":"NIST\/SEMATECH e-Handbook of Statistical Methods, Available online: http:\/\/www.itl.nist.gov\/div898\/handbook\/eda\/section3\/eda357.htm."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/BF02289233","article-title":"The varimax criterion for analytic rotation in factor analysis","volume":"23","author":"Kaiser","year":"1958","journal-title":"Psychometrika"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"3428","DOI":"10.3390\/s7123428","article-title":"Determination of primary spectral bands for remote sensing of aquatic environments","volume":"7","author":"Lee","year":"2007","journal-title":"Sensors"},{"key":"ref_57","first-page":"1892","article-title":"Characteristic wavelengths analysis for remote sensing reflectance on water surface in Taihu Lake","volume":"31","author":"Shen","year":"2011","journal-title":"Spectrosc. Spect. Anal."},{"key":"ref_58","unstructured":"Ruffin, C., and King, R. (July, January 28). The analysis of hyperspectral data using Savitzky-Golay filtering-theoretical basis. Proceedings of Geoscience and Remote Sensing Symposium, Hamburg, Germany."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/S0034-4257(98)00032-7","article-title":"Derivative analysis of hyperspectral data","volume":"66","author":"Tsai","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/S0034-4257(97)00083-7","article-title":"Selecting and interpreting measures of thematic classification accuracy","volume":"62","author":"Stehman","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_61","unstructured":"Congalton, R. (1981). The Use of Discrete Multivariate Analysis for the Assessment of Landsat Classification Accuracy. [Master\u2019s Thesis, Virginia Polytechnic Institute and State University]."},{"key":"ref_62","unstructured":"(2000). IOCCG Report No. 3: Remote Sensing of Ocean Colour in Coastal, and other Optically-Complex, Waters, IOCCG Project Office."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/S0048-9697(00)00687-2","article-title":"A semi-operative approach to lake water quality retrieval from remote sensing data","volume":"268","author":"Pulliainen","year":"2001","journal-title":"Sci. Total. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1127","DOI":"10.1021\/es9809657","article-title":"Optical teledetection of chlorophyll a in turbid inland waters","volume":"33","author":"Gons","year":"1999","journal-title":"Environ. Sci. Technol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/S0034-4257(00)00097-3","article-title":"Determination of chlorophyll content and trophic state of lakes using field spectrometer and IRS-1C satellite data in the Mecklenburg Lake District, Germany","volume":"73","author":"Thiemann","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"3479","DOI":"10.1016\/j.rse.2011.08.011","article-title":"Remote estimation of chl-a concentration in turbid productive waters\u2014Return to a simple two-band NIR-red model?","volume":"115","author":"Gurlin","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"3996","DOI":"10.1016\/j.rse.2007.11.019","article-title":"An evaluation of algorithms for the remote sensing of cyanobacterial biomass","volume":"112","author":"Simis","year":"2008","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/11\/14731\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:51:32Z","timestamp":1760215892000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/11\/14731"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,11,5]]},"references-count":67,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2015,11]]}},"alternative-id":["rs71114731"],"URL":"https:\/\/doi.org\/10.3390\/rs71114731","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,11,5]]}}}