{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:58:35Z","timestamp":1760234315482,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,29]],"date-time":"2021-04-29T00:00:00Z","timestamp":1619654400000},"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>Semi-analytical algorithms (SAAs) invert spectral remote sensing reflectance (Rrs(\u03bb),\u00a0sr\u22121) to Inherent Optical Properties (IOPs) of an aquatic medium (\u03bb is the wavelength). Existing SAAs implement different methodologies with a range of spectral IOP models and inversion methods producing concentrations of non-water constituents. Absorption spectrum decomposition algorithms (ADAs) are a set of algorithms developed to partition anw(\u03bb),\u00a0m\u22121 (i.e., the light absorption coefficient without pure water absorption), into absorption subcomponents of phytoplankton (aph(\u03bb),\u00a0m\u22121) and coloured detrital matter (adg(\u03bb),\u00a0m\u22121). Despite significant developments in ADAs, their applicability to remote sensing applications is rarely studied. The present study formulates hybrid inversion approaches that combine SAAs and ADAs to derive absorption subcomponents from Rrs(\u03bb) and explores potential alternatives to operational SAAs. Using Rrs(\u03bb) and concurrent absorption subcomponents from four datasets covering a wide range of optical properties, three operational SAAs, i.e., Garver\u2013Siegel\u2013Maritorena (GSM), Quasi-Analytical Algorithm (QAA), Generalized Inherent Optical Property (GIOP) model are evaluated in deriving anw(\u03bb) from Rrs(\u03bb). Among these three models, QAA and GIOP models derived anw(\u03bb) with lower errors. Among six distinctive ADAs tested in the study, the Generalized Stacked Constraints Model (GSCM) and Zhang\u2019s model-derived absorption subcomponents achieved lower average spectral mean absolute percentage errors (MAPE) in the range of 8\u201338%. Four hybrid models, GIOPGSCM, GIOPZhang, QAAGSCM and QAAZhang, formulated using the SAAs and ADAs, are compared for their absorption subcomponent retrieval performance from Rrs(\u03bb). GIOPGSCM and GIOPZhang models derived absorption subcomponents have lower errors than GIOP and QAA. Potential uncertainties associated with datasets and dependency of algorithm performance on datasets were discussed.<\/jats:p>","DOI":"10.3390\/rs13091726","type":"journal-article","created":{"date-parts":[[2021,4,29]],"date-time":"2021-04-29T10:30:41Z","timestamp":1619692241000},"page":"1726","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Hybrid Inversion Algorithms for Retrieval of Absorption Subcomponents from Ocean Colour Remote Sensing Reflectance"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1619-1353","authenticated-orcid":false,"given":"Srinivas","family":"Kolluru","sequence":"first","affiliation":[{"name":"Center of Studies in Resources Engineering, Indian Institute of Technology, Bombay 400076, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8833-132X","authenticated-orcid":false,"given":"Surya Prakash","family":"Tiwari","sequence":"additional","affiliation":[{"name":"Center for Environment &amp; Water, Research Institute, King Fahd University of Petroleum &amp; Minerals, Dhahran 31261, Saudi Arabia"}]},{"given":"Shirishkumar S.","family":"Gedam","sequence":"additional","affiliation":[{"name":"Center of Studies in Resources Engineering, Indian Institute of Technology, Bombay 400076, India"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2155","DOI":"10.1002\/jgrc.20115","article-title":"A model based on stacked-constraints approach for partitioning the light absorption coefficient of seawater into phytoplankton and non-phytoplankton components","volume":"118","author":"Zheng","year":"2013","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_2","unstructured":"Twardowski, M.S., Rottgers, R., and Stramski, D. (2018). The Absorption Coefficient, An Overview. Ocean Optics & Biogeochemistry Protocols for Satellite Ocean Colour Sensor Validation, Bedford Institute of Oceanography. Chapter 1."},{"key":"ref_3","unstructured":"WET Labs (2011). ac Meter Protocol Document, WET Labs, Inc."},{"key":"ref_4","unstructured":"Freeman, S. (2012). Calibration and Data Processing of ACS Device."},{"key":"ref_5","unstructured":"Dana, D.R., and Maffione, R.A. (2006, January 20\u201324). A New Hyperspectral Spherical-Cavity Absorption Meter. Proceedings of the AGU Ocean Sciences Meeting, Honolulu, HI, USA."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"R\u00f6ttgers, R., H\u00e4se, C., and Doerffer, R. (2007). Determination of the particulate absorption of microalgae using a point-source integrating-cavity absorption meter: Verification with a photometric technique, improvements for pigment bleaching, and correction for chlorophyll fluorescence. Limnol. Oceanogr. Methods, 5.","DOI":"10.4319\/lom.2007.5.1"},{"key":"ref_7","unstructured":"Mobley, C.D. (1994). Light and Water: Radiative Transfer in Natural Waters, Academic Press."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.pocean.2018.01.001","article-title":"An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing","volume":"160","author":"Werdell","year":"2018","journal-title":"Prog. Oceanogr."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2019","DOI":"10.1364\/AO.52.002019","article-title":"Generalized ocean color inversion model for retrieving marine inherent optical properties","volume":"52","author":"Werdell","year":"2013","journal-title":"Appl. Opt."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"18607","DOI":"10.1029\/96JC03243","article-title":"Inherent optical property inversion of ocean color spectra and its biogeochemcial interpretation 1. Time series from the Sargasso Sea","volume":"102","author":"Garver","year":"1997","journal-title":"J. Geophys. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2705","DOI":"10.1364\/AO.41.002705","article-title":"Optimization of a semianalytical ocean color model for global-scale application","volume":"41","author":"Maritorena","year":"2002","journal-title":"Appl. Opt."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"5755","DOI":"10.1364\/AO.41.005755","article-title":"Deriving inherent optical properties from water color: A multiband quasi-analytical algorithm for optically deep waters","volume":"41","author":"Lee","year":"2002","journal-title":"Appl. Opt."},{"key":"ref_13","unstructured":"Lee, Z., Lubac, B., Werdell, J., and Arnone, R. (2021, March 22). An Update of the Quasi-Analytical Algorithm (QAA-V5). Available online: https:\/\/www.researchgate.net\/publication\/228416418_An_update_of_the_quasi-analytical_algorithm_QAA_v5."},{"key":"ref_14","unstructured":"Lee, Z. (2021, March 22). Update of the Quasi-Analytical Algorithm (QAA_v6). Available online: http:\/\/www.ioccg.org\/groups\/Software_OCA\/QAA_v6_2014209.pdf."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Schofield, O., Bergmann, T., Oliver, M.J., Irwin, A., Kirkpatrick, G., Bissett, W.P., Moline, M.A., and Orrico, C. (2004). Inversion of spectral absorption in the optically complex coastal waters of the Mid-Atlantic Bight. J. Geophys. Res. Ocean., 109.","DOI":"10.1029\/2003JC002071"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4249","DOI":"10.1364\/AO.52.004249","article-title":"Approach for determining the contributions of phytoplankton, colored organic material, and nonalgal particles to the total spectral absorption in marine waters","volume":"52","author":"Lin","year":"2013","journal-title":"Appl. Opt."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2601","DOI":"10.1002\/2014JC010604","article-title":"A model for partitioning the light absorption coefficient of natural waters into phytoplankton, nonalgal particulate, and colored dissolved organic components: A case study for the Chesapeake Bay","volume":"120","author":"Zheng","year":"2015","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"237","DOI":"10.4319\/lom.2006.4.237","article-title":"Retrievals of a size parameter for phytoplankton and spectral light absorption by colored detrital matter from water-leaving radiances at SeaWiFS channels in a continental shelf region off Brazil","volume":"4","author":"Ciotti","year":"2006","journal-title":"Limnol. Oceanogr. Methods"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"384","DOI":"10.4319\/lom.2007.5.384","article-title":"Partitioning total spectral absorption in phytoplankton and colored detrital material contributions","volume":"5","author":"Oubelkheir","year":"2007","journal-title":"Limnol. Oceanogr. Methods"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"5805","DOI":"10.1364\/AO.54.005805","article-title":"Inversion of spectral absorption coefficients to infer phytoplankton size classes, chlorophyll concentration, and detrital matter","volume":"54","author":"Zhang","year":"2015","journal-title":"Appl. Opt."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1510","DOI":"10.4319\/lo.1989.34.8.1510","article-title":"Modeling in situ phytoplankton absorption from total absorption spectra in productive inland marine waters","volume":"34","author":"Roesler","year":"1989","journal-title":"Limnol. Ocean."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.rse.2017.09.008","article-title":"Remote sensing of chlorophyll\u2014A in coastal waters based on the light absorption coefficient of phytoplankton","volume":"201","author":"Zheng","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"22767","DOI":"10.1029\/95JC02176","article-title":"In situ phytoplankton absorption, fluorescence emission, and particulate backscattering spectra determined from reflectance","volume":"100","author":"Roesler","year":"1995","journal-title":"J. Geophys. Res."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1137\/S1052623496303470","article-title":"Convergence properties of the nelder-mead simplex method in low dimensions","volume":"9","author":"Lagarias","year":"1998","journal-title":"SIAM J. Optim."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"149","DOI":"10.3354\/meps105149","article-title":"In vivo absorption characteristics in 10 classes of bloom-forming phytoplankton\u2014Taxonomic characteristics and responses to photoadaptation by means of discriminant and HPLC analysis","volume":"105","author":"Johnsen","year":"1994","journal-title":"Mar. Ecol. Prog. Ser."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"614","DOI":"10.4319\/lo.2008.53.2.0614","article-title":"Relating phytoplankton photophysiological properties to community structure on large scales","volume":"53","author":"Uitz","year":"2008","journal-title":"Limnol. Oceanogr."},{"key":"ref_27","unstructured":"Forsythe, G.E. (1977). Computer Methods for Mathematical Computations, Prentice Hall. [1st ed.]."},{"key":"ref_28","unstructured":"Brent, R.P. (2013). Algorithms for Minimization without Derivatives, Dover Publications. Dover Books on Mathematics."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1090\/qam\/10666","article-title":"A Method for the Solution of Certain Non-Linear Problems in Least","volume":"2","author":"Levenberg","year":"1944","journal-title":"Q. Appl. Math."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1137\/0111030","article-title":"An Algorithm for Least-Squares Estimation of Nonlinear Parameters","volume":"11","author":"Marquardt","year":"1963","journal-title":"J. Soc. Indust. Appl. Math."},{"key":"ref_31","unstructured":"Gavin, H.P. (2019). The Levenburg-Marqurdt Algorithm for Nonlinear Least Squares Curve-Fitting Problems, Duke University."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"13321","DOI":"10.1029\/95JC00463","article-title":"Variability in the chlorophyll-specific absorption coefficients of natural phytoplankton: Analysis and parameterization phytoplankton","volume":"100","author":"Bricaud","year":"1995","journal-title":"J. Geophys. Res."},{"key":"ref_33","unstructured":"Lee, Z.-P. (2006). Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algorithms, and Applications, IOCCG. Reports of the International Ocean Colour Coordinating Group."},{"key":"ref_34","unstructured":"Mobley, C.D., and Sundman, L.K. (2021, March 22). Hydrolight 5.2 Users\u2019 Guide. Available online: https:\/\/www.sequoiasci.com\/wp-content\/uploads\/2013\/07\/HE52UsersGuide.pdf."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"235","DOI":"10.5194\/essd-8-235-2016","article-title":"A compilation of global bio-optical in situ data for ocean-colour satellite applications","volume":"8","author":"Valente","year":"2016","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"319","DOI":"10.5194\/essd-7-319-2015","article-title":"CoastColour Round Robin data sets: A database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters","volume":"7","author":"Nechad","year":"2015","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"7174","DOI":"10.1109\/TGRS.2018.2849026","article-title":"An optical algorithm to estimate downwelling diffuse attenuation coefficient in the red sea","volume":"56","author":"Tiwari","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"8710","DOI":"10.1364\/AO.36.008710","article-title":"Absorption spectrum (380\u2013700 nm) of pure water. II. Integrating cavity measurements","volume":"36","author":"Pope","year":"1997","journal-title":"Appl. Opt."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Bricaud, A., Ciotti, A.M., and Gentili, B. (2012). Spatial-temporal variations in phytoplankton size and colored detrital matter absorption at global and regional scales, as derived from twelve years of SeaWiFS data (1998\u20132009). Glob. Biogeochem. Cycles, 26.","DOI":"10.1029\/2010GB003952"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"A1139","DOI":"10.1364\/OE.25.0A1139","article-title":"Assessing uncertainties in scattering correction algorithms for reflective tube absorption measurements made with a WET Labs ac-9","volume":"25","author":"Stockley","year":"2017","journal-title":"Opt. Express"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"24937","DOI":"10.1029\/98JC02160","article-title":"Ocean color chlorophyll algorighms for SeaWiFS","volume":"103","author":"Maritorena","year":"1998","journal-title":"J. Geophys. Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.rse.2019.04.021","article-title":"Chlorophyll algorithms for ocean color sensors\u2014OC4, OC5 & OC6","volume":"229","author":"Werdell","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.marchem.2004.02.008","article-title":"Modeling the spectral shape of absorption by chromophoric dissolved organic matter","volume":"89","author":"Twardowski","year":"2004","journal-title":"Mar. Chem."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.rse.2013.09.016","article-title":"The Ocean Colour Climate Change Initiative: III. A round-robin comparison on in-water bio-optical algorithms","volume":"162","author":"Brewin","year":"2015","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1726\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:55:33Z","timestamp":1760162133000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1726"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,29]]},"references-count":44,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13091726"],"URL":"https:\/\/doi.org\/10.3390\/rs13091726","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,4,29]]}}}