{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T09:24:31Z","timestamp":1768555471667,"version":"3.49.0"},"reference-count":51,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,2,11]],"date-time":"2022-02-11T00:00:00Z","timestamp":1644537600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001700","name":"Ministry of Education, Culture, Sports, Science and Technology","doi-asserted-by":"publisher","award":["17H01850 and 17H04475A"],"award-info":[{"award-number":["17H01850 and 17H04475A"]}],"id":[{"id":"10.13039\/501100001700","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Water transparency (or Secchi disk depth:\u00a0ZSD) is a key parameter of water quality; thus, it is very important to routinely monitor. In this study, we made four efforts to improve a state-of-the-art ZSD estimation algorithm that was developed in 2019 on the basis of a new underwater visibility theory proposed in 2015. The four efforts were: (1) classifying all water into clear (Type I), moderately turbid (Type II), highly turbid (Type III), or extremely turbid (Type IV) water types; (2) selecting different reference wavelengths and corresponding semianalytical models for each water type; (3) employing an estimation model to represent reasonable shapes for particulate backscattering coefficients based on the water type classification; and (4) constraining likely wavelength range at which the minimum diffuse attenuation coefficient (Kd(\u03bb)) will occur for each water type. The performance of the proposed ZSD estimation algorithm was compared to that of the original state-of-the-art algorithm using a simulated dataset (N = 91,287, ZSD values 0.01 to 44.68 m) and an in situ measured dataset (N = 305, \u00a0ZSD values 0.3 to 16.4 m). The results showed a significant improvement with a reduced mean absolute percentage error (MAPE) from 116% to 65% for simulated data and from 32% to 27% for in situ data. Outliers in the previous algorithm were well addressed in the new algorithm. We further evaluated the developed \u00a0ZSD estimation algorithm using medium resolution imaging spectrometer (MERIS) images acquired from Lake Kasumigaura, Japan. The results obtained from 19 matchups revealed that the estimated \u00a0ZSD matched well with the in situ measured \u00a0ZSD, with a MAPE of 15%. The developed ZSD estimation algorithm can probably be applied to different optical water types due to its semianalytical features.<\/jats:p>","DOI":"10.3390\/rs14040868","type":"journal-article","created":{"date-parts":[[2022,2,13]],"date-time":"2022-02-13T20:34:45Z","timestamp":1644784485000},"page":"868","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A Semianalytical Algorithm for Estimating Water Transparency in Different Optical Water Types from MERIS Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3784-8000","authenticated-orcid":false,"given":"Anastazia Daniel","family":"Msusa","sequence":"first","affiliation":[{"name":"Graduate School of Life and Environmental Sciences, University of Tsukuba, Tennoudai 1-1-1, Tsukuba 305-8572, Japan"}]},{"given":"Dalin","family":"Jiang","sequence":"additional","affiliation":[{"name":"Earth and Planetary Observation Sciences (EPOS), Biological and Environmental Sciences, Faculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6397-1144","authenticated-orcid":false,"given":"Bunkei","family":"Matsushita","sequence":"additional","affiliation":[{"name":"Faculty of Life and Environmental Sciences, University of Tsukuba, Tennoudai 1-1-1, Tsukuba 305-8572, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00027-005-0798-x","article-title":"Water clarity modeling in Lake Tahoe: Linking suspended matter characteristics to Secchi depth","volume":"68","author":"Swift","year":"2006","journal-title":"Aquat. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"C06003","DOI":"10.1029\/2006JC004007","article-title":"Estimation of light penetration, and horizontal and vertical visibility in oceanic and coastal waters from surface reflectance","volume":"112","author":"Doron","year":"2007","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_3","first-page":"1","article-title":"Long-term changes in Secchi depth and the role of phytoplankton in explaining light attenuation in the Baltic Sea","volume":"102\u2013103","author":"Laamanen","year":"2012","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.rse.2015.08.002","article-title":"Secchi disk depth: A new theory and mechanistic model for underwater visibility","volume":"169","author":"Lee","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/s10750-015-2584-7","article-title":"Semi-analytical prediction of Secchi depth using remote-sensing reflectance for lakes with a wide range of turbidity","volume":"780","author":"Fukushima","year":"2015","journal-title":"Hydrobiologia"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.rse.2017.06.018","article-title":"Retrieval of Secchi disk depth from a reservoir using a semi-analytical scheme","volume":"198","author":"Rodrigues","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Liu, Y., Xiao, C., Li, J., Zhang, F., and Wang, S. (2020). Secchi Disk Depth Estimation from China\u2019s New Generation of GF-5 Hyperspectral Observations Using a Semi-Analytical Scheme. Remote Sens., 12.","DOI":"10.3390\/rs12111849"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"4086","DOI":"10.1016\/j.rse.2007.12.013","article-title":"A 20-year Landsat water clarity census of Minnesota\u2019s 10,000 lakes","volume":"112","author":"Olmanson","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1007\/s10452-007-9080-8","article-title":"Seasonal variation in primary production of a large high altitude tropical lake (Lake Tana, Ethiopia): Effects of nutrient availability and water transparency","volume":"41","author":"Wondie","year":"2007","journal-title":"Aquat. Ecol."},{"key":"ref_10","first-page":"25","article-title":"Relations between water transparency and maximum depth of macrophyte colonization in lakes","volume":"23","author":"Canfield","year":"1985","journal-title":"J. Aquat. Plant Manag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3831","DOI":"10.1364\/AO.38.003831","article-title":"Hyperspectral remote sensing for shallow waters: 2 Deriving bottom depths and water properties by optimization","volume":"38","author":"Lee","year":"1999","journal-title":"Appl. Opt."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1016\/S0380-1330(93)71245-9","article-title":"Changes in Planktonic Diatoms and Water Transparency in Hatchery Bay, Bass Island Area, Western Lake Erie Since the Establishment of the Zebra Mussel","volume":"19","author":"Holland","year":"1993","journal-title":"J. Great Lakes Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/j.ecss.2008.04.024","article-title":"Relationships between suspended particulate material, light attenuation and Secchi depth in UK marine waters","volume":"79","author":"Devlin","year":"2008","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.rse.2012.05.018","article-title":"High-frequency remote monitoring of large lakes with MODIS 500 m imagery","volume":"124","author":"McCullough","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Bai, S., Gao, J., Sun, D., and Tian, M. (2020). Monitoring Water Transparency in Shallow and Eutrophic Lake Waters Based on GOCI Observations. Remote Sens., 12.","DOI":"10.3390\/rs12010163"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"373","DOI":"10.23818\/limn.39.24","article-title":"Monitoring water transparency of a hypertrophic lake (the Albufera of Val\u00e8ncia) using multitemporal Sentinel-2 satellite images","volume":"39","author":"Soria","year":"2020","journal-title":"Limnetica"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"139351","DOI":"10.1016\/j.scitotenv.2020.139351","article-title":"A novel index for assessing the water quality of urban landscape lakes based on water transparency","volume":"735","author":"Chang","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2986","DOI":"10.1016\/j.rse.2011.05.019","article-title":"Ocean transparency from space: Validation of algorithms estimating Secchi depth using MERIS, MODIS and SeaWiFS data","volume":"115","author":"Doron","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"12191","DOI":"10.1364\/OE.26.012191","article-title":"Variations of transparency derived from GOCI in the Bohai Sea and the Yellow Sea","volume":"26","author":"Mao","year":"2018","journal-title":"Opt. Express"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"7642","DOI":"10.1364\/OE.27.007642","article-title":"Deriving inherent optical properties from classical water color measurements: Forel-Ule index and Secchi disk depth","volume":"27","author":"Wang","year":"2019","journal-title":"Opt. Express"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.isprsjprs.2019.04.002","article-title":"An improved algorithm for estimating the Secchi disk depth from remote sensing data based on the new underwater visibility theory","volume":"152","author":"Jiang","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Vundo, A., Matsushita, B., Jiang, D., Gondwe, M., Hamzah, R., Setiawan, F., and Fukushima, T. (2019). An Overall Evaluation of Water Transparency in Lake Malawi from MERIS Data. Remote Sens., 11.","DOI":"10.3390\/rs11030279"},{"key":"ref_23","unstructured":"Duntley, S.Q. (1952). The Visibility of Submerged Objects, Visibility Laboratory, Massachusetts Institute of Technology; Scripps Institution of Oceanography."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2020JC016172","article-title":"Secchi Disk Measurements in Turbid Water","volume":"125","author":"Bowers","year":"2020","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Uudeberg, K., Ansko, I., P\u00f5ru, G., Ansper, A., and Reinart, A. (2019). Using Optical Water Types to Monitor Changes in Optically Complex Inland and Coastal Waters. Remote Sens., 11.","DOI":"10.3390\/rs11192297"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Liu, X., Lee, Z., Zhang, Y., Lin, J., Shi, K., Zhou, Y., Qin, B., and Sun, Z. (2019). Remote Sensing of Secchi Depth in Highly Turbid Lake Waters and Its Application with MERIS Data. Remote Sens., 11.","DOI":"10.3390\/rs11192226"},{"key":"ref_27","first-page":"102187","article-title":"Observations of water transparency in China\u2019s lakes from space","volume":"92","author":"Liu","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Zeng, S., Lei, S., Li, Y., Lyu, H., Xu, J., Dong, X., Wang, R., Yang, Z., and Li, J. (2020). Retrieval of Secchi Disk Depth in Turbid Lakes from GOCI Based on a New Semi-Analytical Algorithm. Remote Sens., 12.","DOI":"10.3390\/rs12091516"},{"key":"ref_29","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_30","doi-asserted-by":"crossref","first-page":"3761","DOI":"10.1109\/TGRS.2012.2220147","article-title":"Retrieval of Inherent Optical Properties for Turbid Inland Waters from Remote-Sensing Reflectance","volume":"51","author":"Yang","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"112386","DOI":"10.1016\/j.rse.2021.112386","article-title":"Remotely estimating total suspended solids concentration in clear to extremely turbid waters using a novel semi-analytical method","volume":"258","author":"Jiang","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"7442","DOI":"10.1364\/AO.38.007442","article-title":"Estimation of the remote-sensing reflectance from above-surface measurements","volume":"38","author":"Mobley","year":"1999","journal-title":"Appl. Opt."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.isprsjprs.2020.05.003","article-title":"A simple and effective method for removing residual reflected skylight in above-water remote sensing reflectance measurements","volume":"165","author":"Jiang","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_34","unstructured":"NIES (2020, August 24). Lake Kasumigaura Database, National Institute for Environmental Studies, Japan. Available online: http:\/\/db.cger.nies.go.jp\/gem\/moni-e\/inter\/GEMS\/database\/kasumi\/index.html."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"10909","DOI":"10.1029\/JD093iD09p10909","article-title":"A Semianalytic Radiance Model of Ocean Color","volume":"93","author":"Gordon","year":"1988","journal-title":"J. Geophys. Res."},{"key":"ref_36","first-page":"1","article-title":"A model for the diffuse attenuation coefficient of downwelling irradiance","volume":"110","author":"Lee","year":"2005","journal-title":"J. Geophys. Res. Earth Surf."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4241","DOI":"10.1002\/jgrc.20308","article-title":"Penetration of UV-visible solar radiation in the global oceans: Insights from ocean color remote sensing","volume":"118","author":"Lee","year":"2013","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"12685","DOI":"10.1364\/OE.17.012685","article-title":"Scattering by pure seawater at high salinity","volume":"17","author":"Zhang","year":"2009","journal-title":"Opt. Express"},{"key":"ref_39","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. Opt."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2005","DOI":"10.1080\/01431160500075857","article-title":"Detection of intense plankton blooms using the 709 nm band of the MERIS imaging spectrometer","volume":"26","author":"Gower","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.1109\/LGRS.2013.2284343","article-title":"Application of a Semianalytical Algorithm to Remotely Estimate Diffuse Attenuation Coefficient in Turbid Inland Waters","volume":"11","author":"Yang","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Curtarelli, V.P., Barbosa, C.C.F., Maciel, D.A., J\u00fanior, R.F., Carlos, F.M., Novo, E.D.M., Curtarelli, M., and Silva, E. (2020). Diffuse Attenuation of Clear Water Tropical Reservoir: A Remote Sensing Semi-Analytical Approach. Remote Sens., 12.","DOI":"10.3390\/rs12172828"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"4065","DOI":"10.5194\/bg-15-4065-2018","article-title":"An estuarine-tuned quasi-analytical algorithm (QAA-V): Assessment and application to satellite estimates of SPM in Galveston Bay following Hurricane Harvey","volume":"15","author":"Joshi","year":"2018","journal-title":"Biogeosciences"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2175","DOI":"10.1016\/j.asr.2018.12.023","article-title":"An assessment of semi-analytical models based on the absorption coefficient in retrieving the chlorophyll-a concentration from a reservoir","volume":"63","author":"Andrade","year":"2019","journal-title":"Adv. Space Res."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"13155","DOI":"10.1364\/OE.390859","article-title":"Evaluating semi-analytical algorithms for estimating inherent optical properties in the South China Sea","volume":"28","author":"Deng","year":"2020","journal-title":"Opt. Express"},{"key":"ref_46","unstructured":"Lee, Z., Carder, K.L., and Arnone, R. (2014). Update of the Quasi-Analytical Algorithm (QAA_v6), International Ocean Colour Coordnating Group\u2014IOCCG."},{"key":"ref_47","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_48","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_49","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.isprsjprs.2014.12.022","article-title":"A hybrid algorithm for estimating the chlorophyll-a concentration across different trophic states in Asian inland waters","volume":"102","author":"Matsushita","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1002\/lno.10674","article-title":"Optical types of inland and coastal waters","volume":"63","author":"Spyrakos","year":"2018","journal-title":"Limnol. Oceanogr."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"111768","DOI":"10.1016\/j.rse.2020.111768","article-title":"Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters","volume":"246","author":"Balasubramanian","year":"2020","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/4\/868\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:17:57Z","timestamp":1760134677000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/4\/868"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,11]]},"references-count":51,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["rs14040868"],"URL":"https:\/\/doi.org\/10.3390\/rs14040868","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,11]]}}}