{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T23:32:27Z","timestamp":1769729547085,"version":"3.49.0"},"reference-count":105,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,4]],"date-time":"2022-02-04T00:00:00Z","timestamp":1643932800000},"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>Given the great importance of lakes in Earth\u2019s environment and human life, continuous water quality (WQ) monitoring within the frame of the Water Framework Directive (WFD) is the most crucial aspect for lake management. In this study, Earth Observation (EO) data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) sensors have been combined with co-orbital in situ measurements from 50 lakes located in Greece with the main objective of delivering robust WQ assessment models. Correlation analysis among in situ co-orbital WQ data (Chlorophylla, Secchi depths, Total phosphorus-TP-) contributed to distinguishing their inter-relationships and improving the WQ models\u2019 accuracy. Subsequently, stepwise multiple regression analysis (MLR) of the available TP and Secchi depth datasets was implemented to explore the potential to establish optimal quantitative models regardless of lake characteristics. Then, further MLR analysis concerning whether the lakes are natural or artificial was conducted with the basic aim of generating different remote sensing derived models for different types of lakes, while their combination was further utilized to assess their trophic status. Correlation matrix results showed a high and positive relationship between TP and Chlorophyll-a (0.85), whereas high negative relationships were found between Secchi depth with TP (\u22120.84) and Chlorophyll-a (\u22120.83). MLRs among Landsat data and Secchi depths resulted in 3 optimal models concerning the assessment of Secchi depth of all lakes (Secchigeneral; R = 0.78; RMSE = 0.24 m), natural (Secchinatural; R = 0.95; RMSE = 0.14 m) and artificial (Secchiartificial; R = 0.62; RMSE = 0.1 m), with reliable accuracy. Study findings showed that TP-related MLR analyses failed to deliver a statistically acceptable model for the reservoirs; nevertheless, they delivered a robust TPgeneral (R = 0.71; RMSE = 1.41 mg\/L) and TPnatural model (R = 0.93; RMSE = 1.43 mg\/L). Subsequently, trophic status classification was conducted herein, calculating Carlson\u2019s Trophic State Index (TSI) initially throughout all lakes and then oriented toward natural-only and artificial-only lakes. Those three types of TSI (general, natural, artificial) were calculated based on previously published satellite-derived Chlorophyll-a (Chl-a) assessment models and the hereby specially designed WQ models (Secchi depth, TP). The higher deviation of satellite-derived TSI values in relation to in situ ones was detected in reservoirs and shallower lakes (mean depth &lt; 5 m), indicating noticeable divergences among natural and artificial lakes. All in all, the study findings provide important support toward the perpetual WQ monitoring and trophic status prediction of Greek lakes and, by extension, their sustainable management, particularly in cases when ground truth data is limited.<\/jats:p>","DOI":"10.3390\/rs14030739","type":"journal-article","created":{"date-parts":[[2022,2,6]],"date-time":"2022-02-06T20:38:40Z","timestamp":1644179920000},"page":"739","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Modelling of Greek Lakes Water Quality Using Earth Observation in the Framework of the Water Framework Directive (WFD)"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4433-485X","authenticated-orcid":false,"given":"Vassiliki","family":"Markogianni","sequence":"first","affiliation":[{"name":"Institute of Marine Biological Resources and Inland Waters, Hellenic Centre for Marine Research, 46.7 km of Athens-Sounio Avenue, 19013 Attica, Greece"}]},{"given":"Dionissios","family":"Kalivas","sequence":"additional","affiliation":[{"name":"Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos, 11855 Athens, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1442-1423","authenticated-orcid":false,"given":"George P.","family":"Petropoulos","sequence":"additional","affiliation":[{"name":"Department of Geography, Harokopio University of Athens, El. Venizelou 70, Kallithea, 17671 Athens, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6669-6897","authenticated-orcid":false,"given":"Elias","family":"Dimitriou","sequence":"additional","affiliation":[{"name":"Institute of Marine Biological Resources and Inland Waters, Hellenic Centre for Marine Research, 46.7 km of Athens-Sounio Avenue, 19013 Attica, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.envsoft.2018.01.023","article-title":"A new synergistic approach for monitoring wetlands using Sentinels -1 and 2 data with object-based Machine Learning algorithms","volume":"104","author":"Whyte","year":"2018","journal-title":"Environ. Model Softw."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1038\/535349a","article-title":"Study role of climate change in extreme threats to water quality","volume":"535","author":"Michalak","year":"2016","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2373","DOI":"10.3390\/rs4082373","article-title":"Comparative analysis of four models to estimate chlorophyll\u2014A concentration in case-2 waters using MODerate resolution imaging spectroradiometer (MODIS) imagery","volume":"4","author":"Chokmani","year":"2012","journal-title":"Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.1100\/tsw.2009.135","article-title":"Water quality determination of K\u00fc\u00e7\u00fck\u00e7ekmece Lake, Turkey by using multispectral satellite data","volume":"9","author":"Alparslan","year":"2009","journal-title":"Sci. World J."},{"key":"ref_5","unstructured":"Shafique, N.A., Fulk, F.A., Autrey, B.C., and Flotemersch, J.E. (2003, January 5\u20137). Hyperspectral remote sensing of water quality parameters for large rivers in the Ohio river basin. Proceedings of the Ohio River Basin Consortium for Research and Education, Marietta, OH, USA."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1608","DOI":"10.2166\/nh.2017.116","article-title":"Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir","volume":"49","author":"Bonansea","year":"2018","journal-title":"Hydrol. Res."},{"key":"ref_7","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_8","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/S0048-9697(00)00692-6","article-title":"Detecting chlorophyll, Secchi disk depth and surface temperature in a sub-alpine lake using Landsat imagery","volume":"268","author":"Giardino","year":"2001","journal-title":"Sci. Total Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/s11783-008-0027-7","article-title":"Water quality monitoring inland water body through remote sensing\u2014A case study of Guanting Reservoir in Beijing, China","volume":"2","author":"He","year":"2008","journal-title":"Front. Environ. Sci. Engin. China"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1109\/36.103296","article-title":"Quantitative modeling of inland water quality for high resolution MSS system","volume":"29","author":"Dekker","year":"1991","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1007\/s11270-009-0140-7","article-title":"Effect of lake management efforts on the trophic state of a subtropical shallow lake in Lakeland, Florida, USA","volume":"207","author":"Poor","year":"2010","journal-title":"Water Air Soil Pollut."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1080\/014311601450059","article-title":"Determination of chlorophyll concentration changes in Lake Garda using an image-based radiative transfer code for Landsat TM images","volume":"22","author":"Brivio","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1016\/j.rse.2005.04.018","article-title":"Operational algorithm for the retrieval of water quality in the Great Lakes","volume":"97","author":"Pozdnyakov","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1521","DOI":"10.1080\/01431160500419311","article-title":"Remote sensing of the water quality of shallow lakes: A mixture modeling approach to quantifying phytoplankton in water characterized by high suspended sediment","volume":"27","author":"Tyler","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Chatziantoniou, A., Petropoulos, G.P., and Psomiadis, E. (2017). Co-Orbital Sentinel 1 and 2 for LULC mapping with emphasis on wetlands in a Mediterranean setting based on Machine Learning. Remote Sens., 9.","DOI":"10.3390\/rs9121259"},{"key":"ref_16","unstructured":"Magoom, O.T., Converse, H., Miner, D., Clark, D., and Tobin, L.T. (1985). Use of remote sensing to assess estuarine habitats. Proceedings of the 4th Symposium on Coastal and Ocean Management, American Society of Civil Engineers."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1007\/BF00122030","article-title":"Report of the working group on water colour","volume":"18","author":"Morel","year":"1980","journal-title":"Bound. -Layer Meteorol."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Gower, J. (1981). Water Colour Measurements. Oceanography from Space, Plenum.","DOI":"10.1007\/978-1-4613-3315-9"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"103187","DOI":"10.1016\/j.earscirev.2020.103187","article-title":"Monitoring inland water quality using remote sensing: Potential and limitations of spectral indices, bio-optical simulations, machine learning, and cloud computing","volume":"205","author":"Sagan","year":"2020","journal-title":"Earth-Sci. Rev."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Topp, S., Pavelsky, T., Jensen, D., Simard, M., and Ross, M. (2020). Research trends in the use of remote sensing for inland water quality science: Moving towards multidisciplinary applications. Water, 12.","DOI":"10.3390\/w12010169"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Gholizadeh, M., Melesse, A., and Reddi, L. (2016). A comprehensive review on water quality parameters estimation using remote sensing techniques. Sensors, 16.","DOI":"10.3390\/s16081298"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.rse.2011.11.013","article-title":"Review of constituent retrieval in optically deep and complex waters from satellite imagery","volume":"118","author":"Odermatt","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_23","unstructured":"Barber, R.T., Mooers, N.K., Bowman, M.J., and Zeitzschel, B. (1983). Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery. A Review, Lecture Notes on Coastal and Estuarine Studies, Springer."},{"key":"ref_24","unstructured":"Sathyendranath, S. (2000). Remote Sensing of Ocean Colour in Coastal, and Other Optically-Complex, Waters, IOCCG. Reports of the International Ocean-Colour Coordinating Group, No. 3."},{"key":"ref_25","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_26","doi-asserted-by":"crossref","first-page":"24116","DOI":"10.3390\/s141224116","article-title":"Evaluation of multi-resolution satellite sensors for assessing water quality and bottom depth of lake garda","volume":"14","author":"Giardino","year":"2014","journal-title":"Sensors"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2037","DOI":"10.1080\/01431161003645840","article-title":"Landsat remote sensing of chlorophyll a concentrations in central north island lakes of New Zealand","volume":"32","author":"Allan","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"809","DOI":"10.7780\/kjrs.2014.30.6.11","article-title":"High resolution ocean color products estimation in Fjord of Svalbard, arctic sea using Landsat-8 oli","volume":"30","author":"Kim","year":"2014","journal-title":"Korean J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5009","DOI":"10.1007\/s10661-014-3755-0","article-title":"Water quality monitoring and assessment of an urban Mediterranean lake facilitated by remote sensing applications","volume":"186","author":"Markogianni","year":"2014","journal-title":"Environ. Monit. Assess."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Markogianni, V., Kalivas, D., Petropoulos, G., and Dimitriou, E. (2018). An appraisal of the potential of Landsat 8 in estimating chlorophyll-a, ammonium concentrations and other water quality indicators. Remote Sens., 10.","DOI":"10.3390\/rs10071018"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Markogianni, V., Kalivas, D., Petropoulos, G.P., and Dimitriou, E. (2020). Estimating Chlorophyll-a of Inland Water Bodies in Greece Based on Landsat Data. Remote Sens., 12.","DOI":"10.3390\/rs12132087"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/S0924-2716(02)00120-X","article-title":"Towards airborne remote sensing of water quality in The Netherlands\u2014Validation and error analysis","volume":"57","author":"Hans","year":"2002","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1093\/ps\/78.5.674","article-title":"Phosphorus: A rate limiting nutrient in surface waters","volume":"78","author":"Correll","year":"1999","journal-title":"Poult. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3069","DOI":"10.1080\/01431169508954609","article-title":"Telespectrometrical estimation of water transparency, chlorophyll-a and total phosphorus concentration of Lake Peipsi","volume":"16","author":"Kutser","year":"1995","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.scitotenv.2004.02.020","article-title":"Water quality change in reservoirs of Shenzhen, China: Detection using LANDSAT\/TM data","volume":"328","author":"Wang","year":"2004","journal-title":"Sci. Total Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2309","DOI":"10.1080\/01431160902973873","article-title":"Empirical estimation of total phosphorus concentration in the mainstream of the Qiantang River in China using Landsat TM data","volume":"31","author":"Wu","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.4319\/lo.1982.27.6.1101","article-title":"The nitrogen and phosphorus dependence of algal biomass in lakes: An empirical and theoretical analysis","volume":"27","author":"Smith","year":"1982","journal-title":"Limnol. Oceanogr."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"7848","DOI":"10.1021\/es061359b","article-title":"Estimating nutrients and chlorophyll a relationships in Finnish lakes","volume":"40","author":"Malve","year":"2006","journal-title":"Environ. Sci. Technol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1364","DOI":"10.1139\/f79-195","article-title":"Indicators of phosphorus and nitrogen deficiency in five algae in culture","volume":"36","author":"Healey","year":"1979","journal-title":"Can. J. Fish Aquat. Res."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2621","DOI":"10.1139\/f06-146","article-title":"Relationships among nutrients, algae, and land use in urbanized southern California streams","volume":"63","author":"Busse","year":"2006","journal-title":"Can. J. Fish. Aquat. Sci."},{"key":"ref_41","first-page":"1","article-title":"A remote sensing based frame work for predicting water quality of different source waters","volume":"34","author":"Akbar","year":"2010","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Song, K., Zhang, B., Wang, Z., Li, F., Duan, H., and Guo, Y. (August, January 31). Water TOC and TP concentration estimation using Landsat TM data with empirical algorithms in Chagan lake, China. Proceedings of the 2006 IEEE International Symposium on Geoscience and Remote Sensing, Denver, CO, USA.","DOI":"10.1109\/IGARSS.2006.882"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"361","DOI":"10.4319\/lo.1977.22.2.0361","article-title":"A trophic state index for lakes","volume":"22","author":"Carlson","year":"1977","journal-title":"Limnol. Oceanogr."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.1007\/s11270-011-0959-6","article-title":"Hyperspectral Remote Sensing of Total Phosphorus (TP) in Three Central Indiana Water Supply Reservoirs","volume":"223","author":"Song","year":"2012","journal-title":"Water Air Soil Pollut."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Fuller, L.M., Aichele, S.S., and Minnerick, R.J. (2004). Predicting Water Quality by Relating Secchi-Disk Transparency and Chlorophyll a Measurements to Satellite Imagery for Michigan Inland Lakes, August 2002, US Geological Survey Scientific Investigations Report.","DOI":"10.3133\/sir20045086"},{"key":"ref_46","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_47","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.rse.2012.03.006","article-title":"Combining lake and watershed characteristics with Landsat TM data for remote estimation of regional lake clarity","volume":"123","author":"McCullough","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.1080\/01431169308953955","article-title":"Detecting water quality parameters in the norfolk broads, U.K., using landsat imagery","volume":"14","author":"Baban","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"27","DOI":"10.4081\/jlimnol.2003.s1.27","article-title":"Regional Assessment of lake water clarity using satellite remote sensing","volume":"62","author":"Nelson","year":"2003","journal-title":"J. Limnol."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"7245","DOI":"10.1007\/s10661-013-3098-2","article-title":"Hindcasting water clarity from Landsat satellite images of unmonitored shallow lakes in the Waikato region, New Zealand","volume":"185","author":"Hicks","year":"2013","journal-title":"Environ. Monit. Assess."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2183","DOI":"10.1080\/01431160701422254","article-title":"Comparison of MODIS and Landsat TM5 images for mapping tempo-spatial dynamics of Secchi disk depths in Poyang Lake National Nature Reserve, China","volume":"29","author":"Wu","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"6855","DOI":"10.1080\/01431161.2010.512947","article-title":"A current review of empirical procedures of remote sensing in Inland and near-coastal transitional waters","volume":"32","author":"Matthews","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_53","unstructured":"Olmanson, L.G., Kloiber, S.M., Bauer, M.E., and Brezonik, P.L. (2001). Image Processing Protocol for Regional Assessments of Lake Water Quality, University of Minnesota."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"373","DOI":"10.4319\/lo.1980.25.2.0373","article-title":"Light, Secchi Disks, and Trophic States","volume":"25","author":"Megard","year":"1980","journal-title":"Limnol. Oceanogr."},{"key":"ref_55","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_56","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1007\/s10750-006-0221-1","article-title":"Alternate stable states and the shape of the lake trophic distribution","volume":"571","author":"Peckham","year":"2006","journal-title":"Hydrobiologia"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1002\/iroh.19290220128","article-title":"The Scope of chief problems of regional limnology","volume":"21","author":"Nauman","year":"1929","journal-title":"Int. Rev. Ges. Hydrobiol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1007\/s40710-018-0315-6","article-title":"Relationships among land use patterns, hydromorphological features and physicochemical parameters of surface waters: WFD lake monitoring in Greece","volume":"5","author":"Mavromati","year":"2018","journal-title":"Environ. Process."},{"key":"ref_59","unstructured":"American Public Health Association (APHA) (1989). Standard Methods for the Examination of Water and Wastewater, American Public Health Association. [17th ed.]."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/S0034-4257(02)00022-6","article-title":"A procedure for regional lake water clarity assessment using Landsat multispectral data","volume":"82","author":"Kloiber","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1016\/j.ecss.2004.06.019","article-title":"Use of satellite imagery for water quality studies in New York Harbor","volume":"61","author":"Hellweger","year":"2004","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_62","first-page":"1","article-title":"Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression","volume":"65","author":"Chu","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Barrett, D.C., and Frazier, A.E. (2016). Automated Method for Monitoring Water Quality Using Landsat Imagery. Water, 8.","DOI":"10.3390\/w8060257"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"3965","DOI":"10.48084\/etasr.2664","article-title":"A Satellite-based Remote Sensing Technique for Surface Water Quality Estimation","volume":"9","author":"Japitana","year":"2019","journal-title":"Eng. Technol. Appl. Sci. Res."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"1632","DOI":"10.1109\/JSTARS.2014.2301295","article-title":"Empirical Relationships for Monitoring Water Quality of Lakes and Reservoirs Through Multispectral Images","volume":"7","author":"Caselles","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"ref_66","unstructured":"Dancey, C.P., and Reidy, J. (2007). Statistics without Maths for Psychology, Pearson Education. [4th ed.]."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"A915","DOI":"10.1364\/OE.26.00A915","article-title":"Approach for identifying optically shallow pixels when processing ocean-color imagery","volume":"26","author":"McKinna","year":"2018","journal-title":"Opt. Express"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1007\/s10661-015-4616-1","article-title":"Assessment of water quality based on Landsat 8 operational land imager associated with human activities in Korea","volume":"187","author":"Lim","year":"2015","journal-title":"Environ. Monit. Assess."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1831","DOI":"10.1016\/j.jes.2014.06.019","article-title":"Assessment of nutrient distribution in Lake Champlain using satellite remote sensing","volume":"26","author":"Isenstein","year":"2014","journal-title":"J. Environ. Sci."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1109\/JSTARS.2011.2174339","article-title":"Using Landsat\/TM imagery to estimate nitrogen and phosphorus concentration in Taihu Lake, China","volume":"5","author":"Chen","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"4171","DOI":"10.1109\/JSTARS.2015.2438293","article-title":"Using remote sensing to track variation in phosphorus and its interaction with chlorophyll-a and suspended sediment","volume":"8","author":"Huang","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1111\/lre.12054","article-title":"Determining the spatial variation of phosphorus in a lake system using remote sensing techniques","volume":"19","author":"Moses","year":"2014","journal-title":"Lakes Reserv. Res. Manag."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1080\/07438140509354442","article-title":"Landsat-based remote sensing of lake water quality characteristics, including chlorophyll and colored dissolved organic matter (CDOM)","volume":"2","author":"Brezonik","year":"2005","journal-title":"Lake Reserv. Manag."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"3349","DOI":"10.1080\/014311698214037","article-title":"Laboratory experiment, field and remotely sensed data analysis for the assessment of suspended solids concentration and secchi depth of the reservoir surface water","volume":"19","author":"Choubey","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"3123","DOI":"10.1080\/01431161.2020.1868606","article-title":"Secchi Depth estimation for optically-complex waters based on spectral angle mapping\u2014Derived water classification using Sentinel-2 data","volume":"42","author":"Zhou","year":"2021","journal-title":"Int. J. Remote Sens."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"107487","DOI":"10.1016\/j.ecss.2021.107487","article-title":"Spatiotemporal variability of Secchi depths of the North Arabian Gulf over the last two decades","volume":"260","author":"Ohammad","year":"2021","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Kratzer, S., Kyryliuk, D., Edman, M., Philipson, P., and Lyon, S.W. (2019). Synergy of Satellite, In Situ and Modelled Data for Addressing the Scarcity of Water Quality Information for Eutrophication Assessment and Monitoring of Swedish Coastal Waters. Remote Sens., 11.","DOI":"10.3390\/rs11172051"},{"key":"ref_78","unstructured":"Prasad, A.D., and Siddaraju, P. (2012). Carlson\u2019s Trophic State Index for the assessment of trophic status of two lakes in Mandya district. Adv. Appl. Sci. Res., 3."},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Zheng, L., An, Z., Chen, X., and Liu, H. (2021). Changes in Water Environment in Erhai Lake and Its Influencing Factors. Water, 13.","DOI":"10.3390\/w13101362"},{"key":"ref_80","unstructured":"Hackney, C.T., Adams, S.M., and Martin, W.H. (1992). Reservoirs. Biodiversity of the Southeastern United States: Aquatic communities, John Wiley and Sons."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1139\/f81-058","article-title":"Prediction of total phosphorus concentrations, chlorophyll a, and secchi depths in natural and artificial lakes","volume":"38","author":"Canfield","year":"1981","journal-title":"Can. J. Fish. Aquat. Sci."},{"key":"ref_82","unstructured":"Virginia Water Resources Research Institute, and State University Blacksburg (2020, October 10). Nutrients in Lakes and Reservoirs-Aliterature Review for Use in Nutrient Criteria Development. VWRRC Special Report SR34\u20132007. Virginia. Available online: http:\/\/www.vwrrc.vt.edu."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1007\/BF00013717","article-title":"Prediction of Secchi disc depths in Florida lakes: Impact of algal biomass and organic color","volume":"99","author":"Canfield","year":"1983","journal-title":"Hydrobiologia"},{"key":"ref_84","unstructured":"Heiskary, S., and Wilson, B. (2005). Minnesota Lake Water Quality: Developing Nutrient Criteria, Minnesota Pollution Control Agency. [3rd ed.]."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1007\/BF00006726","article-title":"The effect of non-algal turbidity on the relationship of Secchi depth to chlorophyll a","volume":"140","author":"Lind","year":"1986","journal-title":"Hydrobiologia"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"371","DOI":"10.4319\/lo.1980.25.2.0371","article-title":"The use of chlorophyll-secchi disk relationships","volume":"25","author":"Lorenzen","year":"1980","journal-title":"Limnol. Oceanogr."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"1057","DOI":"10.1080\/014311699212849","article-title":"Use of satellite imagery to estimate surface chlorophyll a and Secchi disc depth of Bull Shoals Reservoir, Arkansas, USA","volume":"20","author":"Allee","year":"1999","journal-title":"Int. J. Remote Sens."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"111284","DOI":"10.1016\/j.rse.2019.111284","article-title":"A harmonized image processing work-flow using Sentinel-2\/MSI and Landsat-8\/OLI for mapping water clarity in opti-cally variable lake systems","volume":"231","author":"Page","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"116844","DOI":"10.1016\/j.watres.2021.116844","article-title":"Remote sensing estimation of water clarity for various lakes in China","volume":"192","author":"Zhang","year":"2021","journal-title":"Water Res."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1080\/02626669609491524","article-title":"Remote sensing, ecological water quality modelling and in situ measurements: A case study in shallow lakes","volume":"41","author":"Dekker","year":"1996","journal-title":"Hydrolog. Sci. J."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"2477","DOI":"10.1016\/S0043-1354(99)00419-4","article-title":"Suspended soil as a source of potentially bioavailable phosphorus in surface runoff waters from clay soils","volume":"34","author":"Uusitalo","year":"2000","journal-title":"Water Res."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/0034-4257(90)90039-O","article-title":"The relationship of MSS and TM digital data with suspended sediments, chlorophyll, and temperature in Moon Lake, Mississippi","volume":"33","author":"Ritchie","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_93","first-page":"465","article-title":"Landsat Thematic Mapper monitoring of turbid inland water quality","volume":"58","author":"Lathrop","year":"1992","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_94","unstructured":"Lillesand, T.M., and Kiefer, R.W. (2000). Remote Sensing and Image Interpretation, John Wiley and Sons. [4th ed.]."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1117\/12.190060","article-title":"The optical properties of pure water","volume":"2258","author":"Buiteveld","year":"1994","journal-title":"SPIE Ocean. Opt. XII"},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"8858408","DOI":"10.1155\/2020\/8858408","article-title":"Modelling Reservoir Chlorophyll-a, TSS, and Turbidity Using Sentinel-2A MSI and Landsat-8 OLI Satellite Sensors with Empirical Multivariate Regression","volume":"2020","author":"Ouma","year":"2020","journal-title":"J. Sens."},{"key":"ref_97","unstructured":"Kontopoulou, E., Kolokoussis, P., and Karantzalos, K. (2017, January 5\u20139). Water quality estimation in Greek lakes from Landsat 8 multispectral satellite data. Proceedings of the 10th World Congress of the European Water Resources Association (EWRA) on Water Resources and Environment (EWRA2017), European Water 2017 No.58, Athens, Greece."},{"key":"ref_98","first-page":"25","article-title":"Spectral characterization of aquatic nutrients and water quality parameters in marine environment","volume":"15","author":"Tripathi","year":"2004","journal-title":"Bibliogr. Inform."},{"key":"ref_99","unstructured":"Membrillo-Abad, A.S., Torres-Vera, M.A., Alcocer, J., Prol-Ledesma, R.M., Oseguera, L.A., and Ruiz-Armenta, J.R. (2016). Trophic State Index estimation from remote sensing of lake Chapala, M\u00e9xico. Rev. Mex. Cienc. Geol., 33."},{"key":"ref_100","first-page":"67","article-title":"Trophic State Index derivation through the remote sensing of Case-2 water bodies in the Mediterranean region","volume":"6","author":"Papoutsa","year":"2014","journal-title":"Cent. Eur. J. Geosci."},{"key":"ref_101","doi-asserted-by":"crossref","unstructured":"Rivani, A., and Wicaksono, P. (2018, January 20\u201321). Water trophic status mapping of tecto-volcanic maninjau lake during algae bloom using landsat 8 OLI satellite imagery. Proceedings of the 2018 IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES), Bali, Indonesia.","DOI":"10.1109\/ICARES.2018.8547055"},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1007\/s10661-006-9215-8","article-title":"Water quality monitoring using remote sensing in support of the EU water framework directive (WFD): A case study in the Gulf of Finland","volume":"124","author":"Chen","year":"2007","journal-title":"Environ. Monit. Assess."},{"key":"ref_103","unstructured":"Thorton, K.W., Kimmel, B.L., and Payne, F.E. (1990). Reservoir primary production. Reservoir Limnology: Ecological Perspectives, John Wiley and Sons."},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.rse.2011.09.022","article-title":"Landsat: Building a strong future","volume":"122","author":"Loveland","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.rse.2013.09.016","article-title":"Groom 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\/14\/3\/739\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:14:22Z","timestamp":1760134462000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/3\/739"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,4]]},"references-count":105,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["rs14030739"],"URL":"https:\/\/doi.org\/10.3390\/rs14030739","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,4]]}}}