HOW EFFICIENT CAN SENTINEL-2 DATA HELP SPATIAL MAPPING OF MUCILAGE EVENT IN THE MARMARA SEA?

dc.contributor.authorSunar, F.
dc.contributor.authorDervisoglu, A.
dc.contributor.authorYağmur, Nur
dc.contributor.authorColak, E.
dc.contributor.authorKuzyaka, E.
dc.contributor.authorMutlu, S.
dc.date.accessioned2025-10-29T11:08:01Z
dc.date.issued2022
dc.departmentFakülteler, Mühendislik Fakültesi, Harita Mühendisliği Bölümü
dc.description24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow -- JUN 06-11, 2022 -- Nice, FRANCE
dc.description.abstractWith the repetition of mucilage event, which is triggered by many different anthropogenic, climatic and microbiological factors, in the Marmara Sea in 2021, the importance of water quality in the seas has come to the fore again. To present the spatial distribution of the mucilage, a feasibility study has been carried out with point-based water quality measurements and remote sensing data. In-situ measurements are collected routinely within the scope of the Integrated Marine Pollution Monitoring Program (DEN-IZ) which was conducted in cooperation with the Ministry of Environment, Urbanisation and Climate Change and the Scientific and Technological Research Council of Turkey - Marmara Research Center (TUBITAK-MAM). In this preliminary study, 16 in-situ measurements, 5 of which were taken from water containing mucilage, on 29 April 2021 in the Gulf of Gemlik were used. Then, univariate regression analyzes were performed in two different scenarios (i.e. 5 mucilage points and all in-situ points) with Sentinel-2 satellite imagery and in-situ water quality measurements for 2 different parameters (i.e. chlorophyll-a - Chl-a) and turbidity). According to R-2 and accuracy assessment measures (f- and t- statistics etc.), the most suitable models were determined for two scenarios and two parameters. Finally, the performances of the selected models were tested with 2 different in-situ measurements and satellite images (dated 22 and 27 April) taken from dates close to the data set used; and it was concluded that the models created with 16 points were successful for both Chl-a and turbidity estimation for this preliminary study.
dc.description.sponsorshipInt Soc Photogrammetry & Remote Sensing
dc.description.sponsorshipIntegrated Marine Pollution Monitoring 2020-2022 Programme
dc.description.sponsorshipThis work has been supported by the Integrated Marine Pollution Monitoring 2020-2022 Programme carried out by the Ministry of Environment, Urbanization and Climate Change/General Directorate of EIA, Permit and Inspection/Department of Laboratory, Measurement and coordinated by TUBITAK-MRC ECPI.
dc.identifier.doi10.5194/isprs-archives-XLIII-B3-2022-181-2022
dc.identifier.endpage186
dc.identifier.issn1682-1750
dc.identifier.issn2194-9034
dc.identifier.orcid0000-0002-5915-6929
dc.identifier.orcid0000-0001-7455-4282
dc.identifier.orcid0000-0002-1893-6427
dc.identifier.orcid0000-0001-9222-3102
dc.identifier.scopus2-s2.0-85131941102
dc.identifier.scopusqualityQ3
dc.identifier.startpage181
dc.identifier.urihttps://doi.org/10.5194/isprs-archives-XLIII-B3-2022-181-2022
dc.identifier.urihttps://hdl.handle.net/20.500.14854/5152
dc.identifier.volume43-B3
dc.identifier.wosWOS:000855647800024
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherCopernicus Gesellschaft Mbh
dc.relation.ispartofXxiv Isprs Congress: Imaging Today, Foreseeing Tomorrow, Commission Iii
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20251020
dc.subjectWater Quality
dc.subjectMucilage
dc.subjectSentinel-2
dc.subjectRegression model
dc.subjectGulf of Gemlik
dc.subjectMarmara Sea
dc.titleHOW EFFICIENT CAN SENTINEL-2 DATA HELP SPATIAL MAPPING OF MUCILAGE EVENT IN THE MARMARA SEA?
dc.typeConference Object

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