Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/104841
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dc.contributor.authorRomán, Alejandro-
dc.contributor.authorTovar-Sánchez, Antonio-
dc.contributor.authorGauci, Adam-
dc.contributor.authorDeidun, Alan-
dc.contributor.authorCaballero, Isabel-
dc.contributor.authorColica, Emanuele-
dc.contributor.authorD’Amico, Sebastiano-
dc.contributor.authorNavarro, Gabriel-
dc.date.accessioned2023-01-04T07:01:01Z-
dc.date.available2023-01-04T07:01:01Z-
dc.date.issued2022-
dc.identifier.citationRomán, A., Tovar-Sánchez, A., Gauci, A., Deidun, A., Caballero, I., Colica, E.,...Navarro, G. (2022). Water-Quality Monitoring with a UAV-Mounted Multispectral Camera in Coastal Waters. Remote Sensing, 15(1), 237.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/104841-
dc.description.abstractRemote-sensing ocean colour studies have already been used to determine coastal water quality, coastal biodiversity, and nutrient availability. In recent years, Unmanned Aerial Vehicles (UAVs) equipped with multispectral sensors, originally designed for agriculture applications, have also enabled water-quality studies of coastal waters. However, since the sea surface is constantly changing, commonly used photogrammetric methods fail when applied to UAV images captured over water areas. In this work, we evaluate the applicability of a five-band multispectral sensor mounted on a UAV to derive scientifically valuable water parameters such as chlorophyll-a (Chl-a) concentration and total suspended solids (TSS), including a new Python workflow for the manual generation of an orthomosaic in aquatic areas exclusively based on the sensor’s metadata. We show water-quality details in two different sites along the Maltese coastline on the centimetre-scale, improving the existing approximations that are available for the region through Sentinel-3 OLCI imagery at a much lower spatial resolution of 300 m. The Chl-a and TSS values derived for the studied regions were within the expected ranges and varied between 0 to 3 mg/m3 and 10 to 20 mg/m3, respectively. Spectral comparisons were also carried out along with some statistics calculations such as RMSE, MAE, or bias in order to validate the obtained results.en_GB
dc.language.isoenen_GB
dc.publisherMDPI AGen_GB
dc.rightsinfo:eu-repo/semantics/openAccessen_GB
dc.subjectRemote sensingen_GB
dc.subjectMultispectral imagingen_GB
dc.subjectDrone aircraften_GB
dc.subjectWater quality -- Researchen_GB
dc.subjectChlorophyll -- Analysisen_GB
dc.titleWater-quality monitoring with a UAV-mounted multispectral camera in coastal watersen_GB
dc.typearticleen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holderen_GB
dc.description.reviewedpeer-revieweden_GB
dc.identifier.doi10.3390/rs15010237-
dc.publication.titleRemote Sensingen_GB
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