| Summary: | Remote-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 (<i>Chl-a</i>) 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 <i>Chl-a</i> and TSS values derived for the studied regions were within the expected ranges and varied between 0 to 3 mg/m<sup>3</sup> and 10 to 20 mg/m<sup>3</sup>, respectively. Spectral comparisons were also carried out along with some statistics calculations such as <i>RMSE</i>, <i>MAE</i>, or bias in order to validate the obtained results.
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