Abstract

In recent decades, the monitoring of coastal areas has become a priority due to the continued growth of human population pressure. Areas such as these constitute biodiversity hotspots in which the increase in phytoplankton blooms has become a socioecological problem with severe impacts at global and regional levels. One area affected by these blooms is the Patagonian fjords, a complex and intricate coastal system that is highly exposed to climate forces and anthropogenic activities, particularly the aquaculture industry (primarily salmon and mussel farming), which is the main driver of the local economy. In this context, ensuring prompt and accurate monitoring of phytoplankton in the area is crucial. As such, the focus of the present study is on the use of a new technology that combines hyperspectral sensors and unmanned aerial vehicles (UAVs) to detect, identify and differentiate phytoplankton species from optical data. Findings have identified differences not only between diatoms and dinoflagellates through the shape and magnitude of the spectral signal at 440, 470, 500, 520, 550, 570 and 580 nm, but also at the genus level (Rhizosolenia sp., Pseudo-nitzschia sp., Skeletonema sp., Chaetoceros sp. and Leptocylindrus sp.) and species level (Heterocapsa triquetra). Chlorophyll a concentration played a key role in reflectance spectra, demonstrating high variability in the green-red (? 500–750 nm) bands at low concentrations (< 2 µg L?1), and even greater variability in the blue bands (? 400–490 nm) under higher concentrations (> 4 µg L?1). Although the present study represents a positive step forward in the use of new tools and offers a novel monitoring methodology with regards to phytoplankton found in complex coastal systems, including the detection of a new identification route, increasingly high-quality imaging and data from a broader range of ecosystems and environments remains a necessity. © Author(s) 2025.