Phytoplankton detection study through hyperspectral signals in Patagonian Fjords

Abstract. Over recent decades, monitoring coastal areas has becoming a priority due to human population pressure. These areas constitute biodiversity enclaves where the increment in phytoplankton blooms have become a socio-ecological problem with severe impacts at global and regional scales. An important area they affect is the Patagonia Fjords, a complex and intricate coastal system strongly exposed to climate forcings and anthropogenic impacts with the aquaculture industry (salmon and mussel farming) as the main source of income. Within this context, fast and accurate monitoring of phytoplankton in the area is crucial. In this study, we focus on using a new technology combining hyperspectral sensors and unmanned aerial vehicles (UAVs) to detect, identify, and differentiate phytoplankton species from optical data. Findings show 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 genera level (Rhizosolenia sp., Pseudo-nitzschia sp., Skeletonema sp., Chaetoceros sp., and Leptocylindrus sp.) and even species level like Heterocapsa triquetra. Chlorophyll-a concentration played a key role in reflectance spectra showing high variability in the green-red bands (~ 500–750 nm) at low concentrations (< 2 μg L^-1), and even greater at the blue bands (~ 400–490 nm) under higher concentrations (> 4 μg L^-1). Although this work presents a step forward in using new tools and monitoring methodology of phytoplankton in complex coastal systems with a new identification route, more high-quality data from a wide range of ecosystems and environments is still necessary.