Widespread phytoplankton monitoring in small lakes: a case study comparing satellite imagery from planet SuperDoves and ESA sentinel-2

Abstract

Satellite imagery has enabled widespread monitoring of algae in larger water bodies, however until recently, the spatial resolution of available sensors has not been sufficient to apply this to smaller lakes. Therefore, this study investigated a new dataset of high-resolution metre-scale imagery for monitoring phytoplankton at spatial and temporal scales previously impossible with satellite data. Specifically, the Planet SuperDoves constellation was used to monitor a small (0.069 km2), eutrophic lake from 2021 to 2024. Several chlorophyll-a (Chl-a) algorithms were tested on both SuperDoves and Sentinel-2 data against in situ measurements. Additionally, the suitability of citizen science data as a validation tool for widespread algal bloom monitoring was investigated by comparing reports of algal blooms in five small water bodies in central Scotland with corresponding SuperDoves Chl-a images. Chl-a was successfully retrieved using the Ocean Colour 3 algorithm (R2 = 0.64, root mean squared error (RMSE) = 0.93 g L−1), which outperformed the best performing Sentinel-2 Chl-a algorithm (R2 = 0.61, RMSE = 1.01 g L−1). Furthermore, both Sentinel-2 and SuperDoves data were equally effective for algal bloom detection, each having F1-scores of 0.89 at a Chl-a bloom threshold of 40 g L−1. This demonstrates that metre-scale satellite monitoring of algae is possible even in challenging and optically complex environments such as small, shallow water bodies. This leads towards a potential step-change in the number of remotely monitorable inland water bodies, which would be a significant advancement for global lake science, environmental management and public health protection efforts.