Colour-informed ecoregion analysis highlights a satellite capability gap for spatially and temporally consistent freshwater cyanobacteria monitoring

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Cyanobacteria blooms pose significant risks to water quality in freshwater ecosystems worldwide, with implications for human and animal health. Constructing consistent records of cyanobacteria dynamics in complex inland waters from satellite imagery remains challenged by discontinuous sensor capabilities, particularly with regard to spectral coverage. Comparing 11 satellite sensors, we show that the number and positioning of wavebands fundamentally alter bloom detection capability, with wavebands centred at 412, 620, 709, 754 and 779 nm proving most critical for capturing cyanobacteria dynamics. Specifically, analysis of observations from the Medium Resolution Imaging Spectrometer (MERIS) and Ocean and Land Colour Instrument (OLCI), coincident with the Moderate Resolution Imaging Spectroradiometer (MODIS) demonstrates how the spectral band configuration of the latter affects bloom detection. Using an Optical Water Types (OWT) library understood to capture cyanobacterial biomass through varying vertical mixing states, this analysis shows that MODIS can identify optically distinct conditions like surface accumulations but fails to resolve initial bloom evolution in well-mixed conditions, particularly in optically complex regions. Investigation of coherent ecoregions formed using Self-organising Maps trained on OWT membership scores confirm that MODIS captures broad spatial patterns seen with more capable sensors but compresses optical gradients into fewer optical types. These constraints have significant implications for interpreting spatial–temporal dynamics of cyanobacteria in large waterbodies, particularly during 2012–2016 when MERIS and OLCI sensors were absent, and small waterbodies, where high spatial resolution sensors not originally design to study water are used. In addition, these findings underscore the importance of key wavebands in future sensor design and the development of approaches to maintain consistent long-term records across evolving satellite capabilities. Our findings suggest that attempts at quantitatively harmonising cyanobacteria bloom detection across sensors may not be ecologically appropriate unless these observation biases are addressed. For example, analysing the frequency and intensity of surfacing blooms, while considering the meteorological factors that may drive these phenomena, could be considered over decadal timescales, whereas trend analysis of mixed-column biomass should only concern appropriate sensor observation periods.

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