Remote Sensing of Harmful Algal Blooms in Coastal Ecosystems

Harmful algal blooms (HABs) have emerged as a critical threat to coastal ecosystems worldwide, affecting fisheries, water quality and public health. Remote sensing offers synoptic, high-frequency observations by measuring light reflected and emitted from the water surface, enabling detection, mapping and monitoring of HABs over spatial and temporal scales beyond the reach of traditional ship-based surveys. Advances in satellite sensors—ranging from multispectral to hyperspectral imagers—and refined atmospheric correction algorithms have improved discrimination of bloom constituents such as chlorophyll-a and accessory pigments. Coupling these remote observations with in situ measurements and machine learning techniques has further sharpened detection thresholds and forecasting accuracy. As a result, remote sensing has become indispensable for early warning systems, resource management and policy decisions, providing precise assessments of bloom extent, intensity and evolution across diverse coastal settings.

Research from Nature Portfolio

Global high-resolution mapping of coastal phytoplankton blooms from 2003 to 2020 revealed a significant rise in bloom frequency (+59.2%) and spatial extent (+13.2%) in 126 of 153 coastal nations. Analyses linked these trends to ocean circulation changes and rising sea surface temperatures, offering a foundational dataset for worldwide bloom-risk evaluation.

The twin Sentinel-2A/B satellites, combined with in situ sampling, have enabled enhanced detection of fine-scale HABs at 10 m resolution. Utilising the ACOLITE atmospheric correction tool together with the normalized difference chlorophyll index (NDCI) has delivered unprecedented detail on patchy dinoflagellate blooms, outperforming Landsat-8 and Sentinel-3 and providing critical spatiotemporal insights for regional water-quality management.

Remote Sensing of Harmful Algal Blooms in Coastal Ecosystems publication trend

The graph below shows the total number of articles in remote sensing of harmful algal blooms in coastal ecosystems across all publications each year (not limited to Nature Index journals).

Technical terms

Remote sensing reflectance (Rrs): Ratio of water-leaving radiance to incident solar irradiance, indicating water-column optical properties.

Normalized fluorescence line height (nFLH): Satellite-derived metric of chlorophyll fluorescence, used to detect phytoplankton blooms amid coloured dissolved organic matter.

Normalized difference chlorophyll index (NDCI): Spectral index leveraging red and red-edge bands to estimate chlorophyll-a concentration.

Harmful algal bloom index (ABI): Empirical adjustment of nFLH that minimises turbidity-induced false positives in bloom detection.

Euphotic depth: Depth at which available light falls to 1% of surface irradiance, influencing phytoplankton growth and bloom dynamics.

References

1. Coastal phytoplankton blooms expand and intensify in the 21st century. Nature (2023).
2. New capabilities of Sentinel-2A/B satellites combined with in situ data for monitoring small harmful algal blooms in complex coastal waters. Scientific Reports (2020).
3. Modified MODIS fluorescence line height data product to improve image interpretation for red tide monitoring in the eastern Gulf of Mexico. Journal of Applied Remote Sensing (2016).
4. A Remote Sensing and Machine Learning-Based Approach to Forecast the Onset of Harmful Algal Bloom. Remote Sensing (2021).
5. Improved MODIS-Aqua Chlorophyll-a Retrievals in the Turbid Semi-Enclosed Ariake Bay, Japan. Remote Sensing (2018).