Synergistic Effect of Multi-Sensor Data on the Detection of Margalefidinium polykrikoides in the South Sea of Korea

High Spatial-Resolution Red Tide Detection in the Southern Coast of Korea Using U-Net from PlanetScope Imagery

Red tides caused by Margalefidinium polykrikoides occur continuously along the southern coast of Korea, where there are many aquaculture cages, and therefore, prompt monitoring of bloom water is required to prevent considerable damage. Satellite-based ocean-color sensors are widely used for detecting red tide blooms, but their low spatial resolution restricts coastal observations. Contrarily, terrestrial sensors with a high spatial resolution are good candidate sensors, despite the lack of spectral resolution and bands for red tide detection. In this study, we developed a U-Net deep learning model for detecting M. polykrikoides blooms along the southern coast of Korea from PlanetScope imagery with a high spatial resolution of 3 m. The U-Net model was trained with four different datasets that were constructed with randomly or non-randomly chosen patches consisting of different ratios of red tide and non-red tide pixels. The qualitative and quantitative assessments of the conventional red tide index (RTI) and four U-Net models suggest that the U-Net model, which was trained with a dataset of non-randomly chosen patches including non-red tide patches, outperformed RTI in terms of sensitivity, precision, and F-measure level, accounting for an increase of 19.84%, 44.84%, and 28.52%, respectively. The M. polykrikoides map derived from U-Net provides the most reasonable red tide patterns in all water areas. Combining high spatial resolution images and deep learning approaches represents a good solution for the monitoring of red tides over coastal regions.

New capabilities of Sentinel-2A/B satellites combined with in situ data for monitoring small harmful algal blooms in complex coastal waters

The increased frequency of harmful algal blooms (HABs) is a major environmental concern worldwide, resulting not only in increased treatment costs for drinking water but also in impacts on tourism, commercial fishing and aquaculture and risks to human and animal health. Traditional strategies with ship-based approaches based on field sampling and laboratory analysis have been adopted to assess HABs. However, these methods are labour intensive and costly and do not provide synoptic views of the bloom conditions. Here, we show that the Sentinel-2 twin satellite mission of the Copernicus programme, in combination with in situ data, is a powerful tool that can offer valuable spatiotemporal information about a bloom of the dinoflagellate Lingulodinium polyedra that occurred on the SW Iberian Peninsula. Using the robust ACOLITE atmospheric correction processor combined with the normalized difference chlorophyll index (NDCI), the enhanced mapping of small blooms can be performed at a 10 m spatial resolution, revealing surface patches and a heterogeneous distribution. This research also demonstrates the improved capabilities of Sentinel-2 compared to those of Landsat-8 and Sentinel-3 for continuous monitoring. The Sentinel-3 and Sentinel-2 missions provide ecosystem observations that allow the environmental community and water managers to evaluate changes in water quality and bloom distribution and that facilitate field-based measurements. Therefore, the value added by the Copernicus products in terms of frequency and synoptic observations is of paramount importance for ecological and management purposes at regional and national scales.