Coastal water quality monitoring is essential for tracking and mitigating sewage plumes, oil spills, rising sea surface temperatures, and harmful algal blooms. One way to measure water quality parameters is through direct water sampling in the field. However, water sampling is often time consuming, cost and labour intensive, and leaves lower- and middle-income countries with limited data.

Remote sensing with multi- and hyperspectral satellites serve to augment field datasets by providing data with finer temporal and spatial resolution. Satellite missions typically orbit the Earth, some passing over a certain area daily, and use sensors to collect electromagnetic radiation reflected from land and oceans. Visible and near-infrared radiation are the most relevant for coastal water quality monitoring. Images are processed to mask out clouds and sun glint, minimizing or removing atmospheric effects on the water reflectance. Computer algorithms are then applied to estimate water quality parameters from the corrected reflectance data. These algorithms can be simple to implement empirical or semi-empirical formulas calibrated to be region-specific, which is often preferred for specific coastal features or complex turbid waters. Machine and deep learning approaches are advantageous as they can quantitatively combine the satellite data, model outputs, and meteorological variables into the output data.

Credit: Ileana Callejas

Remote sensing with satellites is quickly becoming a powerful tool to monitor parameters such as sea surface temperature, turbidity, and levels of chlorophyll-a, enabling ocean warming and harmful algal blooms to be tracked over large regions. For resource scarce countries like those in Latin America, this remotely sensed data could be the only substantial dataset. Since 2020, satellite datasets have been successfully used to capture improvements in water quality in coastal regions during the COVID-19 lockdowns, including around Belize in Central America. Current findings using remote sensing data are being used to plan for future satellite missions such as the PACE (Plankton, Aerosol, Cloud, ocean Ecosystem) mission set to launch in early 2024, which will be able to distinguish between various types of algae with high accuracy.

Spanish Translation: This article was edited in English, with a Spanish translation provided by the author (Box 1). The translation was not checked for correctness by Springer Nature.