A singular value decomposition approach for detecting and delineating harmful algal blooms in the Red Sea

Harmful algal blooms (HABs) have adverse effects on marine ecosystems. An effective approach for detecting, monitoring, and eventually predicting the occurrences of such events is required. By combining a singular value decomposition (SVD) satellite remote sensing observations, we propose algorithm to detect delineate species-specific HABs. We implemented tested proposed SVD HABs associated with mixed assemblages different phytoplankton functional type (PFT) groupings in Red Sea. The results were validated concurrent in-situ data from surface samples, demonstrating that SVD-model performs remarkably well at detecting distinguishing HAB species Sea basin. offers cost-effective tool implementing an automated remote-sensing monitoring system Such could be used outbreaks based near real-time measurements, essential support aquaculture industries, desalination plants, tourism, public health.