Advanced ai strategies for coastal analysis: a case study at las canteras beach in Gran Canaria

Abstract

We propose a semantic segmentation model to analyze coast- al dynamics. Using advanced AI techniques, precise segmenta- tion masks are generated, overcoming challenges like changing weather conditions, glare, or shadows. A diverse dataset ensures adaptability, classifying features such as waves, sand, foam, and static infrastructures at the pixel level. This enables detailed anal- ysis of interactions between marine elements and coastal struc- tures, and can lead to measurements such as wave period, crucial for predicting overtopping events and identifying abnormal sea behavior. Experiments at Las Canteras Beach in Gran Canaria, a location where our model was not trained, yet it still performed well, demonstrate its effectiveness. This research illustrates AI's potential in advancing coastal management and environmental monitoring.