Automatic Detection of Coral Reef Induced Turbulent Boundary Flow in the Red Sea from Flock-1 Satellite Data

Abstract

The novelty of this study is the use of a multi-objective evolutionary algorithm for the automatic detection of hydrodynamic turbulent boundaries overlying coral reefs. The procedure is implemented using sequences of Flock-1 satellite data acquired in the Red Sea. The study demonstrates that implementing Pareto-optimal solutions allows for the generation of accurate coral reef-water interface patterns. This is validated by a Pareto-optimal front and the receiver-operating characteristic (ROC) curve. The Pareto-optimal front indicates a significant relationship between hydrodynamic turbulent boundaries, macroalgae, and coral reefs. The ROC curves confirm the finding of the Pareto-optimal front that hydrodynamic turbulent boundary layers and macroalgae are caused by coral reefs. The performance accuracy is identified with an under-curve area of 90%. In conclusion, the multi-objective evolutionary algorithm has the applicability for the automatic detection of hydrodynamic turbulent boundary layers to coral reef studies.