Satellite image-based AI system for monitoring coral bleaching in Hawaii

Coral reefs play a critical role in sustaining marine biodiversity, supporting fisheries, and protecting coastlines. However, climate change and anthropogenic pressures have led to widespread coral bleaching, threatening ecological and economic stability—especially in tourism-dependent regions like Hawaii. Despite the urgency, current monitoring methods often lack real-time responsiveness and scalability. This study proposes an AI-based monitoring system that leverages satellite imagery to detect and track coral bleaching in Hawaii. The system integrates deep learning techniques for semantic segmentation of coral regions, temporal change detection to identify bleaching progress, and spectral analysis to estimate reef health. By visualizing high-risk areas through heatmaps, the framework enables early intervention and data-driven conservation planning. While the current focus is on the core detection and analysis functionalities, the system is designed with extensibility in mind—allowing future integration of automated reporting tools and real-time alert mechanisms. Our approach aims to provide an efficient and scalable solution for reef monitoring that bridges the gap between environmental science and AI technology. It offers both ecological insight and practical utility, contributing to the sustainable management of Hawaii’s vital coral reef ecosystems.