FURI | Spring 2026

Testing Efficacy of Hyperspectral Imaging to Understand Change in Water Quality

This study evaluates the effectiveness of hyperspectral imaging (HSI) for monitoring water quality changes. By relating hyperspectral reflectance to indicators like chlorophyll-a, dissolved oxygen, and nutrient concentrations, predictive models can be designed to improve the detection of environmental change. These methods provide faster and more scalable monitoring compared to traditional sampling where it will support earlier identification of pollution and improved ecosystem management. Future work will focus on integrating deep learning with HSI to scale these methods to aerial and satellite Earth observation systems.