Université de Sherbrooke
AI-Driven, adjacency-effect corrections for improved remote sensing of Inland Lakes — The objective of this project is to develop an AI-based algorithm that can improve atmospheric correction of satellite images over Canadian lakes. This will address current inaccuracies that hinder monitoring efforts, which are crucial for various aspects of Canadian life. The project aims to create a hyperspectral algorithm for accurate atmospheric correction by collecting in situ data and using advanced modeling techniques. AI will be leveraged to improve computational efficiency and enable more precise utilization of remote sensing data. This will ultimately advance the field of lake monitoring and benefit multiple stakeholders.