Title:
AI-Driven, adjacency-effect corrections for improved remote sensing of Inland Lakes
Agreement Number:
24AO3SHE17
Agreement Value:
$309,623.00
Agreement Date:
Mar 15, 2024 - Mar 31, 2027
Description:
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.
Organization:
Canadian Space Agency
Expected Results:
The Research component of the program provides financial support to organizations to conduct space related research and development in priority areas. It will support targeted knowledge development and innovation to sustain and enhance the Canadian capacity to use space to address national needs and priorities in the future.
Location:
Sherbrooke, Quebec, CA J1K 2R1
Reference Number:
003-2023-2024-Q4-00110
Report Type:
Grants and Contributions
Recipient's Legal Name:
Université de Sherbrooke
Program:
Class Grant and Contribution Program to Support Research, Awareness and Learning in Space Science and Technology
Program Purpose:
This program supports knowledge development and innovation in the CSA's priority areas while increasing the awareness and participation of Canadians in space-related disciplines and activities.
The Research Component aims to support the development of science and technology; foster the continual development of a critical mass of researchers and highly qualified people in Canada; and support information gathering and space-related studies and research pertaining to Canadian Space Agency priorities.