Grants and Contributions:

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Title:

Deep Learning for Classification of SAR-Derived Forest Change

Agreement Number:

AO2020-MDAG

Agreement Value:

$157,924.00

Agreement Date:

Nov 9, 2020 - Jul 31, 2022

Description:

Title: Deep Learning for Classification of SAR-Derived Forest Change Use Canadian radar technology, combined with AI algorithms, to detect and map forest changes.

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:

Richmond, British Columbia, CA V6V 2J3

Reference Number:

003-2020-2021-Q3-04760

Agreement Type:

Contribution

Report Type:

Grants and Contributions

Recipient Type:

For-profit organization

Additional Information:

The amount allocated covers more than one fiscal year.

Recipient's Legal Name:

MDA Geospatial Services Inc.

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.