Grants and Contributions

Sedimentary rocks exposed at the Martian surface offer an information-rich record of the planet's past environmental conditions and biological habitability. Curiosity's expected exploration of unique sedimentological units in Mount Sharp offer exciting opportunities for exploring the interplay between climate, water, and biological habitability at the critical time in Mars' past when water-rich conditions existed and hence could have originated life. This proposal seeks to leverage our team's expertise in quantifying and modeling these geochemical and hydrological processes and Curiosity's prowess as a roving field geologist and mobile laboratory to develop a framework for interpreting past Martian climate and habitability.

This project aims to develop a web-based GIS software prototype that will provide remote sensing based algal bloom detection, algae concentration, and water quality assessments and monitoring. This technology will benefit Canadians by enabling healthier ecosystems that provide clean air, water, and local climate regulation.

This project aims to develop a hyperspectral-based capability to map plant species from space, focusing on enhancing spatial resolution of hyperspectral data and assessing its effectiveness for plant species mapping.

This project aims to develop an AI and satellite-based tool to enhance boreal caribou habitat mapping in the Uashat Mak Mani-Utenam community, adding a spatio-temporal dimension and supporting research.

This project aims to integrate SEO data with AI into a novel dashboard to track biodiversity and climate variables (EBVs and ECVs) to make climate and biodiversity monitoring more scalable and automated.

This project aims to develop the DeCAF-RRT, a wide-area monitoring tool using satellite Earth observation (SEO), to support salmon habitat monitoring. Effective monitoring promotes healthy ecosystems, sustainable biodiversity, and stable salmon populations for food and economic security.

This project aims to develop a trustworthy AI software based on a data-driven predictive-3D technology from a single 2D satellite image. It will provide new high-resolution 3D maps and change-detection to aid in assessing land, agriculture, and provide resilience to topography changes.

This project aims to develop an AI-powered system using satellite imagery and remote sensing technology to monitor biodiversity and track ecosystem changes in New Brunswick, including habitat features, forest regrowth, and the impacts of ecosystem management and climate change.

This initiative aims to develop cost-effective monitoring tools for Northern Canada’s ecosystems, collaborating with government and Indigenous partners to track climate and biodiversity impacts and guide future SAR land monitoring strategies.

This project will contribute to the Arctic POlar Night EXperiment (PONEX) campaign, which is a sub-orbital component of the Canadian Space Agency’s High-altitude Aerosols, Water vapour and Clouds (HAWC) mission. PONEX will involve a coordinated ground-based and aircraft field campaign in Inuvik, Northwest Territories, in January 2026 and will be the first such campaign to employ aircraft during polar night. This project will support two trainees, who will participate in the deployment, operation, and data analysis of two of the ground-based instruments: a scanning Doppler Lidar and a Water Vapour Lidar, both provided by Environment and Climate Change Canada. These instruments will measure vertical wind profiles, cloud base heights, planetary boundary layer heights, aerosol backscatter profiles, and water Docusign Envelope ID: F463D985-E1B1-4924-AD6E-88066E1BE7B5 vapour profiles. These measurements, in combination with other PONEX ground-based and aircraft datasets, will be used to undertake science investigations in support of the HAWC scientific objectives.