MLVX Technologies Inc.
Quantification of carbon sequestration in Canadian agricultural lands using satellite hyperspectral imagery — The project aims to build a method to systemically and methodically quantify the Carbon dioxide (CO2) level present at ground-elevation using hyperspectral data. Hyperspectral data captures the entire spectrum per pixel, providing a vast amount of information. By combining CO2 data captured at ground-elevation as the ground-truth labels, a Machine Learning model will be developed that is able to take satellite hyperspectral data as its input, and predict its underlying CO2 level. This project aims to provide the information required for the governments and private entities such as farmers to track their carbon footprint, and capture the associated economic benefits.