Our software takes daily, high resolution PlanetScope images and combines them into cloud-free images for each season in a year.
Improves the accuracy of our mapping algorithm.
Each training/validation site is mapped by several trained labellers, who trace field boundaries visible in the imagery
We assess labeller accuracy using a multi-dimensional scoring algorithm, allowing us to select the best label for each site, or to combine several individuals’ labels into a single “consensus” label
With every iteration, the uncertain sites are identified and labelled, improving model performance
With every iteration, the uncertain sites are identified and labelled, improving model performance
With every iteration, the uncertain sites are identified and labelled, improving model performance
With every iteration, the uncertain sites are identified and labelled, improving model performance
