Marigold uses built-in capabilities for complex masking.
K-means clustering is an unsupervised classification algorithm that segments the input dataset into a "k" number of different clusters. From these clusters, areas that require masking can be identified, and then turned into mask layers to apply to datasets.
**Tip: Check out our instructional video on Vegetation Masking to learn how to effectively create and apply masks in Marigold for vegetated areas.
Now that you have mastered the use of unsupervised classification techniques to mask shadows and various surface cover types, you can utilize Marigold's processing tools to pinpoint lithologies, alterations, and mineralization with enhanced precision.
Questions? Contact support@descarteslabs.com