1. Collected data by flying aircraft over the area. Used a land classification mask to restrict the are to ~ 600 sq km

2. Make image patches of 11m by 11m. I believe there is some overlap in the patches. Sharpen the images for contrast.

3. The training data comes from previously known glyphs. Positive label patches are ones with a glyph. Negative label patches are randomly sampled from the vicinity of the glyph.

4. It looks like they fine tuned resnet 50 with these labels

5. Ran inference on other patches. They had false positives

6. Manually verified these AI predicted glyphs by ground surveys

I couldn't figure out how they drew the outlines in the pictures. I guess it was manually done