Hello All – We are back at it again with a different group of undergraduate students. This time the goal is to develop a machine learning model that can look at a patch of lunar terrain and decide whether it contains a crater. For this we need to accumulate lots of terrain patches that do, and that don’t, contain craters. Our issue is that we would like to be able to see small craters, whereas the pictures we have drawn so far have very poor resolution when the size goes below, say, one degree by one degree on the Moon. Our question is, how can we optimize our use of PyGMT to get the best closeups possible of lunar terrain? We are using the Ohio Supercomputer, so computing resources are not an issue. Do we need to load in a different DEM? Are there sample available of how this can be done? Many thanks,
David Calvis