Hi all,
I'm working on classifying the dense cloud to create a DSM/DTM in hopes of getting a canopy height model of tundra plants in Northern Alaska. The vegetation is between 5-50cm and the area is quite flat, so my needs are very fine scale. I have traditional air photos (stereotriplets) that were taken at 1:3000 and am using those to generate the dense cloud. I have been using the following parameters when classifying ground points:
max angle: 15 degrees
max distance: .05 m
cell size: .1 m
I then create a DTM from the classified ground points. Then I make a copy of the chunk and create a DSM from the UNCLASSIFIED points (excluding noise). Then I take it into arc and subtract the DTM from the DSM to get my CHM. The results seem totally reasonable minus a couple of negative values which I'm not sure why those are occurring. Some noise error I think?
I have another site where the vegetation is slightly taller, up to 90 cm. I am wondering if I should change the aforementioned parameters to something different when classifying the ground points. This site tends to have more shrubs (willows and dwarf birch) and less tussocks/graminoids.
So I am wondering:
1) does this general workflow seem appropriate for generating canopy height estimates in a tundra environment?
2) should I change the classify ground point settings for the site that has slightly taller vegetation or is this already pretty fine-scale?
Thanks for the input!!