Inconsistent Automatic Point Cloud Analysis

TerraUnda

I don't feel like I should be struggling with this as much as I am but things seem really inconsistent. I have tried probably hundreds of combinations of settings with LiDAR data I collected with a DJI L3 and cannot come up with settings that work, even after combing through as much documentation and watching as many Blue Marble YouTube videos I can. When I do find something that works (temporarily) I take a screenshot of the settings. Then I go back and try it with the same exact settings on a different day and get completely different results, none of which will classify buildings. I haven't even gotten to the vegetation yet because the ground and buildings settings adjustments are so inconsistent. I've tried running various settings on a full resolution point cloud of over 2,000 points per square meter and also on thinned pointclouds of around 100 points per square meter. Is GM just not able to handle dense point clouds? It seems like, from what I'm reading, the automatic calculations are more tuned for low density LiDAR data from fixed wing aircraft, like 10 points per square meter or something like that. What if I want to find very small or obscured objects, like cultural stone monument artifacts in a dense jungle with thick canopy cover? I need denser data to do this. GM also hangs a lot when running classifications on the denser point clouds. I have tried with both .laz and .copz.laz files. Anyone else out there trying to process pointcloud data collected with a DJI L3? Any help would be much appreciated.

BMG_Amanda

Hello TerraUnda,

Global Mapper is able to handle dense point clouds. The technical support team can help you troubleshoot these types of issues. Please send your data (or a sample of your data) to geohelp@bluemarblegeo.com.