I'm currently doing a masters thesis on using drone photogrammetry to create a canopy height model of a grassland. This involves manually creating a DTM using an RTK GPS and using that data to normalise the DSM with lastools.
Unfortunately I'm getting stuck on converting my manually staked out points into a LAS file. I've tried both shp2las and txt2las with no luck. I'm very new to using lastools so I'm sure I'm doing something wrong.
My text file looks like this currently:
144.979281 -37.7011934 87.77934091
144.9792865 -37.70124286 87.15098529
144.979286 -37.70128589 86.92052778
144.9792809 -37.70132609 86.8250625
When I try to load this up into txt2las I get a "cannot parse" error.
Any ideas?
https://www.dropbox.com/s/m7y6du5csy2143v/Bababi%20DTM-Shapefile.zip?dl=0
– Chris Nov 07 '21 at 10:42txt2lassince that's the format you show) and provide the exact command usage and exact output. – Vince Nov 07 '21 at 12:07https://rapidlasso.com/2017/06/13/integrating-external-ground-points-in-forests-to-improve-dtm-from-dense-matching-photogrammetry/#comments
I need to height normalize my DSM so that I can generate a canopy height model. There is too much vegetation to automatically extract a DTM, hence why I have to manually create one using an RTK GPS.
The good news is that I managed to get txt2las to parse my file and generate a point cloud.
Unfortunately now, I'm stuck on the next step, densifying the dtm using the las2dem tool.
– Chris Nov 08 '21 at 03:01https://www.dropbox.com/s/c0l0wnj9cyd6np3/Screenshot%20%2816%29.png?dl=0
https://www.dropbox.com/s/8l9twmavx4o82zp/attempt4.laz?dl=0
– Chris Nov 08 '21 at 03:07