Point Cloud density to raster format
Hello, I’m working with Computree for my graduation thesis on ecological research.
I want to analyse the the structural heterogenity of forest-stand through lidar scans.
I used different methods to show the vertical heterogenity in the forest (voxelisation, QSM-Modelling etc..) what worked pretty well, but i cant find a good method to show the horizontal heterogenity of the Vegetation-Pointcloud.
First I thought about using the DSM (zmax) function but this doesn’t show me the point density in one raster zell but the hight of the points, right? (See the picture)
Does Computree offer a function which generates a 2D Raster of the Vegetation-Points where the z-Value of one raster zell shows me the number of scanpoints that fall into that zell?
thank you and best wishes
RE: Point Cloud density to raster format - Added by Hackenberg Jan about 1 year ago
Alexandres plugin (ONF) has at least a step which comes close to it. I do not have a precompiled version of CT atm, so I am not 100 % sure if I give you the correct Names inside the user Interface. Look for menu “Voxels”. Inside “Voxels” you should find a step which is named in C++ ONF_StepComputeHitGrid. In general the c++ name has a similar name to the User Interface name, so that might be enough to find. If you dont find, here is another hint, but you need to translate the description ( return tr(“Créer grille 3D de densité de points”);) which is something like “Creates a 3d density grid”.
This step - I looked into the code again to be sure - will give you exactly what you want. It does not use a x,y Raster, but uses a x,y,z Raster. That means to get what you asked for, you still need to loop the result and sum up all 3d raster cells values with same x,y coordinate. It should be only 5-10 lines of R code to do so.
Two other ideas. You extract from the result each z- step one horizontal slize. That means you split up the x,y,z grid by same z coordinate. You can analyse each slice indepentently. I think its cool, as you dont mix stem distribution and crown distribution.
Or you can use the steps result to analyse in the same procedure horizontal and vertical at once.
Ignore this answer if you got other reply from Alexandre. He knows a lot better his plugin than i do.