This script is fairly straightforward. We loop through the (x,y) point locations in the LIDAR data and project them to our grid with a cell size of one meter. Due to the precision of the LIDAR data, we'll end up with multiple points in a single cell. We average these points to create a common elevation value. Another issue that we have to deal with is data loss. Whenever you resample the data, you lose information.
In this case, we'll end up with NODATA holes in the middle of the raster. To deal with this issue, we fill these holes with average values from the surrounding cells, which is a form of interpolation. We only need two modules, both available on PyPI, as shown in the following code:
from laspy.file ...
