I have multiple large LiDAR datasets (.laz) from different areas, where I need to extract buildings. I have prepared a shapefile containing a buffer around the buildings I care about, and are using the FUSION tool
PolyClipData to clip the point clouds.
I am relatively new to working with ALS data and have a couple of questions to hopefully save me some time as I start processing other datasets. My first data set (after having thinned it) is 780 million points, of which about 15 million points are within the buffer zones. It takes my computer more than five hours to use the
PolyClipData tool. Is that normal?
I afterwards will create DEM and DTMs using the clipped data set. In the end, all I care about is the height of the buildings and extracting roof shapes.
I have considered a couple of things that might make the tool faster, but unfortunately don't have the time to test them, and I am hoping to get help knowing if and why any of these (or further) solutions might be helpful.
a) Is it more efficient to have square polygons than rounded polygons to cut the point clouds with?
b) Is it better to dissolve the polygons into a multipolygon or is it better to have multiple polygons?
c) Is it faster to creta DEMs and DTM for the entire data set and then cut those using the polygons? I figure that the interpolation will take much longer with more points. But on the other hand, cutting the output raster from the DEM and the DTM should be fast.
d) I am using .laz files and using the laszip.dll tool to let FUSION work directly on those files. Would I in total save time if I thin my dataset (
ThinData) directly into .lda (FUSION native format) or .las?