filter_StemReturns: Remove low outlier returns, which originate most probably...
In niknap/MeanShiftR: Tree delineation from lidar using mean shift clustering

Description Usage Arguments Value Author(s)

The AMS3D algorithm can lead to clustering artefacts such that a single tree crown may be assigned to more than one cluster ID and the derived enclosing crown polygons may show very high spatial overlap. This function enables cleaning of the crown polygon dataset by removing redundant polygons which most likely represent just one single tree. Of several overlapping polygons, the polygon with the largest tree height value is kept, while the other polygons are removed. The algorithm involves pairwise comparisons of all polygons which are handed over to the function. Hence, it is recommended to apply it on small tiles (e.g., 1 ha), as processing time may become very slow for large areas.

1	filter_StemReturns(pc.dt, H.quantile = 0.1, filter.factor = 0.9, rm.class = NA)

`pc.dt`	Point cloud in data.table format containing columns X, Y, Z and ID
`H.quantile`	Lower end height quantile on which filter factor is applied
`filter.factor`	which multiplied with the H.quantile height defines the threshold below which a return will be classified as stem.
`rm.class`	Switch for automatically removing returns belonging to classes. Should be set to "Stem" to remove stem returns, "Crown" to remove crown returns or NA to keep all returns.