v.outlier - distinguish positive and negative outlier filtering from lidar point clouds
|Reported by:||sbl||Owned by:|
In forest areas LIDAR returns usually both: signals from tree-tops (canopy) and from the ground as well. Unfortunately v.outlier (as it is today) filters positive and negative outliers at the same time, because it filters based on the absolute value of deviation from an interpolated surface. In forest areas, this appoarch affects both ground- and canopy-returns (meaning that very often both are being removed).
Usually a local minimum filtering is applied for removing vegetation returns from LIDAR point clouds (see: http://www2.geog.ucl.ac.uk/~plewis/lidarforvegetation/UCL-ALS-Lidar_for_Vegetation_Applications_2010.pdf or http://www.fs.fed.us/rm/pubs_other/rmrs_2007_evans_j001.pdf).
This is why I propose a p- and a n-flag for v.outlier, in order to be able to specify, that only positive or negative outliers are filtered. The attached code did the job for me. The attached two images illustrate my result when applying my modified version of v.outlier to my data rereatedly (similar to http://www.fs.fed.us/rm/pubs_other/rmrs_2007_evans_j001.pdf). On is a shaded relief of the DSM and the other a shaded relief of the DTM of the same region (after removing positive outliers).
Change History (10)
comment:1 by , 11 years ago
|CPU:||Unspecified → All|
|Platform:||Unspecified → All|
|Version:||svn-trunk → svn-develbranch6|
follow-up: 4 comment:3 by , 9 years ago
|Milestone:||6.4.2 → 7.0.0|
|Version:||svn-develbranch6 → unspecified|