[GRASS-dev] [GRASS GIS] #1480: v.outlier - distinguish positive and negative outlier filtering from lidar point clouds

[GRASS GIS]

#1480: v.outlier - distinguish positive and negative outlier filtering from lidar
point clouds
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 Reporter:  sbl          |       Owner:  grass-dev@…              
     Type:  enhancement  |      Status:  new                      
 Priority:  normal       |   Milestone:                           
Component:  Vector       |     Version:  svn-trunk                
 Keywords:  review       |    Platform:  Unspecified              
      Cpu:  Unspecified  |  
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 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).[[BR]]

 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]).[[BR]]

 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).

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