v.outlier - Removes outliers from vector point data.
vector, statistics, extract, select, filter, LIDAR
v.outlier
v.outlier --help
v.outlier [-
e]
input=
name output=
name
outlier=
name [
qgis=
name]
[
ew_step=
float] [
ns_step=
float]
[
lambda=
float] [
threshold=
float]
[
filter=
string] [--
overwrite] [--
help]
[--
verbose] [--
quiet] [--
ui]
- -e
-
Estimate point density and distance
Estimate point density and distance for the input vector points within the
current region extends and quit
- --overwrite
-
Allow output files to overwrite existing files
- --help
-
Print usage summary
- --verbose
-
Verbose module output
- --quiet
-
Quiet module output
- --ui
-
Force launching GUI dialog
- input=name [required]
-
Name of input vector map
Or data source for direct OGR access
- output=name [required]
-
Name for output vector map
- outlier=name [required]
-
Name for output outlier vector map
- qgis=name
-
Name for vector map for visualization in QGIS
- ew_step=float
-
Length of each spline step in the east-west direction
Default: 10 * east-west resolution
- ns_step=float
-
Length of each spline step in the north-south direction
Default: 10 * north-south resolution
- lambda=float
-
Tykhonov regularization weight
Default: 0.1
- threshold=float
-
Threshold for the outliers
Default: 50
- filter=string
-
Filtering option
Options: both, positive, negative
Default: both
v.outlier removes outliers in a 3D point cloud. By default, the outlier
identification is done by a bicubic spline interpolation of the observation
with a high regularization parameter and a low resolution in south-north and
east-west directions. Those points that differ in an absolute value more than
the given threshold from a fixed value, reckoned from its surroundings by the
interpolation, are considered as an outlier, and hence are removed.
The
filter option specifies if all outliers will be removed (default), or
only positive or only negative outliers. Filtering out only positive outliers
can be useful to filter out vegetation returns (e.g. from forest canopies)
from LIDAR point clouds, in order to extract Digital Terrain Models. Filtering
out only negative outliers can be useful to estimate vegetation height.
There is a flag to create a vector that can be visualizated by qgis. That means
that topology is build and the z coordinate is considered as a category.
v.outlier input=vector_map output=vector_output outlier=vector_outlier thres_O=25
In this case, a basic outlier removal is done with a threshold of 25 m.
v.outlier input=vector_map output=vector_output outlier=vector_outlier qgis=vector_qgis
Now, the outlier removal uses the default threshold and there is also an output
vector available for visualizaton in QGIS (http://www.qgis.org).
v.outlier input=elev_lid792_bepts output=elev_lid792_bepts_nooutliers \
outlier=elev_lid792_bepts_outliers ew_step=5 ns_step=5 thres_o=0.1
This module is designed to work with LIDAR data, so not topology is built but in
the QGIS output.
v.surf.bspline
Original version of the program in GRASS 5.4:
Maria Antonia Brovelli, Massimiliano Cannata, Ulisse Longoni and Mirko Reguzzoni
Updates for GRASS 6:
Roberto Antolin
Last changed: $Date: 2014-08-05 08:59:29 +0200 (Tue, 05 Aug 2014) $
Available at: v.outlier source code (history)
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