This is the command v.outliergrass that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator
PROGRAM:
NAME
v.outlier - Removes outliers from vector point data.
KEYWORDS
vector, statistics, extract, select, filter
SYNOPSIS
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]
Flags:
-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
Parameters:
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 of output outlier vector map
qgis=name
Name of vector map for visualization in QGIS
ew_step=float
Length of each spline step in the east-west direction
Default: 10
ns_step=float
Length of each spline step in the north-south direction
Default: 10
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
DESCRIPTION
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.
EXAMPLES
Basic outlier removal
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.
Basic outlier removal
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).
North carolina location example
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
NOTES
This module is designed to work with LIDAR data, so not topology is built but in the QGIS
output.
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