v.lidar.growing(1grass) GRASS GIS User's Manual v.lidar.growing(1grass)
NAME
v.lidar.growing - Building contour determination and Region Growing
algorithm for determining the building inside
KEYWORDS
vector, LIDAR
SYNOPSIS
v.lidar.growing
v.lidar.growing --help
v.lidar.growing input=name output=name first=name [tj=float]
[td=float] [--overwrite] [--help] [--verbose] [--quiet] [--ui]
Flags:
--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
Input vector (v.lidar.edgedetection output)
output=name [required]
Name for output vector map
first=name [required]
Name of the first pulse vector map
tj=float
Threshold for cell object frequency in region growing
Default: 0.2
td=float
Threshold for double pulse in region growing
Default: 0.6
DESCRIPTION
v.lidar.growing is the second of three steps to filter LiDAR data. The
filter aims to recognize and extract attached and detached object (such
as buildings, bridges, power lines, trees, etc.) in order to create a
Digital Terrain Model.
The modules identifies which is the internal area of every object on a
LiDAR point surface. The classification categories from v.lidar.edgede-
tection are now rasterized. For each cell, it is evaluated if it (the
cell) contains a point with double impulse (difference between the
first and last pulse greater than a given threshold). Starting from
cells classified as OBJECT and with only one pulse all linked cells are
selected and a convex hull algorithm is applied to them. Simultane-
ously, the mean of the corresponding heights (mean edge height) are
computed. Points inside the convex hull are classified as OBJECT if
their height is greater than or equal to the previously mean computed
edge height. This last step is done only in case of high planimetric
resolution.
NOTES
The input data should be the output result of the v.lidar.edgedetec-
tion, module. Otherwise, it goes to error! The output of this module
will be the input of v.lidar.correction module. The output will be a
vector map which points are pre-classified as:
TERRAIN SINGLE PULSE (cat = 1, layer = 2)
TERRAIN DOUBLE PULSE (cat = 2, layer = 2)
OBJECT SINGLE PULSE (cat = 3, layer = 2)
OBJECT DOUBLE PULSE (cat = 4, layer = 2)
The final result of the whole procedure (v.lidar.edgedetection, v.li-
dar.growing, v.lidar.correction) will be a point classification in the
same categories as above.
EXAMPLES
Basic region growing procedure
v.lidar.growing input=edge output=growing first=firstpulse
SEE ALSO
v.lidar.edgedetection, v.lidar.correction, v.surf.bspline, v.surf.rst,
v.in.lidar, v.in.ascii
AUTHOR
Original version of program in GRASS 5.4:
Maria Antonia Brovelli, Massimiliano Cannata, Ulisse Longoni and Mirko
Reguzzoni
Update for GRASS 6.X:
Roberto Antolin and Gonzalo Moreno
REFERENCES
Antolin, R. et al., 2006. Digital terrain models determination by LiDAR
technology: Po basin experimentation. Bolletino di Geodesia e Scienze
Affini, anno LXV, n. 2, pp. 69-89.
Brovelli M. A., Cannata M., Longoni U.M., 2004. LIDAR Data Filtering
and DTM Interpolation Within GRASS, Transactions in GIS, April 2004,
vol. 8, iss. 2, pp. 155-174(20), Blackwell Publishing Ltd.
Brovelli M. A., Cannata M., 2004. Digital Terrain model reconstruction
in urban areas from airborne laser scanning data: the method and an
example for Pavia (Northern Italy). Computers and Geosciences 30 (2004)
pp.325-331
Brovelli M. A. and Longoni U.M., 2003. Software per il filtraggio di
dati LIDAR, Rivista dell?Agenzia del Territorio, n. 3-2003, pp. 11-22
(ISSN 1593-2192).
Brovelli M. A., Cannata M. and Longoni U.M., 2002. DTM LIDAR in area
urbana, Bollettino SIFET N.2, pp. 7-26.
Performances of the filter can be seen in the ISPRS WG III/3 Comparison
of Filters report by Sithole, G. and Vosselman, G., 2003.
SOURCE CODE
Available at: v.lidar.growing source code (history)
Accessed: unknown
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