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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
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.edgedetection 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. Simultaneously,
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.
The input data should be the output result of the
v.lidar.edgedetection,
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.lidar.growing,
v.lidar.correction) will be a point
classification in the same categories as above.
v.lidar.growing input=edge output=growing first=firstpulse
v.lidar.edgedetection,
v.lidar.correction,
v.surf.bspline,
v.surf.rst,
v.in.lidar,
v.in.ascii
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
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)
Latest change: Monday Nov 18 20:15:32 2019 in commit: 1a1d107e4f6e1b846f9841c2c6fabf015c5f720d
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GRASS Development Team,
GRASS GIS 7.8.9dev Reference Manual