v.lidar.growing(1grass)

1v.lidar.growing(1)            Grass User's Manual           v.lidar.growing(1)
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NAME

6       v.lidar.growing   -  Building  contour determination and Region Growing
7       algorithm for determining the building inside
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KEYWORDS

10       vector, LIDAR
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SYNOPSIS

13       v.lidar.growing
14       v.lidar.growing --help
15       v.lidar.growing   input=name   output=name    first=name     [tj=float]
16       [td=float]   [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]
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18   Flags:
19       --overwrite
20           Allow output files to overwrite existing files
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22       --help
23           Print usage summary
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25       --verbose
26           Verbose module output
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28       --quiet
29           Quiet module output
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31       --ui
32           Force launching GUI dialog
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34   Parameters:
35       input=name [required]
36           Name of input vector map
37           Input vector (v.lidar.edgedetection output)
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39       output=name [required]
40           Name for output vector map
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42       first=name [required]
43           Name of the first pulse vector map
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45       tj=float
46           Threshold for cell object frequency in region growing
47           Default: 0.2
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49       td=float
50           Threshold for double pulse in region growing
51           Default: 0.6
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DESCRIPTION

54       v.lidar.growing is the second of three steps to filter LiDAR data.  The
55       filter aims to recognize and extract attached and detached object (such
56       as  buildings, bridges, power lines,  trees, etc.) in order to create a
57       Digital Terrain Model.
58       The modules identifies which is the internal area of every object on  a
59       LiDAR point surface. The classification categories from v.lidar.edgede‐
60       tection are now rasterized. For each cell, it is evaluated if  it  (the
61       cell)  contains  a  point  with  double impulse (difference between the
62       first and last pulse greater than a  given  threshold).  Starting  from
63       cells classified as OBJECT and with only one pulse all linked cells are
64       selected and a convex hull algorithm is  applied  to  them.  Simultane‐
65       ously,  the  mean  of  the corresponding heights (mean edge height) are
66       computed.  Points inside the convex hull are classified  as  OBJECT  if
67       their  height  is greater than or equal to the previously mean computed
68       edge height. This last step is done only in case  of  high  planimetric
69       resolution.
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NOTES

72       The  input  data  should be the output result of the v.lidar.edgedetec‐
73       tion, module. Otherwise, it goes to error! The output  of  this  module
74       will  be  the  input of v.lidar.correction module. The output will be a
75       vector map which points are pre-classified as:
76       TERRAIN SINGLE PULSE (cat = 1, layer = 2)
77       TERRAIN DOUBLE PULSE (cat = 2, layer = 2)
78       OBJECT SINGLE PULSE (cat = 3, layer = 2)
79       OBJECT DOUBLE PULSE (cat = 4, layer = 2)
80       The  final  result  of  the  whole  procedure   (v.lidar.edgedetection,
81       v.lidar.growing,  v.lidar.correction) will be a point classification in
82       the same categories as above.
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EXAMPLES

85   Basic region growing procedure
86       v.lidar.growing input=edge output=growing first=firstpulse
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AUTHOR

93       Original version of program in GRASS 5.4:
94       Maria  Antonia Brovelli, Massimiliano Cannata, Ulisse Longoni and Mirko
95       Reguzzoni
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97       Update for GRASS 6.X:
98       Roberto Antolin and Gonzalo Moreno
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REFERENCES

101       Antolin, R. et al., 2006. Digital terrain models determination by LiDAR
102       technology:  Po  basin experimentation. Bolletino di Geodesia e Scienze
103       Affini, anno LXV, n. 2, pp. 69-89.
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105       Brovelli M. A., Cannata M., Longoni U.M., 2004.  LIDAR  Data  Filtering
106       and  DTM  Interpolation  Within GRASS, Transactions in GIS, April 2004,
107       vol. 8, iss. 2, pp. 155-174(20), Blackwell Publishing Ltd.
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109       Brovelli M. A., Cannata M., 2004. Digital Terrain model  reconstruction
110       in  urban  areas  from  airborne laser scanning data: the method and an
111       example for Pavia (Northern Italy). Computers and Geosciences 30 (2004)
112       pp.325-331
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114       Brovelli  M.  A.  and Longoni U.M., 2003. Software per il filtraggio di
115       dati LIDAR, Rivista dell?Agenzia del Territorio, n. 3-2003,  pp.  11-22
116       (ISSN 1593-2192).
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118       Brovelli  M.  A.,  Cannata M. and Longoni U.M., 2002. DTM LIDAR in area
119       urbana, Bollettino SIFET N.2, pp. 7-26.
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121       Performances of the filter can be seen in the ISPRS WG III/3 Comparison
122       of Filters report by Sithole, G. and Vosselman, G., 2003.
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124       Last changed: $Date: 2015-09-08 04:45:01 +0200 (Tue, 08 Sep 2015) $
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SOURCE CODE

127       Available at: v.lidar.growing source code (history)
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129       Main  index  | Vector index | Topics index | Keywords index | Graphical
130       index | Full index
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132       © 2003-2019 GRASS Development Team, GRASS GIS 7.4.4 Reference Manual
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136GRASS 7.4.4                                                 v.lidar.growing(1)