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
11

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]  [--verbose]  [--quiet]
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18   Flags:
19       --overwrite
20           Allow output files to overwrite existing files
21
22       --verbose
23           Verbose module output
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25       --quiet
26           Quiet module output
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28   Parameters:
29       input=name
30           Name of input vector map
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32       output=name
33           Name for output vector map
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35       first=name
36           Name of the first pulse vector map
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38       tj=float
39           Threshold for cell object frequency in region growing
40           Default: 0.2
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42       td=float
43           Threshold for double pulse in region growing
44           Default: 0.6
45

DESCRIPTION

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

65       The  input  data  should be the output result of the v.lidar.correction
66       module. Otherwise, it goes to error! The output of this module will  be
67       the input of v.lidar.correction module. The output will be a vector map
68       which points are pre-classified as:
69       TERRAIN SINGLE PULSE (cat = 1, layer = 2)
70       TERRAIN DOUBLE PULSE (cat = 2, layer = 2)
71       OBJECT SINGLE PULSE (cat = 3, layer = 2)
72       OBJECT DOUBLE PULSE (cat = 4, layer = 2)
73       The  final  result  of  the  whole  procedure   (v.lidar.edgedetection,
74       v.lidar.growing,  v.lidar.correction) will be a point classification in
75       the same categories as above.
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EXAMPLES

78   Basic region growing procedure
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80       v.lidar.growing input=edge output=growing
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82

SEE ALSO

84       v.lidar.edgedetection, v.lidar.correction, v.surf.bspline
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AUTHOR

87       Original version of program in GRASS 5.4:
88       Maria Antonia Brovelli, Massimiliano Cannata, Ulisse Longoni and  Mirko
89       Reguzzoni
90       Update for GRASS 6.X:
91       Roberto Antolin and Gonzalo Moreno
92

REFERENCES

94       Antolin, R. et al., 2006. Digital terrain models determination by LiDAR
95       technology: Po basin experimentation. Bolletino di Geodesia  e  Scienze
96       Affini, anno LXV, n. 2, pp. 69-89.
97       Brovelli  M.  A.,  Cannata M., Longoni U.M., 2004. LIDAR Data Filtering
98       and DTM Interpolation Within GRASS, Transactions in  GIS,  April  2004,
99       vol. 8, iss. 2, pp. 155-174(20), Blackwell Publishing Ltd.
100       Brovelli  M. A., Cannata M., 2004. Digital Terrain model reconstruction
101       in urban areas from airborne laser scanning data:  the  method  and  an
102       example for Pavia (Northern Italy). Computers and Geosciences 30 (2004)
103       pp.325-331
104       Brovelli M. A. and Longoni U.M., 2003. Software per  il  filtraggio  di
105       dati  LIDAR,  Rivista dell?Agenzia del Territorio, n. 3-2003, pp. 11-22
106       (ISSN 1593-2192).
107       Brovelli M. A., Cannata M. and Longoni U.M., 2002. DTM  LIDAR  in  area
108       urbana, Bollettino SIFET N.2, pp. 7-26.
109       Performances of the filter can be seen in the ISPRS WG III/3 Comparison
110       of Filters report by Sithole, G. and Vosselman, G., 2003.
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112       Last changed: $Date: 2007-10-18 15:40:28 +0200 (Thu, 18 Oct 2007) $
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114       Full index
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116       © 2003-2008 GRASS Development Team
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120GRASS 6.3.0                                                 v.lidar.growing(1)
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