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


       vector, LIDAR


       v.lidar.growing --help
       v.lidar.growing input=name output=name first=name  [tj=float]   [td=float]   [--overwrite]
       [--help]  [--verbose]  [--quiet]  [--ui]

           Allow output files to overwrite existing files

           Print usage summary

           Verbose module output

           Quiet module output

           Force launching GUI dialog

       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

           Threshold for cell object frequency in region growing
           Default: 0.2

           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
       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.


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


          v.lidar.edgedetection,   v.lidar.correction,,,,


       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.

       Last changed: $Date: 2015-09-08 04:45:01 +0200 (Tue, 08 Sep 2015) $


       Available at: v.lidar.growing source code (history)

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