Ubuntu Manpage: v.lidar.edgedetection - Detects the object's edges from a LIDAR data set.

NAME

       v.lidar.edgedetection  - Detects the object's edges from a LIDAR data set.

KEYWORDS

       vector, LIDAR, edges

SYNOPSIS

       v.lidar.edgedetection
       v.lidar.edgedetection help
       v.lidar.edgedetection   [-e]   input=name   output=name    [see=float]    [sen=float]    [lambda_g=float]
       [tgh=float]   [tgl=float]   [theta_g=float]   [lambda_r=float]   [--overwrite]  [--verbose]  [--quiet]

   Flags:
       -e
           Estimate point density and distance
           Estimate point density and distance for the input vector points within the current region extends and
           quit

       --overwrite
           Allow output files to overwrite existing files

       --verbose
           Verbose module output

       --quiet
           Quiet module output

   Parameters:
       input=name
           Name of input vector map

       output=name
           Name for output vector map

       see=float
           Interpolation spline step value in east direction
           Default: 4

       sen=float
           Interpolation spline step value in north direction
           Default: 4

       lambda_g=float
           Regularization weight in gradient evaluation
           Default: 0.01

       tgh=float
           High gradient threshold for edge classification
           Default: 6

       tgl=float
           Low gradient threshold for edge classification
           Default: 3

       theta_g=float
           Angle range for same direction detection
           Default: 0.26

       lambda_r=float
           Regularization weight in residual evaluation
           Default: 2

DESCRIPTION

v.lidar.edgedetection is the first 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.
In particular, this module detects the edge of each single feature over the terrain surface of a LIDAR
point surface. First of all, a bilinear spline interpolation with a Tychonov regularization parameter is
performed. The gradient is minimized and the low Tychonov regularization parameter brings the
interpolated functions as close as possible to the observations. Bicubic spline interpolation with
Tychonov regularization is then performed. However, now the curvature is minimized and the regularization
parameter is set to a high value. For each point, an interpolated value is computed from the bicubic
surface and an interpolated gradient is computed from the bilinear surface. At each point the gradient
magnitude and the direction of the edge vector are calculated, and the residual between interpolated and
observed values is computed. Two thresholds are defined on the gradient, a high threshold tgh and a low
one tgl. For each point, if the gradient magnitude is greater than or equal to the high threshold and its
residual is greater than or equal to zero, it is labeled as an EDGE point. Similarly a point is labeled
as being an EDGE point if the gradient magnitude is greater than or equal to the low threshold, its
residual is greater than or equal to zero, and the gradient to two of eight neighboring points is greater
than the high threshold. Other points are classified as TERRAIN.
The output will be a vector map in which points has been classified as TERRAIN, EDGE or UNKNOWN. This
vector map should be the input of v.lidar.growing module.

NOTES

       In this module, an external table will be created which will  be  useful  for  the  next  module  of  the
       procedure  of  LiDAR  data  filtering. In this table the interpolated height values of each point will be
       recorded. Also points in the output vector map will be classified as:
       TERRAIN (cat = 1, layer = 1)
       EDGE (cat = 2, layer = 1)
       UNKNOWN (cat = 3, layer = 1)
       The final result of the whole procedure (v.lidar.edgedetection, v.lidar.growing, v.lidar.correction) will
       be a point classification in four categories:
       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)

EXAMPLES

   Basic edge detection

       v.lidar.edgedetection input=vector_last output=edge see=8 sen=8 lambda_g=0.5

AUTHORS

       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.

       Last changed: $Date: 2010-09-16 00:25:59 -0700 (Thu, 16 Sep 2010) $

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       © 2003-2013 GRASS Development Team

GRASS 6.4.3                                                                        v.lidar.edgedetection(1grass)