Hi Kaipi,
I've only been doing rural LiDAR processing, so can't help regards building
removal for the DTM.
One thing that isn't mentioned in the Brovelli, 2004 article or the online
documention on the wiki, is that spline 'step' relates to metres (1 step =
1m). Obvious I know, but wasn't to me when I started fiddling with the
parametersand the LiDAR data for the first time. Therefore:
-see and sen parameter in v.lidar.edgedetection to 400
is 400m! and hence:
-the detected edges are now so wide, that they cover complete buildings
The spline step parameters should be double the average distance between
points. So for 50pts/m² the spline steps chould be 0.04 (2*(1/50)) for
example. Play with these either side of 0.04 in the parameters until you get
a good result. These modules were designed a few years ago now, and not
really designed for such high resolution data, though should still work.
Though I am not entirely sure what you are attempting to do (e.g. purpose of
data: remove building for DTM/ or create 3D model of the building DSM).
You will find that v.outlier is the biggest restriction on how many points
you can process at one time. I was working with roughly 1.5pts/m² and found
that I had to work in 1km tiles due to the v.outlier restriction. Something
to be wary of when you decrease the spline step incase you start getting
errors.
For reference, I was using:
GRASS GIS (v.6.4.0svn, library Revision: 37101 (2009-05-10)) (windows
version)
----- Original Message -----
From: "kaipi" <mapcoll...@gmx.net>
To: <grass-user@lists.osgeo.org>
Sent: Friday, October 30, 2009 12:43 PM
Subject: [GRASS-user] Problem with Lidar Tools
Dear list,
I am quite new to Grass and need to generate a DSM from Lidar data. Here is
my workflow so far:
v.in.ascii input=f:\lidar_test\single.csv output=single fs=, x=1 y=2 z=3 -z
-b -t --o
v.build single
g.region vect=single
v.in.ascii input=f:\lidar_test\first.csv output=first fs=, x=1 y=2 z=3 -z -b
-t --o
v.outlier input=single output=inlier_s outlier=outlier_s thres_o=5 soe=1
son=1 lambda_i=0.1 --o
v.outlier input=first output=inlier_f outlier=outlier_f thres_o=5 soe=1
son=1 lambda_i=0.1 --o
v.lidar.edgedetection input=inlier_s output=edgedetected see=400 sen=400
lambda_g=0.01 tgh=6 tgl=3 theta_g=0.26 lambda_r=1 --o
v.lidar.growing input=edgedetected output=growing first=inlier_f tj=0.25
td=0.6 --o
v.lidar.correction input=growing output=classified terrain=terrain sce=5
scn=5 lambda_c=1 tch=2 tcl=1 --o
v.lidar.correction input=classified output=classified_it2
terrain=terrain_it2 sce=5 scn=5 lambda_c=1 tch=2 tcl=1 --o
v.build terrain_it2
v.out.ogr in=terrain_it2 dsn=F:\lidar_test\terrain_it2 format=ESRI_Shapefile
type=point lco=SHPT=POINTZ -e
v.lidar.edgedetection classifies the data into cat 1 and cat 2 (=Terrain or
Edge ?). This seams to work. The next step is v.lidar.growing. This tool
should classify into 4 categories: TERRAIN SINGLE PULSE, TERRAIN DOUBLE
PULSE, OBJECT SINGLE PULSE or OBJECT DOUBLE PULSE. But this does not happen.
The cats still remain the same (cat1 and cat2) and the output looks
identical to the output from v.lidar.edgedetection. v.lidar.growing seams to
have no effect.
Am I doing something wrong ?
I have another problem with the parameters of the lidar tools (although I
read Brovellis "Managing and processing LIDAR data within GRASS"). Can you
give me some hints how to adjust the default values to very high res Lidar
data (=50 points/m²). I raised see and sen parameter in
v.lidar.edgedetection to 400 with the result, that the detected edges are
now so wide, that they cover complete buildings. This way I can get rid of
the most buildings but the result is not really satisfying and I guess the
problem is false classification of v.lidar.growing
Let me know if you need more infos.
I am using GRass 6.3.0 on Windows. Can I expect improvements switching to
6.4 or switching to Linux ?
Thank you very much !!
kaipi
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