[GRASS-user] Lidar points height from ground

Fri Mar 30 10:52:03 EDT 2012

Hi!
Don't know if i understood everything correctly. (Only ob mobile right now)
If it's not mandatory to use grass you can also use Laslib drom martin
isenburg. I am pretty sure that. it should do what you want pretty fast and
with huge amount of points..
I hope i got you right .. if not sorry f0r the noise

Regards
Werner
Am 30.03.2012 16:43 schrieb "michael vetter" <mv at ipf.tuwien.ac.at>:

>  hey,
>
> you can also calculate a normalized point cloud by subtract Z(from point)
> from the DTM(Z)
>
> you need a DTM (as raster) and the LiDAR points as ASCII
>
>
> 1. "r.stats -gn in=DTM >temp_elev"
> 2. create a dictionary in python, from "temp_elev" k=x,y and value=z (x
> and y should INT)
> 3. loop the point cloud and subtract the z from k for each LiDAR point and
> add a nZ column >> nDTM_LiDAR_points
>
> 2 and 3 should run in the same script!
>
>     e.g. In Python:
>
> #read input raster data (ascii from r.stats -gn DTM)
> for lineR in iR.readlines():
>     valR = lineR.strip().split(' ')
>     x = float(valR[0])
>     y = float(valR[1])
>     k = ('%s %s' % (int(x),int(y)))
>     z = float(valR[2])
>     value.append(z)
>     D[k] = value
>     value = []
>
> #read input point cloud as ascii and caclate nZ
> for lineP in iP.readlines():
>     valP = lineP.strip().split(' ')
>     x = float(valP[0])
>     y = float(valP[1])
>     k = ('%s %s' % (int(x),int(y)))
>     Z = float(valP[2])
>     output.write('%s %s %s %s\n' %(x,y,Z,Z-D[k][0]))
> oF.write(output.getvalue())
>
> then you can 'awk' the data you are interested in 'cat nDTM_LiDAR_points |
> awk '{if($4 < 2 && $4 > 1) print $0}' >LiDAR_1_to_2
>
> r.in.xyz LiDAR_1_to_2 out=LiDAR_1_to_2 method=n
>
> you can see the related reference to a similar workflow:
>
> http://www.isprs.org/proceedings/XXXVIII/5-W12/Papers/ls2011_submission_35.pdf
>
> Michael
>
> Am 2012-03-30 14:52, schrieb Daniel Lee:
>
> Hi Daniel V ;)
>
> You're right, that might not be the best way to go. I thought that it
> might simply be faster to do a topological operation rather than a DB edit.
> To be honest, I'd stay away from any 3D objects like volumes because it'd
> just get pretty complicated if you use them... As far as I know ;) Could be
> wrong. My suggestion would use the following steps:
>
> 1. Make terrain raster
> 2. Make surface raster
> -- Here I'm assuming that for you basically have only two height "layers"
> - i.e. no points that contain information between the surface raster and
> terrain (like bushes beneath a tree cover).
> 3. Make a relative digital surface model (rDSM) (r.mapcalc --> rDSM =
> surface - terrain)
> 4. Reclassify the rDSM into the different classes you're interested in
> 5. Convert the reclassified raster into an area vector file.
> -- This makes a 2D map of polygons that cover the same areas as the raster
> classes.
> 6. Extract the points inside the different different height classes
> (v.select)
>
> However, if you're working with regularly spaced points that pass onto a
> regular grid (=1 pt. / raster pixel) you could always use r.stats to tell
> you how much area is in each raster category. Then you really wouldn't need
> vectors at all.
>
> Daniel L.
>
> --
>
> B.Sc. Daniel Lee
> GeschÃ¤ftsfÃ¼hrung fÃ¼r Forschung und Entwicklung
> ISIS - International Solar Information Solutions GbR
> Vertreten durch: Daniel Lee, Nepomuk Reinhard und Nils RÃ¤der
>
> Deutschhausstr. 10
> 35037 Marburg
> Festnetz: +49 6421 379 6256
> Mobil: +49 176 6127 7269
> E-Mail: Lee at isi-solutions.org
> Web: http://www.isi-solutions.org
>
> ISIS wird gefÃ¶rdert durch die Bundesrepublik Deutschland, Zuwendungsgeber:
> Bundesministerium fÃ¼r Wirtschaft und Technologie aufgrund eines Beschlusses
> des Deutschen Bundestages, sowie durch die EuropÃ¤ische Union,
> Zuwendungsgeber: EuropÃ¤ischer Sozialfonds.
> ZusÃ¤tzliche UnterstÃ¼tzung erhÃ¤lt ISIS von dem Entrepreneurship Cluster
> Mittelhessen, der UniversitÃ¤t Marburg, dem Laboratory for Climatology and
> Remote Sensing und dem GIS-Lab Marburg.
>
>
>
> Am 30. MÃ¤rz 2012 14:09 schrieb Daniel Victoria <daniel.victoria at gmail.com>
> :
>
>> Hi Daniel Lee (two Daniels changing emails is a hard thing to follow...)
>>
>> I can create the different height classes raster easily but I'm not
>> sure how to get the lidar points from the cloud that are in each
>> vertical slice.
>>
>> Maybe work with raster volumes? Is there a way to cross points at
>> different volumes?
>>
>> The fact is, I'm not seeing how to do this without having to import
>> the lidar point cloud.
>>
>> Schematically, what I want to do is count the number of points that
>> are in the vertical bins 1 2, (g is ground), a vertical slice...
>>         ___
>>         | . :
>> bin 2  | :
>>         | .
>>         -----
>> bin 1  | ...
>>         | .
>>        ggggg
>>
>> Cheers and many thanks for the attention
>> Daniel V
>>
>>
>> On Fri, Mar 30, 2012 at 8:08 AM, Daniel Lee <lee at isi-solutions.org>
>> wrote:
>> > Hi Daniel,
>> >
>> > You could try making different rasters with classes (0-5m over ground,
>> 5-10m
>> > over ground, etc.) and then convert them into polygons, then check how
>> many
>> > points are inside them. I'm not sure if it'd be faster than the way you
>> > suggested originally, though, when you think that you'd have to make the
>> > rasters first, etc.
>> >
>> > I ended up giving up on large vector operations with LiDAR point clouds
>> in
>> > GRASS 6.4 because it simply took way too long, but I was dealing with
>> > millions of points. For such a small dataset it's probably fine, since
>> as
>> > long as you know your script is okay you can let it run through your
>> lunch
>> > break ;)
>> >
>> >
>> > Daniel
>> >
>> > --
>> >
>> > B.Sc. Daniel Lee
>> > GeschÃ¤ftsfÃ¼hrung fÃ¼r Forschung und Entwicklung
>> > ISIS - International Solar Information Solutions GbR
>> > Vertreten durch: Daniel Lee, Nepomuk Reinhard und Nils RÃ¤der
>> >
>> > Deutschhausstr. 10
>> > 35037 Marburg
>> > Festnetz: +49 6421 379 6256
>> > Mobil: +49 176 6127 7269
>> > E-Mail: Lee at isi-solutions.org
>> > Web: http://www.isi-solutions.org
>> >
>> > ISIS wird gefÃ¶rdert durch die Bundesrepublik Deutschland,
>> Zuwendungsgeber:
>> > Bundesministerium fÃ¼r Wirtschaft und Technologie aufgrund eines
>> Beschlusses
>> > des Deutschen Bundestages, sowie durch die EuropÃ¤ische Union,
>> > Zuwendungsgeber: EuropÃ¤ischer Sozialfonds.
>> > ZusÃ¤tzliche UnterstÃ¼tzung erhÃ¤lt ISIS von dem Entrepreneurship Cluster
>> > Mittelhessen, der UniversitÃ¤t Marburg, dem Laboratory for Climatology
>> and
>> > Remote Sensing und dem GIS-Lab Marburg.
>> >
>> >
>> >
>> >
>> > Am 30. MÃ¤rz 2012 13:00 schrieb Daniel Victoria <
>> daniel.victoria at gmail.com>:
>> >
>> >> I need to calculate the number of points at different height levels.
>> That
>> >> is, how many points are from 0 to 5 meters? And from 5 to 10? And so
>> on. So
>> >> I believe I need to work with vector points and a database. Or is there
>> >> another way?
>> >> Thanks
>> >> Daniel
>> >>
>> >> On Mar 30, 2012 6:47 AM, "Daniel Lee" <lee at isi-solutions.org> wrote:
>> >>>
>> >>> Hi there,
>> >>>
>> >>> I don't work too much with vectors, but my personal experience with
>> them
>> >>> has been fairly slow, perhaps due to the topology. If you have access
>> to the
>> >>> raw point cloud, you could try importing the ground and surface
>> points as
>> >>> separate rasters using r.in.xyz and then use r.mapcalc to get the
>> height by
>> >>> subtracting the ground from the surface raster. Or do you definitely
>> need
>> >>> vector points as an output?
>> >>>
>> >>> Best,
>> >>> Daniel
>> >>>
>> >>> --
>> >>>
>> >>> B.Sc. Daniel Lee
>> >>> GeschÃ¤ftsfÃ¼hrung fÃ¼r Forschung und Entwicklung
>> >>> ISIS - International Solar Information Solutions GbR
>> >>> Vertreten durch: Daniel Lee, Nepomuk Reinhard und Nils RÃ¤der
>> >>>
>> >>> Deutschhausstr. 10
>> >>> 35037 Marburg
>> >>> Festnetz: +49 6421 379 6256
>> >>> Mobil: +49 176 6127 7269
>> >>> E-Mail: Lee at isi-solutions.org
>> >>> Web: http://www.isi-solutions.org
>> >>>
>> >>> ISIS wird gefÃ¶rdert durch die Bundesrepublik Deutschland,
>> >>> Zuwendungsgeber: Bundesministerium fÃ¼r Wirtschaft und Technologie
>> aufgrund
>> >>> eines Beschlusses des Deutschen Bundestages, sowie durch die
>> EuropÃ¤ische
>> >>> Union, Zuwendungsgeber: EuropÃ¤ischer Sozialfonds.
>> >>> ZusÃ¤tzliche UnterstÃ¼tzung erhÃ¤lt ISIS von dem Entrepreneurship Cluster
>> >>> Mittelhessen, der UniversitÃ¤t Marburg, dem Laboratory for Climatology
>> and
>> >>> Remote Sensing und dem GIS-Lab Marburg.
>> >>>
>> >>>
>> >>>
>> >>>
>> >>> Am 29. MÃ¤rz 2012 22:59 schrieb Daniel Victoria
>> >>> <daniel.victoria at gmail.com>:
>> >>>>
>> >>>> Hi all,
>> >>>>
>> >>>> I'm trying to calculate the height from the ground of several lidar
>> >>>> points (15million) in order to get the number of points that occur at
>> >>>> different height levels. I read some older posts about using r.in.xyz
>> >>>> (or r.in.lidar in grass 7) but I could not understand how to count
>> the
>> >>>> number or points that have height from 0 to 5 m above the ground, for
>> >>>> instance. So, I'm trying to do the following.
>> >>>>
>> >>>> 1) import points using v.in.lidar (Grass 7 ubuntu linux)
>> >>>> 2) create a column in the database for the ground height and one for
>> >>>> elevation
>> >>>> 3) populate height column from ground raster (generate in another
>> >>>> process) using v.what.rast
>> >>>> 4) calculate elevation as zcoord - ground for each point
>> (v.db.update)
>> >>>>
>> >>>> As you might imagine, this takes a long time. Just to import a 400Mb
>> >>>> lidar file takes around 50min.
>> >>>> Is there any easier way that I'm not envisioning?
>> >>>>
>> >>>> I'm running Grass 7 with liblas on a Ubuntu Virtual Machine and
>> sqlite
>> >>>> backend.
>> >>>>
>> >>>> Thanks
>> >>>> Daniel
>> >>>> _______________________________________________
>> >>>> grass-user mailing list
>> >>>> grass-user at lists.osgeo.org
>> >>>> http://lists.osgeo.org/mailman/listinfo/grass-user
>> >>>
>> >>>
>> >
>>
>
>
>
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>
>
> --
> Mag. Michael Vetter
>
> Institute of Photogrammetry and Remote Sensing (I.P.F.)
> Vienna University of Technology (TU Wien)
> Gusshausstrasse 27-29, 1040 Vienna, Austria
>
>
> Centre for Water Resource Systems (CWRS)
> Vienna University of Technology (TU Wien)
> Karlsplatz 13/222, A-1040 Vienna, Austria
>
>
> Tel: +43-(0)1-58801-22226
> E-mail: mv at ipf.tuwien.ac.atwww.ipf.tuwien.ac.atwww.waterresources.at
>
>
>
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