Reduce Density of points

[Carmen Cima Rodriguez]

Hi everybody,

I need help with a doubt. I have a huge amount of lidar points in my tile. The average density is 34 points/m2 and the range of the values are from 1 to 244 points/m2, and they have a irregular distribution. I need to reduce this density without increase a lot my error.

Anybody knows how to do it.

Thanks

C

[Terje Mathisen]

This is relatively easy to do, but do you really need to?

How large is your entire area, i.e. what is the total file size?

Can you make a quick graph showing points/cell with reasonable resolution?

Terje
> Thanks
> C
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[Carmen Cima Rodriguez]

[Francois Joyal]

Hi Carmen

In fact I have an other question related to yours: How to reduce density of points by an altitude criteria? I mean how to delete points within 5 cm in Z value? That means only significant points (in z value) will be kept. Instead having 100000 points on a flat area, I'll obtain only 1000 points if I give a Z criteria. Thanks to all how can response.

Frank

[Martin Isenburg]

Hello Carmen,

I need help with a doubt. I have a huge amount of lidar points in my tile. The average density is 34 points/m2 and the range of the values are from 1 to 244 points/m2, and they have a irregular distribution. I need to reduce this density without increase a lot my error.

There are several strategies how to reduce the average density but it really depends on what you ultimately want to compute from the thinned-out LiDAR to determine which is the best method. I would use different strategies for DTM / DSM / CHM production versus forestry metric computation versus ... so it would help if you could describe why you need to reduce the density and what task you will be carrying out on the reduced point cloud.

Regards,

Martin @rapidlasso

[Martin Isenburg]

Hello Francois,

the next release of LAStools will have a new feature in lasthin that will allow "adaptive thinning" based on a vertical tolerance of, for example, 20 centimeters. Here are the command lines that will be available in the next (!!!) release of LAStools.

lasthin -i ..\data\fusa.laz ^

            -ignore_class 1 3 4 5 6 7 ^

            -adaptive 0.2 ^

            -classify_as 8 ^

            -o fusa_classified_keypoints.laz

will produce a new version of the venerable "fusa.laz" where the "most important" ground points (classification code 2) are reclassified as keypoints (classification code 8).

lasthin -i ..\data\fusa.laz ^

            -ignore_class 1 3 4 5 6 7 ^

            -adaptive 0.2 ^

            -flag_as_keypoint ^

            -o fusa_flagged_keypoints.laz

or we can get a coarser version of only ground and buildings using

lasthin -i ..\data\fusa.laz ^

            -keep_class 2 6 ^

            -adaptive 0.2 ^

            -o fusa_thinned_ground_buildings.laz

I have attached two screenshots for the result that the last command line is getting. If you want to get a pre-release for testing (and bug-finding) let me know.

Regards,

Martin @rapidlasso

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[Martin Isenburg]

Hello,

the latest release of LAStools  (160329) has the new '-adaptive 0.1' thinning as a new option (see README).

http://lastools.org/download/lasthin_README.txt

It also fixes a small bug that was leading to duplicate points when using the beam-widening option '-subcircle 0.1' that I had advocated as a preprocessing step for generating pit-free CHMs on the blog article on that topic "rasterzing perfect canopy height models". Updating to that latest version should improve your CHMs further.

Also laspublish still had a small defect as the links from the download map to the LiDAR were often broken. This was fixed too.

http://lastools.org/download/laspublish_README.txt

As always you can find the complete list of changes here:

http://lastools.org/download/CHANGES.txt

Regards,

Martin @rapidlasso

[cai...@vicforests.com.au]

Hi Martin,

I found a las file has error see attached lasinfo file

lasinfo for I:\Lidar\eg2011\LAZ\mine656000_minn5849500_maxe656500_maxn5850000.laz
reporting all LAS header entries:
  file signature:             'LASF'
  file source ID:             0
  global_encoding:            0
  project ID GUID data 1-4:   00000000-0000-0000-0000-000000000000
  version major.minor:        1.0
  system identifier:          ''
  generating software:        'TerraScan'
  file creation day/year:     0/0
  header size:                227
  offset to point data:       323
  number var. length records: 1
  point data format:          1
  point data record length:   28
  number of point records:    630839
  number of points by return: 571753 57168 1895 23 0
  scale factor x y z:         0.01 0.01 0.01
  offset x y z:               0 0 0
  min x y z:                  0.00 0.00 0.00
  max x y z:                  656550.00 5850049.99 1279.08
variable length header record 1 of 1:

I'd like to know, how to fix this problem?


Regards

Cai Li  I  GIS Analyst, Resources  I  VicForests

Level 7, 473 Bourke Street, Melbourne  Vic  3000  I  G P O Box 191, Melbourne   Vic   3001
T:  +61 03 9608 9571  I   F:  +61 03 9608 9566  I  E:  cai...@vicforests.com.au

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[Martin Isenburg]

Hello Cai-Li,

It could be that the bounding box is correct because there might be some null points whose attributes are all zero in the file. Unfortunately did you not send a complete lasinfo report as the min and max listing of all point attributes would divulge that.

You can fix the counters and the bounding box in the LAS header with

lasinfo -i in.laz -repair

or only the bounding box with

lasinfo -i in.laz -repair_bb

Regards,

Martin

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