LasHeight

[Mark Tukman]

I'm trying to run lascanopy to create a 30-meter raster that represents the % of all returns between 3 and 24 feet above ground.  

First I believe I need to run lasground, to normalize the points to height above ground.  But when I run something like the command below, the values are way too high (many points have new Zs greater than 500).  Vert. and horizontal units are survey feet and should be properly coded.    I tried using the '-feet' and '-elevation_feet' args and got the same result.  

lasheight -i "E:\lidar_proc\raw_laz\SOCO_0047_096.laz" -replace_z -olaz

Here's a link to the laz file:

https://tukmangeospatial.egnyte.com/dl/uM0c8Tpc0L

Thanks to anyone who can help!

Mark

[Martin Isenburg]

Hello,

well. There are a few points (isolated noise points) - or here exactly one - that are high above the others as you can see in the lasinfo report histogram below with 10 meter bins for the z coordinate generated with the '-histo z 10' option. They are clearly visible in lasview if you press '=' a few times to make the displayed points really fat. You could drop the noise points but there are many many points classified as noise (namely 186125  noise (7)) so maybe that's dropping too many. It may be worthwhile to rerun the noise removal more conservatively with lasnoise.

Also note that simply calling this 

lasheight -i SOCO_0047_096.laz -replace_z -odix _h -olaz

tends to give edge artifacts along the tile boundary when ground points are sparse along the tile edges. Especially in complex terrain this will be noticeable.

http://rapidlasso.com/2015/08/07/use-buffers-when-processing-lidar-in-tiles/

To do height computations correctly - also along the tile boundaries - we need to use buffers. Since we do not use lastile with option '-buffer 30' because you have already pre-existing tiles we need to use on-the-fly buffering for which we should index first. For a full folder of tiles that would look like this:

lasindex -i E:\lidar_proc\raw_laz\*.laz ^

              -cores 4

lasheight -i E:\lidar_proc\raw_laz\*.laz ^

                -buffered 30 ^

                -drop_class 7 ^

                -replace_z ^

                -odir E:\lidar_proc\norm_laz -olaz ^

                -cores 4

  

==================================================================

lasinfo (180910) report for 'C:\software\LAStools\bin\SOCO_0047_096.laz'

reporting all LAS header entries:

  file signature:             'LASF'

  file source ID:             0

  global_encoding:            1

  project ID GUID data 1-4:   00000000-0000-0000-4F53-4F4E0000414D

  version major.minor:        1.2

  system identifier:          'WSI'

  generating software:        'LasMonkey 1.6.5'

  file creation day/year:     87/2014

  header size:                227

  offset to point data:       329

  number var. length records: 1

  point data format:          3

  point data record length:   34

  number of point records:    6165323

  number of points by return: 4322686 1517298 293894 29838 1607

  scale factor x y z:         0.01 0.01 0.01

  offset x y z:               0 0 0

  min x y z:                  6356317.01 1958902.02 585.37

  max x y z:                  6358416.97 1961001.98 2564.33

variable length header record 1 of 1:

  reserved             0

  user ID              'LASF_Projection'

  record ID            34735

  length after header  48

  description          'California 2 NAD83(2011)-Ft US'

    GeoKeyDirectoryTag version 1.1.0 number of keys 5

      key 1024 tiff_tag_location 0 count 1 value_offset 1 - GTModelTypeGeoKey: ModelTypeProjected

      key 3072 tiff_tag_location 0 count 1 value_offset 26942 - ProjectedCSTypeGeoKey: NAD83 / California zone 2

      key 3076 tiff_tag_location 0 count 1 value_offset 9003 - ProjLinearUnitsGeoKey: Linear_Foot_US_Survey

      key 4096 tiff_tag_location 0 count 1 value_offset 5103 - VerticalCSTypeGeoKey: VertCS_North_American_Vertical_Datum_1988

      key 4099 tiff_tag_location 0 count 1 value_offset 9003 - VerticalUnitsGeoKey: Linear_Foot_US_Survey

LASzip compression (version 2.2r0 c2 50000): POINT10 2 GPSTIME11 2 RGB12 2

reporting minimum and maximum for all LAS point record entries ...

  X           635631701  635841697

  Y           195890202  196100198

  Z               58537     256433

  intensity           0        255

  return_number       1          5

  number_of_returns   1          5

  edge_of_flight_line 0          0

  scan_direction_flag 0          1

  classification      1          7

  scan_angle_rank   -16         20

  user_data           0          0

  point_source_ID   451       1457

  gps_time 65893482.521173 65895845.077638

  Color R 1792 65280

        G 3072 65280

        B 1024 65280

number of first returns:        4322686

number of intermediate returns: 325255

number of last returns:         4323131

number of single returns:       2805749

overview over number of returns of given pulse: 2805749 2446656 792068 112825 80

25 0 0

histogram of classification of points:

          741189  unclassified (1)

          767651  ground (2)

         4431626  high vegetation (5)

           38732  building (6)

          186125  noise (7)

z coordinate histogram with bin size 10.000000

  bin [580,590) has 75

  bin [590,600) has 431

  bin [600,610) has 976

  bin [610,620) has 1639

  bin [620,630) has 7323

  bin [630,640) has 6205

  bin [640,650) has 9661

  bin [650,660) has 11640

  bin [660,670) has 13761

  bin [670,680) has 19820

  bin [680,690) has 29567

  bin [690,700) has 29648

  bin [700,710) has 28769

  bin [710,720) has 29920

  bin [720,730) has 31230

  bin [730,740) has 37234

  bin [740,750) has 41493

  bin [750,760) has 47133

  bin [760,770) has 48739

  bin [770,780) has 51146

  bin [780,790) has 55802

  bin [790,800) has 62561

  bin [800,810) has 72751

  bin [810,820) has 79890

  bin [820,830) has 76737

  bin [830,840) has 79621

  bin [840,850) has 84678

  bin [850,860) has 90340

  bin [860,870) has 99383

  bin [870,880) has 109937

  bin [880,890) has 104819

  bin [890,900) has 110394

  bin [900,910) has 115708

  bin [910,920) has 126006

  bin [920,930) has 132058

  bin [930,940) has 136638

  bin [940,950) has 146002

  bin [950,960) has 163010

  bin [960,970) has 143854

  bin [970,980) has 158633

  bin [980,990) has 154374

  bin [990,1000) has 169978

  bin [1000,1010) has 167200

  bin [1010,1020) has 157339

  bin [1020,1030) has 153878

  bin [1030,1040) has 147440

  bin [1040,1050) has 136646

  bin [1050,1060) has 127925

  bin [1060,1070) has 127751

  bin [1070,1080) has 139493

  bin [1080,1090) has 142387

  bin [1090,1100) has 140920

  bin [1100,1110) has 141368

  bin [1110,1120) has 144431

  bin [1120,1130) has 132698

  bin [1130,1140) has 123512

  bin [1140,1150) has 114776

  bin [1150,1160) has 115613

  bin [1160,1170) has 120956

  bin [1170,1180) has 110535

  bin [1180,1190) has 120454

  bin [1190,1200) has 113640

  bin [1200,1210) has 101796

  bin [1210,1220) has 91575

  bin [1220,1230) has 74931

  bin [1230,1240) has 60019

  bin [1240,1250) has 45150

  bin [1250,1260) has 36480

  bin [1260,1270) has 29891

  bin [1270,1280) has 23389

  bin [1280,1290) has 18002

  bin [1290,1300) has 17380

  bin [1300,1310) has 17582

  bin [1310,1320) has 16586

  bin [1320,1330) has 15184

  bin [1330,1340) has 10370

  bin [1340,1350) has 5550

  bin [1350,1360) has 2342

  bin [1360,1370) has 504

  bin [1370,1380) has 45

  bin [2560,2570) has 1

  average z coordinate 1006.8227918225849 for 6165323 element(s)

[Floris Groesz]

Another way of handling occasional noise points is just to keep them in your classified dataset and even in your dataset after running lasheight.

you just ignore them when running lascanopy.

instead of taking all the points into account when calculating your metrics on cell level you use "-b_upper 99" for exempel: this leaves out the upper 1% of the points.

This is especially usefull for ignoring noise points right above the canopy. the one noisy point at 500 meter can easily be spotted, but close to canopy noise points are harder to see.

Floris