Create Grid from Point Clouds

Tab on LIDAR point cloud analysis form.  Creates a new grid or grids that matches the DEM covering the map.  Some options require you to have or create a  DTM

 

Grid size (m)

Auto fill holes: remove small voids

Force UTM zone: if no zone is set, it will use the zone of the currernt map.  You should only change if you want to use an adjacent UTM to match other data.

Word densities: by default these will be stored in bytes (max 255); set this if you need up to 65K points.

 

Elevations

  • Ceiling + floor grids: this will have the highest and lower return height in the the pixel.  This only works well if there are multiple returns for every cell.  If you create them both at the same time, it will be much faster than creating both sequentially.
  • Distance Above/Below DEM: height in m for any points in the point cloud that lie above or below the DEM.  The DEM should be a DTM. Uses zcrit on the Tools tab, and the DEM Z choice.
  • Mean/Std: the mean height above the DTM and standard deviation for all returns in the pixel
  • DTM from ground classified points:  this uses only the points classified as ground, so its quality depends on the classification job.
  • Low ground points x-y-z: this creates a database with the X,Y, and Z coordinates of the lowest point within the grid box that has been classified as ground.  This is intended to use as input for triangulation creation of a DTM, with a reduced resolution to better capture the local relief and not every small deviation which might be better viewed as noise.
  • Low points x-y-z: Same as the previous option, but no prior need for classification.  It will include buildings, if the area has any.

Point count/density

  • Point count:
  • By Class: counts in each pixel for 5 classifications; depends on the quality of the classification.
  • Air points above DTM: these are from vegetation, power lines or something else above the ground (the final return in the pulse).  Number of points above the DTM + Zcrit. This will be a minimum estimate, since a pulse with a single return might not have reached the ground.
  • Non last return from LAS record: record has the return number, and the total number of returns from the pulse, so if these are not equal, it is an air point
  • Ground points above DTM.  Number of points within Zcrit of the DEM elevation.
  • First: first return from the LAS record
  • Second return: this shows the distribution of pulses with mutliple returns, positioned at the location of the second return.  The first and following returns could be at a different grid location, depending on the grid spacing and the scan angle of the pulse.
  • Single: pulses with a single return.  These will be in non-vegetated areas.

Other grids

Fusion DTM from TIN

  • Creates a DTM to cover the current map area.
  • Three steps:
    • Create single temporary LAS file , with all points on the current map, with the current filter to select the points to use. 
    • fusion\tinsurfacecreate:
    • fusion\dtm2tif to create a TIFF from the native fusion DEM format
    • GDAL_translateUTM to put the projection into the TIFF, which only has a world file

Filter the LAS data first by classification code (Stats tab, Split by class) if the data has a good classification applied.

Points density, building category only.  Zero values removed by marking as missing.  The colored pixels show points per square meter, classified  in the LAS data.  This category generally appears to be fairly accurate. Almost all points will be on roofs.
Points density, medium vegetation category only.  Zero values removed by marking as missing.  The colored pixels show points per square meter, classified in the LAS data.  This category appears to be fairly accurate for the high density points, but a number of the lowest density points are actually buildings.

Last revision 2/5/2018