Gridding Lidar

Lidar surveys create point clouds, essentially random collections of 3D points.  While data analysis directly with the point cloud is increasing, conversion to regular grids generally greatly decresases the data storage requirements, and allows the use of standard raster GIS tools.

 

Prior to gridding, the user must select the desired final surface or surfaces, generally DTM or DSM.

High and low noise can be flagged, so it is not used, or removed from the data set.

The point cloud can be classified, to at least identify the ground returns, and only these will be used for a DTM.

For a DSM, all points can be used, or the electrical power lines, and vehicles could be removed (neither of these are routinely included in the point clouds distributed by national mapping agencies).

There are two general methods for creating the grids:

Circled anomalies from the triangulation in a DSM from Denmark.  These result from the lack of water reflections in the castle moat.
Two Non vegetation surface grids.  The 1 m grid has a number of anomalies, because the point density of the lidar survey did not reliably deliver a point on the ground in every grid cell, and has a number of spikes.

Last revision 11/23/2017