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Advanced point cloud processing such as Height above Ground

Status: Delivered
by Moderator on ‎08-21-2017 05:12 AM - last edited on ‎08-29-2017 01:02 PM by Technical Evangelist

This makes it easier to create flooding, building height, and forest canopy models based on point cloud data.


Take a regular point cloud, with heights measured as height above mean sea level, and subtract a second surface representing the ground surface. The result would represent height above ground level (e.g. heights of trees, buildings, etc).


This would enable building Spatial Models to, for example,


  1. Acquire point cloud
  2. Classify point cloud to identify tall vegetation (i.e. trees) and ground (bare earth) points
  3. Interpolate ground points to continuous raster ground surface
  4. Subtract ground surface from all points
  5. Use Zonal operators to attribute forest stand polygons with average tree height per polygon
  6. Manager determines which stands are ready for harvest


Status: Delivered


Delivered as part of ERDAS IMAGINE 2018, released March 1st, 2018

by Technical Evangelist
on ‎08-29-2017 01:00 PM
Status changed to: Targeted for an upcoming release
on ‎09-27-2017 02:09 AM

More/higher quality point cloud operators would be very welcome. The current classification is poor compared to LASTools, which also has other useful operators such as point density and noise removal. 

by Technical Evangelist
on ‎01-05-2018 07:57 AM

It's a good job that you can plug LASTools into Spatial Modeler!

by Technical Evangelist
on ‎03-01-2018 10:52 AM
Status changed to: Delivered


Delivered as part of ERDAS IMAGINE 2018, released March 1st, 2018