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If I normalise a lidar dataset I am (according to my thinking) simply subtracting the first return heights from the ground heights. Thus the resulting dataset will only contains the height above ground and a mountainous region would then appear flat when visualised as a cross section profile. Is this correct?

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  • I'd argue that this question is different from the linked duplicate since it asks a different question, i.e. not how to normalize but rather whether the ground surface is flat in a normalized dataset. Commented May 25, 2018 at 12:52

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This is exactly what a white top-hat transform does. This is a simple mathematical morphology operator that involves differencing the original point elevations from the elevations derived from an erosion operation (minimum filter) on the point cloud, followed by a dilation operation (maximum filter). The following is an example of a point cloud for a mountainous area and the subsequent white top-hat transform on the same data:

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Notice that the resulting surface is essentially flat, with elevations associated with the height of points above their respective local minima (i.e. the ground surface). This is also apparent in any profile extracted from their respective DEMs:

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The white top-hat transform can be performed on a LAS point cloud using the LidarTophatTransform tool within the open-source WhiteboxTools geospatial analysis platform. I believe that this is how the lasheight tool of LASTools also works.

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  • In my version of WhiteBox (current) the tool LidarTophatTransform is not there. I have version 3.4 Montreal (3.4.0) Released 2017 Commented May 25, 2018 at 9:08
  • @RobertBuckley Ah, I'm afraid that you are confusing WhiteboxTools and Whitebox GAT...two different products with confusingly similar names and that is my fault (if I could go back, I would have named WhiteboxTools something completely different). Anyhow, you need to download WhiteboxTools v.0.7 from here uoguelph.ca/~hydrogeo/WhiteboxTools/index.html Commented May 25, 2018 at 12:10

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