LiDAR : Classifying Points
Typical Classes
1 – Unclassified
2 – Ground Solid
3 – Low Vegetation
4 – Medium Vegetation
5 – High Vegetation
6 – Building
7 – Low Point (noise)
8 – Model Keypoints (mass point)
9 – Water
If the point class you want is not already defined…DEFINE IT!
Don’t forget to save when done!

View Classification Statistics
To see how many points are in each classification (for interest)


Open the Classify Points Macro Tool in Terrascan Menu



Point Classification Settings
The settings you use will depend on what you are looking for from the data i.e DEM, canopy top, tree trunks, buildings etc etc etc. Below are a bunch of examples of settings but these may not be ideal for your specific use. I will try to explain what some of the variations you can set will do. You should classify your points (build your macros) in thefollowing order : default – isolated points – low points – ground – below ground- hgt above ground – building.

Isolate Points
The isolate points macro looks at every point and if it does not have x # of points within a y buffer zone it considers it isolated. i.e if a point doesn’t have at least 3 other points within 3m of it in all directions it will be classified as isolated and put in the low point class which essentially acts as a noise class.

Low Points
The removal of low points is to help the macro determine the ground level. It takes the lowest points in the cloud as the ground. Sometimes anomalous points appear below the ground due to double reflections or errors (i.e if it reflects off of a surface, hits another surface and then goes back to the receiver, the time is increased which results in it appearing below the surface. This takes the average height of all of the points within a buffer zone of the point in question. If the point in question is xm below the average of all of the points in the buffer zone it is considered a low point.

Ground Points
The purpose of this macro is to classify a ground layer to be used as a dem. All future macros will be related the ground layer. Options include
Building Size – if you set it smaller you can see more details.
Terrain Angle – larger is more detail but can create problems (this is essentially related to smoothing of the dem)
Iteration angle – can take this up to 10 or 11 for a high detail survey. Higher angles can add to the noise in the classification. 1.4 is the default and it is often good to start with this value.

Below Ground Points
This removes remaining points below the ground surface.

Height Above Ground Points
These classify from xm-ym above ground as a certain class (often used for low, medium and high vegetation. It is fairly explanatory. It is common to use 0-1, 1-2, 2-200m (requiring you to include this macro 3 different times)

Building Points
Buildings are typically >2m so you will want to run this macro for any class that has a height of >2m above ground. This is very dataset specific so play around with the rules, the minimum building size and the Z-tolerance. Try the default settings first.
For more information follow this case study.
The Final Step
The last thing to do is run your macro. You can do this on either individual blocks or your entire projects. Both of these options are selectable from the Macro–> Run Menu.
If you want to run on loaded points only (recommend for testing macro settings) you should make sure to have a block open under the terrascan –> File –> Open Block menu. Click Open block and select a block in your viewer.
Now select run from loaded points.
If you want to run the macro on the entire dataset. Select to run it on a selected file.
This pops up the menu on the far right. Use settings as shown. Please note that you do not have to select LAS 1.2 but if you leave this option as default it will not save your points.



March 17, 2016 @ 11:04 am
Nice!
July 26, 2016 @ 5:16 am
I want this software. It will use las analysis.
thank you
August 4, 2016 @ 4:12 am
Halo. Thanks you information about classifying Points. and may i ask you something about this? i still confuse about how to determine parameter value of max.building size, terrain angle, iteration angle and iteration distance? thanks before
June 27, 2017 @ 10:31 am
halo, thanks for your post, it’s been so useful for me to learn how to use terrascan, but i’m still confuse about classifying parameter like terrain angle, iteration angle and iteration distance, could you please refer me a book or paper about it? thank you very much
September 27, 2017 @ 6:50 am
Hi Katrina,
You have done a great job, just one question: When I am loading point cloud after setting up the project in power draft and followed all other steps as well, but I can’t see the loaded file in any of the viewer. I have FWD point cloud for an area of 6,000Ha approx, which was delivered to us with the defined projection (UTM 48N) but not classified yet. I have classify ground, mid and high vegetation so that I can extract DTM and detect individual trees along with all tree parameters. Do you think you can help me out in this??
April 7, 2018 @ 4:49 am
hi
i can’t find steps to write a keypoint model macro i need a low density point of my project
June 6, 2018 @ 12:45 pm
Thanks.