Ground classification

Arttu Soininen

Ground classification

• Iterative process which builds a

triangulated model and molds it upwards
as long as it finds new points matching
iteration parameters

• Location becomes ground if the

application finds a smooth route to the top

• Location becomes ground if you can drive

onto it

Parameters

Source class

Destination class

Initial point selection

Main parameter controling
how many points will be
classified

Initial point logic

• No building covers an area 80m * 80m size
• Lowest point in any such rectangle is ground

Terrain angle

• Maximum terrain slope
• Use 88-90 degrees if man made

features present

• Estimate maximum slope (and add

10-15) if all natural terrain

Iteration angle

• Each potential point is compared

against triangle it is inside

• Iteration angle is angle between triangle

plane and a line connecting potential
point with the closest triangle vertex

Angle

D

is

ta

n

ce

Iteration distance

• Iteration distance is distance from point

to triangle plane

• Safe guard preventing the routine from

classifying large, single floor buildings

Angle

D

is

ta

n

ce

Reduce iteration angle

• Reduces eagerness to classify points

inside small triangles

• Application is more eager to classify

when there is a large hole in the ground

• Application is less eager to classify

when there is a small hole in the ground

Edge

leng

th

Iteration angle inside small triangles
approaches zero when longest edge
is shorter than Edge length setting

Classification hints

• Classify too few points to ground

rather than too many

– It is easy to find and fix holes in the

ground

– Finding and fixing low vegetation points

which have become ground is difficult

Classification hints

• You may preclassify difficult places

before running ground classification

– Classify manually if there are a few very

large buildings preventing from using a
reasonable value for maximum building
size (60 - 100m)

– Classify tops of steepest hills