The Municipality of Täby aims to populate 3D city models with trees, but without known tree points and without tree classifications in the LIDAR data, this is difficult. Unless you use FME, of course.

1. Modelling Trees with FME

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Jonas Nelson
GIS Coordinator
Municipality of Täby, Sweden

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15 km north of Stockholm
70 km2
75 000 inhabitants

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”The world needs trees.
This goes for 3DCMs and
digital twins as well.”

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Agenda
● What do we want to achieve?
● What do we have to work with?
● How do we use FME?

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Central Täby
Looks so much more attractive with trees!

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What do we have to work with?
Being a local government, we have limited economic resources.
▪ Hi-res LIDAR point cloud – unfortunately without vegetation class.
▪ Buildings – both as 2D footprints and 3D-models (made partly with FME).
▪ Raster orthophotos (for draping).
▪ FME Desktop
▪ SketchUp
The point cloud class ”Unclassified” contains trees, but also cars,
lamp posts, balconies, construction cranes, road signs, etc.

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How do we use FME?
▪ Find possible tree areas
▪ Position, height, diameter
▪ Replace with a 3D model
Point cloud without
vegetation class
The result, combined with
3D buildings and an
orthophoto, is
something amazing!

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FME will help us with three things
1. Which of the points in the point cloud might represent
trees?
2. Where are the individual trees?
Get their position, height, and diameter.
3. Replace the trees with scaled 3D tree models in SketchUp.

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1. Which parts of the point cloud might represent trees?

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1. a) Read the Point Cloud

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1. b) Clean the Point Cloud

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1. c) Normalise heights and
filter by elevation

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1. d) Use only points with
at least 2 returns

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1. e) Turn the remaining
point cloud into areas
Note the long and narrow areas.
These are signs above roads,
beams for power lines and bridges,
etc.

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1. f) Delete long and
narrow areas

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1. g) Keep the most
circular areas
Large areas are chopped into ”tree-sized” parts.
Circularity is calculated.
We do lose some trees in this part of the
process, but the overall gain is higher.

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1. h) Clip the original point cloud, using
the computed tree areas
We now have a point cloud representing trees
only (almost).
Everything up to this would not have been
necessary, had we had a point cloud with a class
for “High Vegetation”.

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2. Find individual trees and extract position, height and diameter

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2. a) Create a 1x1 m grid of stacked
points, by rounding
…and sort to
find the
highest Z in
each stack.

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2. b) Compare each stack’s Z_max with it’s
neighbours, to find local max.
The size of this search buffer is important.
Too large and we might miss small trees close to
larger ones.
Too small and every branch might turn into a
local treetop.
Here, we search within 2.5 m, covering the two
closest candidates in every direction.

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2. c) Local maximas =
probable tree top
Note: Trees might be leaning, and they might have
more than one local max (treetop).
This model does not aim to be perfect.

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2. d) Create Voronoi polygons
around each treetop
The Voronoi polygons are limited to 8 m radius
(suitable for our kind of trees, but this could
potentially be another user input parameter).

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2. e) Trim the Voronoi polygons using
the tree areas
This might split a Voronoi polygon in two (or
more) parts. Keep only the one with the treetop,
and only if it is reasonably round in shape.

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2. f) Create Bounding Boxes and move
tree position to center

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2. g) Generate tree diameters
The circle (tree diameter) are computed as the
mean of the bounding box’ length and width.
We now have everything we need for our
trees to be modelled;
Position, Height and Diameter

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From possible tree areas to individual tree objects

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3. Replace the tree position with a 3D model and scale it

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3. a) Read suitable 3D models of trees
I use simple models from SketchUp 3D
Warehouse, and also randomize between
tree different models.

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3. b) The final result, visualised in SketchUp

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Reality check
Google Earth
LoD2 + trees, SketchUp

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Trees are a vital part of a
3D City Model.
FME can help you create
them.

33. Thank You!
jonas.nelson@taby.se
My participation was made possible thanks to

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