Laser Scanning Based Growth Analysis of
Plants as a new Challenge for Deformation
Monitoring
JISDM Vienna
30.3. – 1.4.2016
Jan Dupuis
Christoph Holst & Heiner Kuhlmann
Institute of
Geodesy and Geoinformation
Motivation
Relevance of agriculture and plant breeding
decreasing
productive
land
increasing
population
climate
change
spread of
plant
diseases
amount of
yield
distribution
of insects
→ breeding high productive crops
→ qualifying new genotype  measuring the phenotype
Growth Analysis of Plants
Jan Dupuis
31.03.2016
Folie 2
Motivation
Phenotypic parameters using laser scanners
volume
leaf
area
3D point cloud
stem
height &
volume
Growth Analysis of Plants
Jan Dupuis
31.03.2016
Folie 3
Motivation
Where is the linkage to deformation monitoring?
Deformation monitoring is …
• “…the metrological registration of the geometric
current state of an object, and its comparison to the
state in the past …
• … and to analyse them in relation to the cause of the
changes.” (Kuhlmann et al. 2014)
– system theory  multiple input multiple output- system
input acting
forces
Growth Analysis of Plants
object transfer
function
Jan Dupuis
output
measurements
31.03.2016
Folie 4
Motivation
Where is the linkage to deformation monitoring?
Plant growth analysis:
• geometric current/past state
– leaf area, stem height, plant volume, …
• environmental causes
– water supply, nutrients, climate, …
– insects, viruses, bacteria, fungi, …
– competition with neighbor plants or weeds, …
environment
+ genotype
Growth Analysis of Plants
plant growth
Jan Dupuis
phenotypic
parameters
31.03.2016
Folie 5
Motivation
Plant as a deformation object
• plant growth combines
– rigid body movements and
– changes of shape and
dimension
Movements and deformations
are large compared to the object
size!
Growth Analysis of Plants
Jan Dupuis
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Outline
1. Measurement process and difficulties
2. Mesh-based derivation of the leaf area
3. Approximation-based approach
4. Conclusion
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Jan Dupuis
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Measurement system
• measuring volume:
Ø 2.8m (spherical)
• laser wavelength:
660nm
• scan rate:
458’400 points/sec
• spatial resolution:
~14µm
• 3D point accuracy:
45µm (mpe)
Perceptron, Inc.
measuring arm + laser line scanner
• highest flexibility
 high resolved and accurate
point cloud
Growth Analysis of Plants
Jan Dupuis
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Scanning leaves with lasers
Three major difficulties regarding the object:
1. complexity of plant structure
2. movements of the plant during the
measurement
3. interaction of laser beam with the plant
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Complexity of plant structure
• completeness of point cloud
– overlapping of leaves
– occlusion of stem parts
• what is the object ?
– e.g. small hairs (trichomes)
http://footage.framepool.com/shotimg/316145122-haerchen-tomate-pflanzesetzling-knospe.jpg
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Movements of the plant during the measurement
• small high frequency movements
– flow of air
– sensor movement
→ higher measuring noise
• large low frequency movements
– plant tropism: proper motions
→ multiple surface layers
0.000
0.218
0.473
0.727
0.855
local noise [mm]
Growth Analysis of Plants
Jan Dupuis
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Interaction of plant and laser beam
red laser
local standard deviation
• laser penetrates the leaf surface
– absorption of chlorophyll
– lower intensity  higher noise
• systematic deviations
0.065 mm
0.032 mm
– point cloud ≠ plant surface
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Scanning process
Hand-operated measuring system
• constant point-to-point distance within one scanline
~ 14µm spatial resolution
• irregular distance between two scanlines
– operator moving speed
+ higher noise and plant movement
• irregular point distribution
• point-to-point distance is small
compared to the measurement
noise
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Outline
1. Measurement process and difficulties
2. Mesh-based derivation of the leaf area
3. Approximation-based approach
4. Conclusion
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Data analysis
Common way of leaf area calculation
Delauneytriangulation
point cloud
separation of
single leaves
• software based data processing
– interpolation
! no accessible accuracy analysis !
Leaf Nr. 3
Leaf Nr. 4
Leaf Nr. 5
Leaf Nr. 6
2500
2000
1500
1000
500
0
0
2
4
6
8
10 12 14 16 18 20
Paulus et al. (2014)
• mesh-based area calculation
Leafarea in mm²
3000
Day of measurement
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Problem: point distribution + noise
measured
data points
real surface
2D interpolation
Interpolating raw point clouds:
 leaf area is always too large !
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Create a regular point distribution
• create a regular point
distribution
– point-to-point distance > noise
• eliminates a subset of points
• remaining points equal raw data
points
thinning
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Theoretical impact of thinning
measured
data points
real surface
2D interpolation
increasing thinning level
Larger point-to-point distance 
less triangles
 The larger the thinning level,
the smaller the derived area.
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Mesh-based leaf area
raw
0.2mm
0.4mm
0.6mm
• decreasing leaf area for lager
thinning
– differences between 21% - 62%
• decreasing trend is not constant
High uncertainties for leaf
area derivation !
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Derived absolute leaf growth
• great differences between the
different thinning levels
Absolute growth for different
thinning levels
– 26% up to 379%
• sometimes change of sign for
different thinning levels
No reliable derivation of
plant growth!
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Outline
1. Measurement process and difficulties
2. Mesh-based derivation of the leaf area
3. Approximation-based approach
4. Conclusion
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Approximation-based area calculation
B-spline approximation
• projection on a planar grid
– equidistant knot points Pi,j
• using cubic basis functions
• extraction of boundary points via
alpha shape approach
• triangulation of adjusted surface
points
 surface area
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Approximation-based leaf area calculation
• smaller differences between
thinning levels
higher precision
• spline area is smaller than the
meshed-based area
thinning
level
mesh-based
[mm²]
approx.-based
[mm²]
raw data
0.1 mm
0.2 mm
0.3 mm
0.4 mm
0.5 mm
0.6 mm
0.7 mm
0.8 mm
range
range/avg.
710,727
729,872
648,709
613,970
592,005
581,631
574,069
567,416
578,672
151,200
24,3%
551,269
549,898
547,888
545,136
542,049
537,482
537,974
532,309
531,608
19,661
3,6%
[mm]
accuracy ?
Comparison of mesh- and
approximation-based
leaf area
Higher precision !
Accuracy ?
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Outline
1. Measurement process and difficulties
2. Mesh-based derivation of the leaf area
3. Approximation-based approach
4. Conclusion
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Conclusion
Plant growth analysis is a new challenge for deformation
monitoring!
• high complex dynamic deformation model
• large deformations compared to object size
– rigid body movement and deformations
• high measuring noise compared to
– point-to-point distance
– object size
• commonly unfavorable data analysis
• high scientific relevance
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Thanks for your attention!
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