Laser Scanning Based Growth Analysis of Plants as a new Challenge for Deformation Monitoring
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1 Laser Scanning Based Growth Analysis of Plants as a new Challenge for Deformation Monitoring JISDM Vienna Christoph Holst & Heiner Kuhlmann Institute of Geodesy and Geoinformation
2 Motivation Relevance of agriculture and plant breeding increasing population decreasing productive land spread of plant diseases climate change amount of yield distribution of insects breeding high productive crops qualifying new genotype measuring the phenotype Folie 2
3 Motivation Phenotypic parameters using laser scanners volume 3D point cloud leaf area stem height & volume Folie 3
4 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 object transfer function output measurements Folie 4
5 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 plant growth phenotypic parameters Folie 5
6 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! Folie 6
7 Outline 1. Measurement process and difficulties 2. Mesh-based derivation of the leaf area 3. Approximation-based approach 4. Conclusion Folie 7
8 Measurement system Perceptron, Inc. measuring arm + laser line scanner measuring volume: laser wavelength: scan rate: spatial resolution: 3D point accuracy: Ø 2.8m (spherical) 660nm points/sec ~14µm 45µm (mpe) highest flexibility high resolved and accurate point cloud Folie 8
9 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 Folie 9
10 Complexity of plant structure completeness of point cloud overlapping of leaves occlusion of stem parts what is the object? e.g. small hairs (trichomes) Folie 10
11 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 local noise [mm] Folie 11
12 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 point cloud plant surface mm mm Folie 12
13 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 Folie 13
14 Outline 1. Measurement process and difficulties 2. Mesh-based derivation of the leaf area 3. Approximation-based approach 4. Conclusion Folie 14
15 Leafarea in mm² Paulus et al. (2014) Data analysis Common way of leaf area calculation point cloud Delauneytriangulation separation of single leaves software based data processing mesh-based area calculation interpolation Leaf Nr. 3 Leaf Nr. 4 Leaf Nr. 5 Leaf Nr ! no accessible accuracy analysis! Day of measurement Folie 15
16 Problem: point distribution + noise measured data points real surface 2D interpolation Interpolating raw point clouds: leaf area is always too large! Folie 16
17 Create a regular point distribution thinning create a regular point distribution point-to-point distance > noise eliminates a subset of points remaining points equal raw data points Folie 17
18 Theoretical impact of thinning measured data points real surface 2D interpolation Larger point-to-point distance less triangles The larger the thinning level, the smaller the derived area. increasing thinning level Folie 18
19 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! Folie 19
20 Derived absolute leaf growth great differences between the different thinning levels 26% up to 379% Absolute growth for different thinning levels sometimes change of sign for different thinning levels No reliable derivation of plant growth! Folie 20
21 Outline 1. Measurement process and difficulties 2. Mesh-based derivation of the leaf area 3. Approximation-based approach 4. Conclusion Folie 21
22 Approximation-based area calculation B-spline approximation projection on a planar grid equidistant knot points P i,j using cubic basis functions extraction of boundary points via alpha shape approach triangulation of adjusted surface points surface area Folie 22
23 [mm] Approximation-based leaf area calculation smaller differences between thinning levels higher precision spline area is smaller than the meshed-based area accuracy? thinning level Comparison of mesh- and approximation-based leaf area mesh-based [mm²] approx.-based [mm²] raw data 710, , mm 729, , mm 648, , mm 613, , mm 592, , mm 581, , mm 574, , mm 567, , mm 578, ,608 range 151,200 19,661 range/avg. 24,3% 3,6% Higher precision! Accuracy? Folie 23
24 Outline 1. Measurement process and difficulties 2. Mesh-based derivation of the leaf area 3. Approximation-based approach 4. Conclusion Folie 24
25 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 Folie 25
26 Thanks for your attention! Folie 26
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