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Josef Reitberger (FHM)Peter Krzystek (FHM)
Uwe Stilla (TUM)
„Combined TreeSegmentation and Stem
Detection using FullWaveform Lidar Data“
2
COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Outline
MotivationFull waveform data
AcquisitionDecomposition
Segmentation of tree crownsDetection of tree stemsResults of segmentation and stem detectionAnalysis of full waveform data
ExperimentsResults
Conclusions and future work
3
COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
MotivationSegmentation
Basis for the derivation of forest parameters on single tree levelState of the art: Use of a CHM => The information below thesurface is ignoredProblem: Limited detection rate in lower tree layers
Stem detectionBasic idea: Use of information below the canopy surfaceStem reflections are registered by full waveform laser scanningCan tree detection be improved by using stem reflections?
Do stem reflections have specific characteristics? Compared to ground and crown reflectionsWith respect to pulse width and intensity derived by waveformdecomposition
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Acquisition of full waveform data (1)
Flight in Mai 2006 (Riegl LMS-Q560)
Scan angle: 0° - 22.5°Wavelength: 1550 nmPulse rate: 45 kHzPulse length: 4 nsBeam divergence: 0.5 mradFlying height: 400 m25 points/m2
Full waveform data• Variable length• Sample rate: 15 cm• Recording of the emitted pulse
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Bergmischwald
TestgebieteBergfichtenwald
Aufichtenwald
Test site
Waveformdata
© Bavarian Forest National Park
Mixed mountain forest
Sub alpine spruce forest
Alluvial spruce forest
Acquisition of full waveform data (2)
Bavarian Forest National Park
Reference areas
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
sX
X
Y
Z
Y
sr
Decomposition of full waveform data
Waveform model: Sum of Gaussian functions
W2 I2
3X
2X
1X
4X
5X
3D coordinates of the reflections:
),1()( pssmsm NmrttXX =−+=
Width and intensity of the return pulse as attributes:
mmW σ⋅= 2mmm AI ⋅⋅⋅= σπ2
Point classes: first, middle, last, single
first
last
middle
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Segmentation of tree crowns (1)
Derivation of a CHM by least squares surface reconstruction
Interpolated CHM with local maxima (=tree positions)All points Highest points
Extraction of the highest points
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Segmentation of tree crowns (2)
Delineation of tree crowns with watershed algorithm
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Segmentation of tree crowns (3)
Problem: Sometimes several trees in one segment, which cannot beseparated by only using the CHM
Reference trees
Local maximum
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Detection of tree stems (1)
Separation of points between ground and begin of crownHierarchical clustering by using the horizontal distances between theseparated points
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Detection of tree stems (2)
Fitting of lines using the „Ransac“ algorithm to eliminate outliers
Additional rules: Angle of inclination < 7°
Minimum number of 3 pointsPositions found by stem
detection
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Results of segmentation and stem detection
Evaluation of 11 reference areas (2.6 ha, 1012 trees) Overall detection rate of tree crown segmentation: 49 %Improvement of detection rate by stem detection
Very different for the individual areas
Works best at sparse understorey and a large crown base height
Best reference area: 15 %
Improvement in the intermediate layer for all areas: 8 %
Improvement including all layers for all areas: 4 %
Improvement of tree position: 24 cm (= 21 %)
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Analysis of full waveform data
Do the stem reflections have specific characteristics?
Pulse widthIntensity
Crown points
Stem points
Ground points
Angle of incidence
β
s
(calibrated w.r.t. emitted signal)(calibrated w.r.t. emitted signal and run length s)
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Analysis: Stem, crown and ground
Average pulse width dependingon angle of incidence
Single + last points
Average intensity dependingon angle of incidence
Single points
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Analysis: Different tree species (crown)
Single points
Average pulse width dependingon angle of incidence
Single + first + middle + last points
Average intensity depending on angle of incidence
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Analysis: Different tree species (stem)
Single + first + middle + last points
Average pulse width dependingon angle of incidence
Single points
Average intensity depending on angle of incidence
17
COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Results of waveform analysis
The intensity and pulse width of stem points depend on theangle of incidence
Ground points differ considerably from stem points and crownpoints
Crown points and ground points show no angle dependence
The mean intensity of stem points differs from crown points foran incidence angle larger than 10°
Crown points of coniferous trees differ from crown points of deciduous trees
The mean intensity of stem points differs considerably for thetwo tree species
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Conclusions and future workConclusions
The detection rate and position of single trees can be improvedby stem detectionThe intensity and pulse width can be used for forestclassifications if the order of the reflections in the waveforms isconsidered
Future work: 3D segmentation by using waveform information
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COMBINED TREE SEGMENTATION AND STEM DETECTION USING FULL WAVEFORM LIDAR DATA
Reitberger, Krzystek, Stilla September 2007
Thank youfor your
attention!
Acknowledgement: We thank Dr. Marco Heurich from the Bavarian Forest National Park for the productive contributions und for giving us the opportunity to use the remotesensing test sites.