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Application of Airborne LiDAR Measurement to Forestry산림분야항공기LiDAR 계측의응용
森林分野への航空機LiDAR計測の応用
Yasumasa HirataForestry and Forest Products Research Institute (FFPRI)
산림종합연구소히라타야스마사
森林総合研究所 平田泰雅
Forestry and Forest Products Research Institute
What parameters are required to measure in forest sector?
• Forest manager– Individual tree information– Stand height (Site quality)– Stand volume
• Forest officer– Stand volume– Stand condition
• Government officer– Total volume– Total carbon stock
Forestry and Forest Products Research Institute
木木
Intensity
First return
Last return
One shot of laser
GPSGPS
IMUIMU
TimeTime
Tim
e
first return
last return
Forest measurement by ALS
• Digital surface model (DSM) is created from first return.
• Digital elevation model (DEM) is created from last return.
• Digital canopy height model (DCHM) =DSM –DEM
• Other information (waveform, penetration rate, etc.) is also used to estimate stand condition.
Forestry and Forest Products Research Institute
What can be measured using ALS?
• Direct measurement– Tree height
– Crown area
– Crown depth
• Estimated parameter– DBH
– Volume
– (Carbon stock)
height
Crown area
DBH
Crown depth
Forestry and Forest Products Research Institute
0
20
40
60
80
0 10 20 30 40 50
0
20
40
60
80
0 10 20 30 40 50
Chamaecyparis obtusa
• Local maximum filter is applied toDCHM to extract individual tree-tops.
• Watershed method or valley-followingmethod is applied to DCHM to extractindividual crowns.
Cryptomeria japonica
Crown area(m2)
DBH
(cm
)胸
高直
径(cm
)
Extraction of tree height, crown area and tree number from DCHM
R2=0.82
R2=0.71Extraction and estimation
Forestry and Forest Products Research InstituteHirata et al. (2009)
Measuement in a Japanese cedar pantation
V (m/sec)
H (m)δ
γ
n (Hz/sec)
F (Hz/sec)
θ
δ
300 m600 m1200 m
24 deg.
25,000 Hz
14 m/sec
1.0 mrad
34 Hz
Measurement Parameters
Lightthinning
Heavythinning
Nothinning
99 trees
111 trees125 trees
118 trees
88 trees
113 trees
0.15ha 0.15ha0.20ha
0.15ha 0.15ha0.20ha
Heavythinning
Lightthinning
Nothinning
50m
50m
30m 30m40m
Plot distribution
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3-D display of DSM and DEM
DSM
DEM
Results of ALS measurement
DCHM
Forestry and Forest Products Research Institute
3-D model
Hirata (2005)
00 40
40
H ALS(m)H
grou
nd (m
)
H ground = 1.009 * H ALS – 0.59r2 = 0.85
Tree height from DCHM
Extraction of individual trees
thinning operation
number of standing trees
number of extractive trees
extractive rate (%)
heavy (0.3 ha) 142 136 95.8
light (0.4 ha) 245 212 86.5
no (0.3 ha) 270 203 75.2
Total(1.0 ha) 657 551 83.9
Tree number and height from DCHM
Forestry and Forest Products Research InstituteHirata (2005)
Hf Hl Hl HfHf Hl Hl Hf
Factors of underestimation and overestimation of tree height in mountainous terrain
Forestry and Forest Products Research Institute
• Trees usually incline to one side in mountainous area.• 70 % of trees inclined to the lower side of slope.• Average of (H l – H f) was 0.2 meter.
Hirata (2004)
Relationship between actual tree height and measured tree height (slope=30º)
Valley sideHill sideOn contour
Inclination of standing tree (degree)
Forestry and Forest Products Research InstituteHirata (2007)
25 points/m22 – 3 points/m2
In the case of low sampling density, some tree-tops are not involved by any footprints.
In the case of high sampling density, each tree-top is involved by one of footprints.
crown
footprint
Sampling density
Forestry and Forest Products Research InstituteHirata (2005)
sampling density = 22.53 sampling density = 11.28
sampling density = 5.64 sampling density = 2.82 sampling density = 1.41
Sampling density
sampling density = 0.35sampling density = 0.71
DCM derived from different sampling density
sampling density = 22.53 sampling density = 11.28
sampling density = 5.64 sampling density = 2.82 sampling density = 1.41
sampling density = 0.35sampling density = 0.71
As sampling density runs lower, extractive tree-tops decrease.
Simulation of sampling density
Data size Mean sampling density (points/m2)
S. D. (points/m2)
Original 22.53 12.43
1/2 11.28 6.37
1/4 5.64 3.48
1/8 2.82 2.06
1/16 1.41 1.31
1/32 0.71 0.86
1/64 0.35 0.59
Generating dataset of different sampling density
0
10
20
30
40
50
60
70
80
90
100
0.0 5.0 10.0 15.0 20.0 25.0
25cm
50cm
1m
2m
Rate of involving more than 1 pulse data in every mesh size
sampling density (points/m2)
(%)
Forestry and Forest Products Research InstituteHirata (2005)
0
100
200
300
400
500
600
0 5 10 15 20 25
0.25m
0.5m
1mNum
ber
of
ext
ractive
tre
es
Sampling density of laser beams (points/m2)
mesh size
The relationship between sampling density and number of extractive trees
• In case of the sampling density of more than 5 points/m2, the rate of extractive trees with 1 meter and 0.5 meter mesh sizes against 0.25 meter mesh size were about 60 % and 90 % respectively.
• The rate of extraction of treetops from DCM declined suddenly in case the sampling density was below 3 - 5 points/m2.
Forestry and Forest Products Research InstituteHirata (2005)
30.0
30.5
31.0
31.5
32.0
0 5 10 15 20 25
0.25m
0.5m
1m
Sampling density of laser beams (points/m2)
Mean
tre
e h
eig
ht
of
ext
ractive
tre
es
(m)
mesh size
The relationship between sampling density and mean height of extractive trees in each mesh size
• The mean tree height in the same sampling density is smallest for the 0.25-meter mesh size.
• The difference between mean tree height by mesh size was 0.4 - 0.6 meter.
• The estimated height with low sampling density was underestimated.
Forestry and Forest Products Research InstituteHirata (2005)
truetrue
largerfootprint
largerfootprint
smallerfootprint
smallerfootprint
Difference of DEM and DSM by footprint size
Surface elevation
true point> smaller footprint> larger footprint
Ground elevation
larger footprint>= smaller footprint>= true point
In mountainous area
Forestry and Forest Products Research InstituteHirata (2004)
Coverage of canopy surface by footprint size
footprint = 0.3 m (sampling density = 24.8 /m2)
footprint = 0.6 m(sampling density = 10.1 /m2) footprint = 1.2 m(sampling density = 7.5 /m2)
DCM
Last return of ALS by footprint size
footprint = 0.3 m footprint = 1.2 mfootprint = 0.6 m
Forestry and Forest Products Research Institute
DCM derived from different footprint size
footprint = 0.3 m footprint = 1.2 mfootprint = 0.6 m
DCM0.3 DCM0.6 DCM1.2
Forestry and Forest Products Research Institute
0
100
200
300
400
500
-10 -8 -6 -4 -2 0 2 4 6 8 10
Difference (m)
Are
a (m
2)
Subtraction of DCHM by footprint size of 0.3 meter from DCHM by footprint size of 1.2 meters
DCHM1.2 – DCHM0.3
Forestry and Forest Products Research InstituteHirata (2004)
0
200
400
600
800
1000
-10 -8 -6 -4 -2 0 2 4 6 8 10
Difference (m)
Are
a (m
2)
Subtraction of DCHM by footprint size of 0.3 meter from DCHM by footprint size of 0.6 meter
DCHM0.6 – DCHM0.3
Forestry and Forest Products Research InstituteHirata (2004)
Penetration of laser through canopy
Forestry and Forest Products Research Institute
Penetration of laser in a deciduous forest
more than 50 species- Quercus serrata Murray- Fagus japonica Maxim.- Fagus crenata Blume
Forestry and Forest Products Research Institute
AcquisitionDate
Flight Speed Flight Altitude
Beam divergence
Pulse Frequency
Sampling Density
24/08/2001 13.9 m/sec 250 m 1.0 mrad 25,000 Hz 25.0 pts/m2
14/04/2002 13.9 m/sec 300 m 1.0 mrad 25,000 Hz 31.9 pts/m2
in the leafless seasonin the full‐leaf season
0
100
%
total penetration rate 20% total transmittance 69%
Penetration in different seasons
Forestry and Forest Products Research Institute
in the leafless seasonin the full‐leaf season
Last return of laser in different seasons
Forestry and Forest Products Research Institute
in the leafless seasonin the full‐leaf season
First return of laser in different seasons
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in the leafless seasonin the full‐leaf season
First and last return in cross section in different seasons
Forestry and Forest Products Research Institute
in the leafless seasonin the full‐leaf season
Last return in cross section in different seasons
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Evaluation of different levels of thinning
Forestry and Forest Products Research InstituteHirata et al. (2009)
Relative frequency distributions of the heights above the ground where laser pulses reached
Forestry and Forest Products Research InstituteHirata et al. (2009)
Thinning and penetration rate
Forestry and Forest Products Research InstituteHirata et al. (2009)
Total basal area of remaining trees and penetration rate
Forestry and Forest Products Research InstituteHirata et al. (2009)
Forestry and Forest Products Research Institute
Stnand parameter by ALS
Hirata et al. (2008)
Stand density from DCHM
Forestry and Forest Products Research InstituteHirata et al. (2008)
Mean tree height from DCHM
Forestry and Forest Products Research InstituteHirata et al. (2008)
Stand volume by ALS
Forestry and Forest Products Research InstituteHirata et al. (2008)
Concluding remarks
• What parameters are required to measure in forest sector?– Depend on users and purposes
• Measurement by ALS effects on– Sampling density– Footprint size– Stand density– Species– Topography– Inclination
• Waveform laser scanning• Cost and archieve for the
expansion of use
Forestry and Forest Products Research Institute
References of this presentation• Hirata, Y., 2004. The effects of footprint size and sampling density of
airborne laser scanning to extract individual trees in mountainous terrain. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. XXXVI-8/W2, 102-107.
• Hirata, Y., 2005. Influence of transmittance and sampling density of laser beams in forest measurement of a Cryptomeria japonica stand with an airborne laser scanner (in Japanese with English abstract). Japanese Journal of Forest Planning 39, 81-95.
• Hirata, Y., 2007 Forest Measurement with Airborne Laser Scanner and its Trend (in Japanese). Japanese Journal of Forest Planning 41(1), 1-12.
• Hirata, Y., Furuya, N., Suzuki, M., Yamamoto, H., 2008. Estimation of stand attributes in Cryptomeria japonica and Chamaecyparis obtusa stands from single tree detection using small-footprint airborne LiDAR data. Journal of Forest Planning 13, 303-309.
• Hirata, Y., Furuya, N., Suzuki, M., Yamamoto, H., 2009. Airborne laser scanning in forest management: individual tree identification and laser pulse penetration in a stand with different levels of thinning. Forest Ecology and Management 258(5), 752-760.
Thank you for your attention!
Forestry and Forest Products Research Institute
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