Short Paper

J. Agric. Meteorol. (農業気象) 66 (2): 111-116, 2010

Estimation of coniferous standing tree volume using airborne LiDAR
and passive optical remote sensing
Yohei NAKAI, Fumiki HOSOI, and Kenji OMASAThe University of Tokyo, Graduate School of Agricultural and Life Sciences
1–1–1 Yayoi, Bunkyo, Tokyo 113–8657, Japan
Abstract
In this study, we conﬁrmed the utility of airborne LiDAR and passive optical remote sensing techniques
for estimating the standing tree volume of two coniferous trees, 28 Japanese red pine and 13 Japanesecedar trees respectively. Airborne 3-D LiDAR data and aerial photographs provided the respective heightand crown area for each of the selected trees. Subsequently, we examined the relationships between 1)
LiDAR-derived tree height and Field-based stem volume and 2) the crown area obtained from aerial
photograph and the ﬁeld-based stem volume. In addition, we made a multiplicative equation composedof both tree height and crown area to predict the stem volume, and examined its accuracy by comparing
the predicted standing tree volume with the ﬁeld-based volume. Consequently, stronger correlations wereobserved between the LiDAR-derived tree height and stem volume in both species, while those between
the crown area obtained from aerial photographs and the stem volume were weaker in both species. At
the multiplicative equation, R2 and SE of the stem volume were 0.90 and 0.046 m3 for the Japanese redpine, and 0.83 and 0.025 m3 for the Japanese cedar respectively, which represented a better result thanusing tree height or crown area alone, especially for the Japanese cedar. This shows the effectivenessof the combination of LiDAR and passive optical sensors in estimating the standing tree volume.
Key words: Airborne LiDAR, Japanese red pine, Passive optical remote sensing, Three-dimensional,
Tree volume.

2007; Takeda et al., 2008). However, their biomass
estimation has been conducted on relatively limited
tree species, and the methods remains insufﬁcient forvarious species. With this in mind, there is a need
to apply their biomass estimation method for othertree species and develop the estimation methods forthe same. In addition, as measurement methods, thecombination of LiDAR and passive optical sensors isconsidered effective.
In this study, we derived the structural parametersof the Japanese red pine (Pinus densiﬂora Siebold ＆Zuccarini) from a combination of various remote sensing techniques, i.e. airborne LiDAR and passive opticalremote sensing, and investigated the effectiveness of theparameters for standing tree volume estimation. Since
there has been little study of efforts to estimate thestanding tree volume of the Japanese red pine by theremote sensing based method to date, this species wasselected in this study. In addition, to compare different

1. Introduction
Accurate estimation of tree volume is vital forconservation of the forest ecosystem and understandingof global climate change (Hobbs and Mooney, 1990;
Omasa and Harasawa, 2003). Although field-based
actual measurements reveal an accurate volume, theirapplication is limited because they are very laborious or
destructive (Husch et al., 1982; Nagumo and Minowa,
1990). Recently therefore, remote sensing techniquessuch as LiDAR and passive optical sensors have beendeveloped as indirect methods capable of efﬁciently
obtaining wide area information. They have also been
applied when estimating forest resources such as treevolume and structural parameters (Nelson et al., 1988;
Omasa et al., 2003, 2008; Næsset et al., 2004; Zheng etal., 2004; Urano and Omasa, 2005; Hosoi and Omasa,Received; March 27, 2009.
Accepted; November 11, 2009.
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J. Agric. Meteorol. (農業気象) 66 (2), 2010
2.4 Estimating the tree height from 3-D LiDAR
data and the crown areas from aerial photographs
By triangulating and smoothing the FP-mode 3-D
point cloud data, a polygonal 3D-LiDAR image of thewoody crown within the study area was generated. Inaddition, a DTM (Digital Terrain Model) of the groundsurface was generated by interpolating the extracted
ground-level data from the LP-mode data. For theselected 28 Japanese red pine and 13 Japanese cedar
trees, the heights were determined detecting the tops.
In the aerial photograph, each of the selected tree
canopies was segmented along their contours using amethod based on the Watershed algorithm (Wang etal., 2004). Here, the slope of the crown was calculated
from the intensity data of the aerial photograph andtraced in each crown. The contours of the canopies
were identiﬁed based on the inﬂection points of theslope. In this study, the area of each segment in eachtree was named as the crown area and calculated bycounting the corresponding number of pixels in eachof the segments.
2.5 Derivation of relationships between the ﬁeldbased stem volume and parameters estimatedfrom LiDAR data and aerial photograph
The field-based volume of each tree stem wascalculated from the directly measured DBH andthe LiDAR-derived tree height using an allometricequation in each species (The Forestry Agency ofJapan, 1970).
For both the Japanese cedar and Japanese red pine,
we examined the relationships between i) LiDARderived tree heights and Field-based stem volume ii)
crown areas obtained from aerial photographs andField-based stem volume. In addition, based on theexamination of the above two relationships, we madea multiplicative equation to predict stem volume using
the dual parameters of crown area and tree height,
as follows:tree species, a similar investigation was also conductedon the Japanese Cedar (Cryptomeria japonica [L. f.]
D. Don).
2. Materials and Methods
2.1 Study site
The study was carried out in a mixed plantationin Ibaraki Prefecture, 40 km northeast of central
Metropolitan Tokyo, Japan. The dominant tree species
were the Japanese cedar (Cryptomeria japonica [L. f.]
D. Don), Japanese red pine (Pinus densiﬂora Siebold＆ Zuccarini), ginkgo (Ginkgo biloba Linnaeus),and Japanese zelkova (Zelkova serrata [Thunberg]
Makino), and the undergrowth had been removed.
From this site, 28 Japanese red pine and 13 Japanesecedar trees were selected for this experiment.
2.2 Direct measurement of the tree height andDBHIn December 2008, we measured the heights of theselected 28 Japanese red pine and 13 Japanese cedar
trees on the ground using a range ﬁnder (Lasertape
FG-21-HA, RIEGL, Austria) with an accuracy of ±5cm. Subsequently, we directly measured the Diameterat Breast Height (DBH) of each tree to calculate its
volume. The girth of each tree was measured bysurvey taping and the DBH was obtained by dividing
the length by π.
2.3 Measurement using an airborne LiDAR system
The study area was scanned in August 2005 by aLiDAR (ALTM 3100 DC, Optech Co.) mounted ona helicopter (Aero Asahi Co., Japan). The airborneLiDAR calculated the distance to a target via thetime-of-flight method, and incorporated first- andlast-pulse modes, in which the ﬁrst and last returned
laser pulses were detected. The crown surface data
were received by ﬁrst-pulse mode (FP-mode), so thedata of FP-mode were selected to generate an imageof the woody outer crown in the following process.
The laser wavelength was 1,064 nm, and its repetition
frequency was 50,000 Hz. The scanning frequency
was set to 20 Hz, and the density of the laser pulses
was 13.3 pulses m–2. The scanning angle, range andhorizontal accuracy were 20.0°, ±15 and 13 cm, andthe ﬂight speed and height were 50 km/h and 400 m,respectively. Besides 3-D point cloud data, as data of
passive optical remote sensing, aerial photographs of
the area were also captured from 400 m above.

Vp = a # CA b # H c(1)

Where Vp represents the predicted tree stem volume,
CA the crown area obtained from aerial photographs,
and H the LiDAR-derived tree height. The coefﬁcientsof a, b and c were determined by applying multipleregression analysis.
3. Results and Discussion
Fig. 1 (B) shows the 3D-LiDAR image of part of the112

Y. Nakai et al. : Estimation of standing tree volume using LiDAR and optical remote sensing�

�

(m)

20.00
15.00

10.00

5.00

0.00

10 m

Fig. 1. The data of the measurement area obtained by airborne LiDAR and passive optical remote sensing.
(A) Aerial photograph obtained by optical remote sensing. (B) 3D-LiDAR image generated from FP-mode 3Dpoint cloud data.
LiDAR-derived tree height and stem volume wereobtained for both species than those between the crownarea and stem volume as described below.
Fig. 4 shows the relationships between the crownareas calculated by aerial photographs and the ﬁeldbased tree stem volume of (A) the Japanese red pineand (B) the Japanese cedar. They also showed thepower functional relationships. R2 and SE of the stem
volume for the Japanese red pine were respectively
0.61 and 0.096 m3, and 0.35 and 0.097 m3 for theJapanese cedar. In both species, correlations between
the crown areas and tree stem volumes were worse
than the cases in Fig. 3. It was also observed that thecrown areas of Japanese red pine varied more widely
than the Japanese cedar.
Coefﬁcients a, b and c in Eq. (1) were respectively
10 –4.89, 0.16 and 3.78, for the Japanese red pine andrespectively 10 –5.19, 1.19 and 3.19 for the Japanesecedar. Fig. 5 shows comparisons of the stem volume
between the predicted and ﬁeld-based values of (A) theJapanese red pine and (B) the Japanese cedar. The R2and SE of the stem volume were 0.90 and 0.046 m3
for the Japanese red pine, and 0.83 and 0.025 m3 forthe Japanese cedar. Regarding the values of R2 andSE, it was shown that stem volume can be predicted
more accurately from Eq. (1) composed of both treeheight and crown area as compared with using thetree height or crown area alone, especially for theJapanese cedar.
It emerged in Fig. 3 that the LiDAR-derived treeheight alone allowed an accurate estimation of stem
volume. For details, some errors were observed at aheight exceeding 13 m in Fig. 3, where the regression
curves steepened. Because of the steep curve, a few
errors of LiDAR-derived tree height would havecaused the errors of estimation for the stem volume,

study area generated from 3D point cloud data by theairborne LiDAR. The latter allowed the generation of
precise 3-D visual models of the study area.
Fig. 2 shows the segmentation result in an aerial
photograph based on the Watershed algorithm. Eachcrown is indicated as a black region, with the individual
boundaries represented as white lines. By comparing
the segmentation results with a tree position map
obtained by ground truth measurement and an aerial
photograph, it was conﬁrmed that most tree canopies
were well-segmented, although there were someover- or underestimated areas.
Fig. 3 shows the relationships between tree height
estimated using airborne LiDAR and the ﬁeld-based
tree stem volume of (A) the Japanese red pine and(B) the Japanese cedar. They showed power functionalrelationships. The R2 and Standard Error (SE) of stem
volume for the Japanese red pine were respectively
0.90 and 0.042 m3, and 0.74 and 0.090 m3 for theJapanese cedar. Stronger correlations between theFig. 2. The segmentation result in aerial photographbased on Watershed algorithm. Each crown isindicated as black region and the boundaries of eachcrown are represented as white lines.
113

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Fig. 3. Relationships between the tree height estimated using airborne LiDAR and the ﬁeld based tree stem
volume. (A) Japanese red pine (B) Japanese cedar. Where Vp is predicted tree stem volume, and H is LiDARderived tree height.

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Fig. 4. Relationships between the crown area calculated by the aerial photograph and the ﬁeld based tree stemvolume. (A) Japanese red pine (B) Japanese cedar. Where Vp is predicted tree stem volume, and CA is crownarea obtained from aerial photograph.
����������������������� ���������� ������������������ � ������������� ������� ����� � ������������ � ��������������� �������� ����� � ������������������������������������������������������������������������������ ������������������������������ �Fig. 5. Comparisons of stem volume between the predicted values using LiDAR-derived tree height and crownarea obtained from an aerial photograph, and ﬁeld-based values. (A) Japanese red pine (B) Japanese cedar
estimation. However, even if trees have the samestem volume, the values of the crown area may differ
depending on the 3-D structure, e.g. in terms of
blanching pattern or foliage distribution, which wouldexplain the poor correlation between the crown areas
and the tree stem volume. Consequently, it seems difﬁcult to estimate stem volume accurately from crownwhile some actual measurement errors would be also
included in the ﬁeld-based stem volume, i.e. errors ofrange ﬁnding for tree height measurements and thoseof survey taping for DBH measurements.
In this study, the crown area was chosen as aparameter to represent the horizontal structure of thecrown and it appeared useable for the stem volume114

Y. Nakai et al. : Estimation of standing tree volume using LiDAR and optical remote sensing
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area alone. In terms of species difference, the crownarea of the Japanese red pine varied more widely thanthe Japanese cedar, suggesting the former has morestructural variability than the latter.
Multiple regression analysis revealed the t-values of
the tree height and crown area at 9.02 and 1.10 for theJapanese red pine, and 6.00 and 2.97 for the Japanesecedar respectively. The t-value of tree height exceededthat of the crown area for each species, so it seems
that the element of tree height affects the stem volume
more heavily than the crown area.
It can be concluded that the proposed multiplicativeequation composed of tree height from 3-D LiDAR
data and crown areas from aerial photography isbetter for estimating the stem volume of the present
two coniferous trees than using the tree height orcrown area alone, which shows the effectiveness ofthe combination of LiDAR and passive optical sensors
for standing tree volume estimation. In future, moreworks should be conducted for more species to exploit
the ﬁndings of the present study.
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航空機搭載型 LiDAR および受動型光学リモートセンシングを用いた針葉樹の材積量推定
中井洋平・細井文樹・大政謙次（東京大学農学生命科学研究科）

要

約

本研究では，2 種の針葉樹，28 本のアカマツと 13 本

積と幹体積との相関関係は他より劣ったものの，LiDARのスギの立木材積推定における航空機搭載型 LiDAR由来の樹高と幹体積との間には良い相関関係が見られと受動型光学リモートセンシング技術の有用性を確証した。乗法式においては，アカマツでは R2 ＝ 0.90, SE ＝た。航空機からの 3-D LiDAR データと航空写真によっ0.046 m3，スギでは R2 ＝ 0.83, SE ＝ 0.025 m3 となり，て対象樹それぞれの樹高と樹冠面積が得られた。その特にスギにおいて樹高や樹冠面積を単独使用した際より後，1) LiDAR から得た樹高と野外調査幹体積，2) 航も良い結果となった。これは LiDAR と受動型光学セン

空写真から得た樹冠面積と野外調査幹体積との関係を

サーとの組み合わせは立木材積推定において効果的であ分析した。それに加えて，幹体積を推定するために樹高ることを示している。と樹冠面積を用いた乗法式を作成し，推定した幹体積

キーワード： アカマツ，航空機搭載型 LiDAR，3 次元，と野外調査幹体積とを比較することで精度の検証を行っ

受動型光学リモートセンシング，立木材積た。結果として，両種共に航空写真から得られた樹冠面116