Short Paper

J. Agric. Meteorol. (農業気象) 65 (3): 297-302, 2009

Estimating the leaf inclination angle distribution of the wheat canopy
using a portable scanning lidar
Fumiki HOSOI, Yohei NAKAI, and Kenji OMASA
Graduate School of Agricultural and Life Sciences, The University of Tokyo,
Yayoi 1–1–1, Bunkyo-ku, Tokyo, 113–8657, Japan
Abstract
The leaf inclination angle distributions of wheat (T. aestivum cv. Norin 61) canopy were estimated at
different growth stages (tillering, stem elongation, ﬂowering, and ripening stages) by using a high-resolution portable scanning lidar. The canopy was scanned three-dimensionally by optimally inclined laser
beams emitted from several measuring points surrounding the canopy and 3-D point cloud images ineach growth stage were obtained. After co-registration of lidar images between different measurement
positions, leaves were extracted from the images and each leaf was divided into small pieces along
the leaf-length direction. Each of the pieces was approximated as a plane, to which normals were thenestimated. The distribution of the leaf inclination angles was derived from the angles of these normals
with respect to the zenith. Consequently, distinctive features of the leaf inclination angle distributions at
each growth stage clearly emerged. The mean leaf inclination angles on 6 April, 26 April, 16 May, and
5 June were 53.9º, 45.3º, 44.3º and 56.1º respectively and the standard deviations were 19.6º, 22.2º, 21.7º
and 19.5º respectively. Moreover, laboratory measurements conﬁrmed that the mean and standard deviations of the absolute error of lidar-derived leaf inclination angles were 4.3º and 2.0º, respectively.
Key words: Crop, Growth stage, Leaf inclination angle distribution, Portable scanning lidar, Threedimensional imaging.

and ranging) has been utilized to obtain the 3-D
structural properties of plants (Omasa et al., 2002,2007; Lovell et al., 2003; Hosoi et al., 2005; Hosoi
and Omasa, 2006, 2007, 2009; Takeda et al., 2005,2008). This instrument can record many 3-D point
cloud data of a target quickly and automatically andthus seems usable for repeated measurements of the
LIA distribution of the crop canopy. However, theinstrument has not yet been used to measure theLIA distribution of the crop canopy because therange accuracy and resolution of most commerciallyavailable portable lidars, which were typically one toseveral cm, were insufﬁcient to capture the inclinationof each leaf. Recently, we demonstrated that the LIA
distribution of broad leaved canopies can be measured
using a high-resolution portable scanning lidar withrange resolution of about 1 mm at a measurement
range of about 5 m (Hosoi and Omasa, 2007). Sucha high-resolution portable scanning lidar would be alsouseable for the LIA distribution measurement of a crop
canopy in terms of its resolution.

1. Introduction
The Leaf inclination angle (LIA) distribution is
one of the 3-D structural properties related to light
distribution within the canopy and affecting thephotosynthetic productivity of the whole plant (Leihnerand Ortiz, 1978; Sassenrath-Cole, 1995). Due to its
importance, LIA distributions have been measured inprevious studies by using devices such as a protractor
with a compass (Norman and Campbell, 1989), aclinometer (Gratani and Ghia, 2002) and 3-D digitizers (Sinoquet et al., 1998; Shibayama, 2004). Thesemethods, however, are very laborious, meaning themeasurable leaf number is limited. In particular, forcrop canopies, it is important to repeatedly measure
the LIA distribution over time with the growth but thelaborious nature of the above conventional methods is
unfavorable for repeated measurements.
Recently, a portable scanning lidar (light detection
Received; March 25, 2009.
Accepted; June 15, 2009.
297

J. Agric. Meteorol. (農業気象) 65 (3), 2009
the canopy. Arrows in Fig. 1A show the directions
corresponding to the central angle of the azimuth laser
beam scan from each of the measurement positions.
The central zenith angle of the laser beam scan wasset to 57.5º by placing the lidar head at a height of
2.5 m (Fig. 1B). The central zenith angle was chosen
based on the results of our previous works (Hosoi andOmasa, 2006, 2007). Based on the lidar setting, thelidar measurements were conducted under windlessconditions to avoid disturbance of the canopy by wind.
The measurement dates were 6 April, 26 April, 16May, and 5 June 2006 (155, 175, 195, and 215 days
after sowing [DAS], respectively), which corresponded
to the tillering, stem elongation, ﬂowering, and ripeningstages, respectively.
The lidar data set for each date was composed of four
point-cloud data obtained from the four measurement
positions. The individual coordinate systems for thesedata were registered into a single point-cloud data
set with a common 3-D coordinate system for eachmeasurement date using the iterative closest-point
algorithm (Besl and McKay, 1992). Subsequently,
data corresponding to the individual wheat plants wasextracted from the registered images at each growthstage. At the extracted data, each type of organ, i.e.
leaves, stems, ears, was distinguishable due to the ﬁne
resolution of the lidar, whereupon only leaves wereIn this study, measurement of the LIA distributionsof the wheat (T. aestivum cv. Norin 61) canopy wereattempted at different growth stages by using a highresolution portable scanning lidar.
2. Materials and Methods
The experiment was conducted at an experimental
farm in Ibaraki Prefecture, Japan. Winter wheat(T. aestivum cv. Norin 61) seeds were sown on 2November, 2005 using 90 kg seed grain/ha and 50-cm
row spacing. Four plots (1 m×1 m, see Fig. 1) were
established on different four locations in the farm.
Each plot was assigned to the individual measurementof different four growth stages.
A portable high-resolution scanning lidar that
calculates distances based on trigonometry (a modiﬁed
TDS-130L 3-D laser scanner; Pulstec Industrial Co.,
Ltd., Japan) was used to obtain 3-D information of thewheat canopy (Hosoi and Omasa, 2009). The lidar'smeasurable range is 3.5 to 10 m. The range and scan
resolutions are about 1mm and 2 mm, respectively, ata measurement range of about 5 m. A rotating mountwith a stepper motor and a galvano mirror within
the lidar head automated the horizontal and verticalscanning. Fig. 1A illustrates an aerial view of thewheat canopy measurement by the portable scanninglidar with four measurement positions surrounding

AB
Vertical
Lidar head
1.0 m

Beamdirection

Beam direction
1.0 m

�c

Lidar head

2.5m

Plot�
3.9m
Fig. 1. Schematic views of the wheat canopy measurement by the high-resolution portable scanning lidar. (A)Aerial view. Arrows show the directions corresponding to the central angles of the azimuth laser beam scanfrom each of the measurement positions. (B) Side view. θc show the central zenith angle of the laser beams(modiﬁed from Hosoi and Omasa, 2009).
298

F. Hosoi et al. : Estimating the leaf inclination angle of wheat using a portable lidar
visually selected and extracted from the data. Eachleaf was divided into small pieces at 15mm intervals
along leaf-length directions and LIA was estimatedfor each of the pieces. Points within each of thepieces were ﬁtted by a plane based on the least square
method and normals to the planes were estimated.
The LIA distribution was derived from the angles ofthese normals with respect to the zenith. Based on
the procedure, LIA distribution was estimated in eachof the different growth stages. To accurately estimate
LIA, the interval of the pieces must be determined
appropriately. LIA changes along the leaf length direction, hence the shorter interval is desirable to capture
the change faithfully. However, when the interval is
too short, there is insufﬁcient lidar data to calculate
LIA in each of the pieces. With these two matters inmind, the interval was determined as 15mm.
To evaluate the accuracy of the lidar-derived LIA,
actual LIA values obtained by direct methods, e.g.
the use of a protractor or clinometer, were required.
However, it is very difﬁcult to conduct direct measurements accurately in the ﬁeld because the measurementtakes considerable time, meaning it is difficult tomaintain a stable measurement condition withoutwind impacting the measurement. Subsequently, anindividual wheat plant was uprooted from the ﬁeld at
the ripening stage, placed in a pot and taken into alaboratory. 60 leaf pieces of length 15mm and width
equivalent to the leaf width were randomly selectedfrom the plant and marked to distinguish each of theleaf pieces. Lidar measurements were conducted on theplant in a setting similar to the above described ﬁeld
measurements, i.e. four measurement positions aroundthe plant with the central zenith angle of the laser
beams of 57.5º. Subsequently, LIA values corresponding to the 60 pieces were estimated using a method
similar to that described above. Actual LIA values forthe 60 pieces were measured by a clinometer (A-150;Shinwa Measuring Tools Corp. Japan). The error of
the lidar-derived LIA was estimated by comparing
lidar-derived values with actual ones.

�����Fig. 2. A 3-D image of wheat canopy on 16 May
measured by a high-resolution portable scanninglidar.
angle class consists of a 5º interval. On 6 April, thedistribution concentrated on the angles between 50
to 80º classes (Fig. 3A). On 26 April, a peak wasobserved at a 70º class, while the proportion of thelower angle classes increased (Fig. 3B). On 16 May,
more even distribution was observed without clear
peaks (Fig. 3C). On 5 June, the distribution shifted tohigher angle classes and a peak appeared at the 65ºclass (Fig. 3D). The mean angles of LIA on 6 April,
26 April, 16 May, and 5 June were, respectively, 53.9º,
45.3º, 44.3º and 56.1º and the standard deviations were,respectively, 19.6º, 22.2º, 21.7º and 19.5º.
Through the laboratory measurements, it wasconﬁrmed that the absolute error of lidar-derived LIAranged from 0.0º to 6.8º, and the mean and standard
deviation of the absolute error were 4.3º and 2.0º,
respectively. Those results showed that LIA can be
estimated accurately using a high-resolution portablescanning lidar.
To enable accurate estimation, in the present study,measurements using the high-resolution portable
lidar were conducted from four measurement points
surrounding the canopy with optimally inclined laser
beams of the central zenith angle of 57.5º. For thepurpose of these measurements, the whole canopy
could be illuminated, including internally, by full laser
beams, resulting in obtaining an accurate and precise
3-D point cloud images of the whole canopy. Thanks
to these high quality 3-D images, distinctive features ofthe leaf inclination angle distributions in each growthstage clearly emerged. During the tillering stage on 6

3. Results and Discussion
Fig. 2 is a co-registered 3-D point cloud image ofa wheat canopy taken on 16 May. In this image, eachtype of organ was distinguishable by observing theimage from various perspectives.
Fig. 3 represents the LIA distributions of the wheat
canopy in different growth stages, in which each299

J. Agric. Meteorol. (農業気象) 65 (3), 2009

6 April, 155 DAS

0.12

Mean : 53.9�
S.D. : 19.6°

0.09

0.06

0.09

0.03

0.00
0.15

0.00
0.15
5 1015202530354045505560657075808590

�

0.12

16 May, 195 DAS

Leaf inclination angle (degree)

Mean : 44.3�
S.D. : 21.7°

0.09

0.06

�

26 April, 175 DAS

Mean : 45.3�
S.D. : 22.2°

0.06

0.03

0.12

Proportion

Proportion

0.12

Proportion

0.15

�Proportion

0.15

0.09

5 1015202530354045505560657075808590

�5 June,215 DAS

Leaf inclination angle (degree)

Mean : 56.1�
S.D. : 19.5°

0.06

0.03

0.03

0.00

0.00
5 1015202530354045505560657075808590

5 1015202530354045505560657075808590

Leaf inclination angle (degree)

Leaf inclination angle (degree)

Fig. 3. Leaf inclination angle distributions in each growth stage estimated from 3-D lidar images. (A) 6 April,
155 DAS, tillering stage (n=206) (B) 26 April, 175 DAS, stem elongation stage (n=356) (C) 16 May, 195 DAS,
ﬂowering stage (n=261) (D) 5 June, 215 DAS, ripening stage (n=327). DAS, days after sowing. S.D., standarddeviation.
�6 April,155 DAS

�

26 April, 175 DAS

�

16 May,195 DAS

�

5 June,215 DAS

April, the majority of leaves were growing upwards(see Fig. 4A), which explains the concentration of thedistribution of LIA on relatively higher angle classes(Fig. 3A). At the stem elongation stage on 26 April,although some of leaves still grew upwards, most bent
downwards from the middle of the leaf (see Fig. 4B).
The part around the leaf bending point less inclined(see the part within a dotted circle in Fig. 4B), sothat the proportion of lower angle classes increased(Fig. 3B). At the ﬂowering stage on 16 May, almost
all leaves bent downwards (see Fig. 4C), so that thehigher angle class decreased and the distribution was
equalized (Fig. 3C). At the ripening stage on 5 June,
leaves drooped down due to senescence, particularly at
the lower part of the canopy (see Fig. 4D), explaining
the increase in the higher angle classes at this stage(Fig. 3D).
This study demonstrated that LIA distribution ofwheat canopy at different growth stages can be estimated distinctively and accurately by a high-resolution
portable scanning lidar. To enhance the applicabilityof the method, additional studies applying the present
method to different growing conditions in other ﬁelds
and different kinds of crops are needed. In addition,
the inclination of other types of organs, such as stems
and ears, affects the light environment of the canopy.

Fig. 4. Photographs of side views of wheat canopy
in each measurement date. (A) 6 April, 155 DAS,
tillering stage (B) 26 April, 175 DAS, stem elongation stage (C) 16 May, 195 DAS, ﬂowering stage (D)
5 June, 215 DAS, ripening stage. DAS, days aftersowing. A white dotted circle in (B) is an exampleof a part around a bending point.
300

F. Hosoi et al. : Estimating the leaf inclination angle of wheat using a portable lidar
Although this study focused on the estimation ofLIA using a high-resolution portable lidar, it would
also be signiﬁcant to apply the present method forestimating the inclination angle distribution of othertypes of organs.

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可搬型スキャニングライダーを用いた小麦の葉傾斜角分布計測
細井文樹・中井洋平・大政謙次( 東京大学大学院農学生命科学研究科 )要約本研究では高空間分解能可搬型スキャニングライダーに算出し，その天頂角より葉傾斜角分布を得た。その結を用い，小麦 ( 農林 61 号 ) の葉傾斜角分布を異なる生果，葉傾斜角分布の各成長ステージ毎の違いを明確にと育ステージで計測する方法を考案し，検証した。まず可らえることができた。4 月 6 日，4 月 26 日，5 月 16 日，

搬型ライダーを小麦のキャノピーを取り囲む複数の地点ザービーム入射角の設定も最適化し，キャノピー全体が6 月 5 日の計測において，葉傾斜角分布の平均値と標準，45.3 ± 22.2°，44.3 ±偏差はそれぞれ 53.9 ± 19.6°
21.7°，56.1 ± 19.5°という値を示した。さらに実験室内

その内部まで隈なくレーザービームに照射されるようにでの実験により本方法の誤差検証を行ったところ，絶対に設置し，3 次元点群データを取得した。その際，レー配慮した。各地点から取得されたデータをレジストレーシという結果が得値誤差の平均値と標準偏差は 4.3 ± 2.0°

ョンした後，3 次元データに含まれる葉に相当するデーられた。

タを抽出し，各々の葉のデータを長手方向に分割し，葉キーワード： 可搬型スキャニングライダー，作物，3 次元イの小片に相当するデータを作成した。この葉の小片に相メージング，生育ステージ，葉傾斜角分布当するデータを 3 次元平面と近似し，その法線を小片毎302