Eco-Engineering, 23（4）,105-109, 2011

Original Paper

Estimation of Leaf Area Density Profiles of Japanese Maple andCamellia Woody Canopies Using Portable Scanning Lidars

Fumiki Hosoi and Kenji Omasa*

The University of Tokyo, Graduate School of Agricultural and Life Sciences
1-1-1 Yayoi, Bunkyo, Tokyo 113-8657, Japan（Received May 24, 2011; Accepted July 21, 2011）

ABSTRACTWe estimated the vertical profiles of leaf area density (LAD) of Japanese maple and camellia canopies in a woody areaby using portable scanning lidar. 3D point cloud data on the canopies were collected by lidar from several points on theground. Appropriate selection of ground points allowed the targets to be well scanned in spite of the presence of several
trees around them. LAD profiles were computed by using the voxel-based canopy profiling method. The maximum andmean LAD values were 1.68 and 0.93 m2 m‑3 for the Japanese maple canopy and 0.94 and 0.41 m2 m‑3 for the camellia
canopy. Leaf area index values were 1.61 and 3.35 m2 m‑2, respectively. Comparison of these LAD estimates with actual
measurements taken in volumes of 2 m3 within the canopies gave percentage errors of ‑14.2% in the Japanese maple
canopy and ‑16.4% in the camellia canopy.

Key words : Leaf area density, Portable scanning lidar, Three-dimensional imaging, Voxel-based canopy profiling

Saeki, 1953), but it has limited applicability in the field be-

1. Introduction

cause it is destructive and very laborious. An indirect method,The plant canopy plays important functional roles in the cy-

the gap-fraction method, is widely applied in field surveys bycling of materials and energy through photosynthesis and tran-using commercially available tools such as cameras with fish-spiration, maintenance of plant microclimate, and provision

eye lenses and optical sensors. This method, which is basedof habitats for many species (Monteith, 1973; Jones, 1992;

on light transmittance through the canopy, allows automatic,

Larcher, 2001). Determining the vertical structure of the can-nondestructive estimation of LAD. However, the accuracy

opy is important to understanding how the three-dimensionalof the measurements is affected by the spatial distribution of(3D) composition of the canopy helps to sustain those func-leaves and by the sunlight conditions (Chason et al., 1991;

tional roles (Graetz, 1990; Lefsky et al., 2002). Vertical can-Jonckheere et al., 2004).

opy structure is often represented by the vertical distribution

Recently, portable scanning lidar (light detection and rang-of leaf area density (LAD) in each horizontal layer, defineding) has been used to obtain 3D structural properties of plants

as the distribution of one-sided leaf area per unit of horizontal(Omasa et al., 2002, 2007, 2008; Lovell et al., 2003; Hosoi etlayer volume (Weiss et al., 2004). Several methods of deriv-al., 2005, 2010; Hosoi and Omasa, 2006, 2007, 2009; Takeda

ing LAD profiles have been tried. A straightforward methodet al., 2005, 2008). The instrument can record many 3D point

is to take stratified clippings of biomass samples (Monsi andcloud data of a target quickly and accurately, regardless of*Corresponding author : Phone: +81-3-5841-5340, Fax: +81-3-5841-8175, E-mail: aomasa@mail.ecc.u-tokyo.ac.jp© The Society of Eco-Engineering（7）105

sunlight. Thus, it has the potential to overcome the shortcom-and 10 m. Its range and scan resolutions are about 1 mm andings of conventional ways of measuring LAD. In fact, it ac-2 mm, respectively, at 5 m. A rotating mount with a stepper

curately and effectively estimated LAD profiles in a Japanese

motor and a galvano mirror within the lidar head automatedZelkova woody canopy (Hosoi and Omasa, 2007, 2009; Hosoi

the horizontal and vertical scanning. Part of the canopy was

et al., 2010). However, the applicability of the method has

scanned from a ground position in September 2009. Each leaf

not been demonstrated in other species. To enhance its ap-was distinguishable from the 3D point cloud image because ofplicability, the method should be tested in woody canopies ofthe fine resolution. After randomly selecting 200 leaves in theother tree species that have structures different from that ofimage, we fitted points within each of the leaves to a plane by

Japanese Zelkova. Therefore, we examined its applicability inthe least squares method and estimated normals to the planes.

two other broadleaved tree species.

The leaf inclination angle was defined as the zenith angle ofthe normal. The leaf inclination distribution was derived from

2. Materials and Methods
2.1 Study site

the zenith angles.
The smaller size of plot B meant that we could use theThe experiment was conducted in a woody area within

TDS-130L scanner for 3D measurements in February 2010.

a botanical garden in Shizuoka Prefecture, Japan. About

Three ground measurement positions were carefully chosen

110 tree species grew in the area, including Japanese ce-to fully illuminate the target camellia. The center of the zenithdar ( Cryptomeria japonica (L. f.) D. Don), Japanese redangles of the laser beams was 59°. We also used the lidar topine ( Pinus densiflora Sieb. & Zucc.), Hinoki cypress

derive the leaf inclination distribution of the camellia canopy(Chamaecyparis obtusa Sieb. & Zucc.), camellia (Camellia

as for the Japanese maple.

japonica L.), oak (Quercus serrata Thunb.), and Japanese ma-

2.3 LAD computationple (Acer palmatum Thunb.). We established two plots, mea-

We used the VCP (voxel-based canopy profiling) methodsuring 7 m × 13 m (plot A) and 6 m × 8 m (plot B). Each

(Hosoi and Omasa, 2006) to compute LAD in the Japaneseplot included many trees of various species with different

maple canopy. The data obtained from the different groundsizes and structures. A Japanese maple grew at the center ofpositions were registered into a single point cloud data set

plot A and a camellia at the center of plot B. We selected thesefor each season with a common 3D coordinate system.

as target trees for LAD estimation by lidar measurements.

Nonphotosynthetic tissues such as trunks and branches were

2.2 Lidar measurements

excluded by subtracting the leafless period data from the leafy

A portable scanning lidar (LPM-25HA, Riegl, Austria) wasperiod data. A voxel array with a voxel size of 5 mm × 5 mm

used for the 3D measurement in plot A. This model is able to× 5 mm was prepared on a computer. All points within themeasure distances of between 2 and 60 m. A rotating mountlidar data were converted into voxel coordinates. Then, all la-driven by built-in stepper motors with 0.009° accuracy panned

ser beams emitted from the lidar were traced within the voxel

and tilted the lidar head. The lidar has a range accuracy ofarray in accordance with the laser emission angles, and voxels±8 mm. In September 2009 (leafy period), trees within plot A

were assigned a value of 1 if at least one laser beam was inter-

were scanned by the lidar from four ground positions chosen

cepted by leaves and 2 if voxels that did not have a value of 1

carefully to fully illuminate the target Japanese maple tree,

were intersected by at least one laser beam. LAD in each hori-

which was surrounded by many other trees. The center of thezontal layer was derived by computing the frequency of laser

zenith angles of the laser beams was 66°. The plot was mea-beam contact with leaves from these voxel attribute values.

sured again from the same positions in February 2010 (leaflessIn the computation, the influence of the leaf inclination angleperiod), with the same measurement conditions as before.

and laser beam direction was corrected by using the correc-

Another portable, high-resolution scanning lidar that cal-tion factor cos(θ)[G(θ)]‑1, where θ is the mean zenith angle

culates distances by trigonometry (a modified TDS-130L 3Dof all laser beam incidences and G(θ) is the mean projection

laser scanner; Pulstec Industrial Co., Ltd., Japan) was used toof a unit leaf area on a plane perpendicular to the direction ofobtain the leaf inclination distribution of the Japanese maple

the laser beam atθ(Weiss et al., 2004). The correction factor

canopy. This model is able to measure distances of between 3.5

was determined by the mean zenith angle of laser beams and106（8）Eco-Engineeringthe distribution of leaf inclination angles acquired by the fine-value of LAD in the region. LAD values corresponding to theresolution portable lidar (a modified TDS-130L), as describedsame region were computed by using the VCP-method, and theabove. More details of the VCP method are given by Hosoi

accuracy was estimated by comparison.

and Omasa (2006).
LAD in the camellia canopy in plot B was similarly comput-

3. Results and Discussioned, using a voxel size of 2 mm × 2 mm × 2 mm. As C. japonica

The high spatial resolution of the lidar correctly repro-

is evergreen, nonphotosynthetic tissues were selected by eye

duced the densely distributed leaves in each canopy from theand excluded.

co-registered 3D point cloud data (Figs. 1, 2). Both canopies

2.4 Actual measurements

were fully scanned.

To validate the lidar-derived LAD estimation, we physically

The leaf inclination distribution of the Japanese maple can-measured leaf area in the Japanese maple in September 2009

opy did not favor a particular angle (Fig. 3). In contrast, thatand in the camellia in February 2010. As direct leaf samplingof the camellia canopy was biased toward lower angles (i.e., awas forbidden, we defined regions of 1 m × 1 m × 2 m within

planophile distribution) (Fig. 4).

each canopy and took digital photographs of each of 50 leaves

We plotted the profiles of Japanese maple and camellia

within the regions with a scale. From the scale, we determinedcanopies (Fig. 5). The estimated LAD profile of the Japanese

the relationship between the number of pixels in each photo-maple canopy was monomodal, with a peak of 1.68 m2 m‑3graph and the actual leaf area. Using this relationship, we deter-(and a mean of 0.93 m2 m‑3 ) at around 3.0 m height. That

mined the mean area per leaf. We counted all leaves in the 2 m3of the camellia canopy was more rectangular, with a peakregion, and by multiplying the number of leaves by the meanof 0.94 m2 m‑3 (and a mean of 0.41 m2 m‑3 ) concentrated

area of a leaf we derived the total leaf area within the region.
Dividing the total leaf area by the volume (2 m3) gave the actualFig. 1 Plot A (7 m × 13 m). (A) Photograph. (B) 3D point cloud
image after co-registration of data measured by using portable scanning lidar. White broken line indicates Japanesemaple canopy.

Eco-Engineering

Fig. 2 Plot B (6 m × 8 m). (A) Photograph. (B) 3D point cloud image after co-registration of data measured by using portablescanning lidar. White broken line indicates camellia canopy.

（9）107

0.15

two canopies.

Reelative frequency

Mean 41.6˚
Mean:
41.6
0.12

Comparison of measured LAD values within the canopies
with the corresponding lidar-derived values gave percent-0.09

age errors of −14.2% for the Japanese maple canopy and−16.4% for the camellia canopy. Vertical integration of0.06

LAD values gave LAI values of 1.61 m2 m‑2 for the Japanese
0.03

maple canopy and 3.35 m2 m‑2 for the camellia canopy. The
camellia’s denser canopy may have reduced the accuracy

0.00
51525354555

657585

Leaf inclination angle (degree)of estimation by reducing canopy penetration by the laser.
Nevertheless, the percentage errors were low. Because leaves

Fig. 3 Leaf inclination angle distribution of Japanese maple canopy.

grew more densely in the 2-m3 regions than in other regions ofthe target canopies, the accuracy of LAD estimation in thoseregions would have been representative of the accuracy for the0.15

Mean: 27.9˚Relative frrequency

0.12

whole canopies. This result demonstrated that our method waseffective at estimating the LAD of the canopies of tree species
that had different structural properties, such as leaf inclination

0.09

distributions and LAD profiles. The low error would have in0.06

part been due to the appropriate selection of ground lidar positions around the targets, ensuring enough penetration into the0.03

canopies. This meant that our method could cope with struc0.00

tural differences among even relatively dense canopies when
51525

35

45

55

65

75

85

Leaf inclination angle (degree)Fig. 4 Leaf inclination angle distribution of camellia canopy.

the laser beams could properly penetrate the canopies.
In woody areas with complex or tall canopies, it may bedifficult to find ground positions for full coverage of a target
canopy. Indeed, we obtained inaccurate results in canopies

6.0

Height (m)5.0Japanese maple

above 10 m, even though the method gave us accurate results

Camellia

under 10 m (Hosoi and Omasa, 2007). It may be possible to40
4.0

complement lidar measurements on the ground by using mea-

3.0

surements from above the ground (Hosoi and Omasa, 2007,2.02009). Although this can be difficult in the field, we effective-

1.0

ly combined ground-level lidar measurements with measure-00
0.0

ments obtained by using airborne scanning lidar (Hosoi et al.,
0.00

0.50

1.00
1.50
LAD (m2m-3)

2.00

Fig. 5 Lidar-derived vertical LAD profiles of Japanese maple andcamellia canopies.

2010). The applicability of this technique should be validated
by additional experiments in various locations with differentspecies.

Acknowledgement
at 2.0 to 4.0 m height. These profiles differed from that of aJapanese Zelkova canopy (Hosoi and Omasa 2007), which

This study was supported by aid for plant research from theNew Technology Development Foundation, Japan.

was monomodal but peaked at 10 m height.
The leaf inclination distributions and LAD profiles showed

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