Environ. Sci. Technol. 2003, 37, 1198-1201

Accurate Estimation of Forest
Carbon Stocks by 3-D Remote
Sensing of Individual TreesK E N J I O M A S A , * ,† G U O Y U Q I U , †,‡KENICHI WATANUKI,†K E N J I Y O S H I M I , †,§ A N D
YUKIHIDE AKIYAMA|
Graduate School of Agricultural and Life Sciences, The
University of Tokyo, 1-1-1 Yayoi, Bunkyo, Tokyo 113-8657,
Japan, Institute of Resources Science, Beijing Normal
University, 19 Out Xinjiekou Avenue, Beijing 100875, China,
Graduate School of Integrated Science and Art, University of
East Asia, 2-1, Ichinomiya-Gakuen, Shimonoseki, Yamaguchi
751-8503, Japan, and Aero Asahi Co., 1-18-1 Shinsayama,
Sayama, Saitama 350-1331, Japan

Forests are one of the most important carbon sinks on
Earth. However, owing to the complex structure, variable
geography, and large area of forests, accurate estimation offorest carbon stocks is still a challenge for both site
surveying and remote sensing. For these reasons, theKyoto Protocol requires the establishment of methodologies
for estimating the carbon stocks of forests (Kyoto Protocol,
Article 5). A possible solution to this challenge is toremotely measure the carbon stocks of every tree in an
entire forest. Here, we present a methodology for estimating
carbon stocks of a Japanese cedar forest by using a highresolution, helicopter-borne 3-dimensional (3-D) scanninglidar system that measures the 3-D canopy structure of every
tree in a forest. Results show that a digital image (10-cmmesh) of woody canopy can be acquired. The treetop canbe detected automatically with a reasonable accuracy.
The absolute error ranges for tree height measurements
are within 42 cm. Allometric relationships of height to carbon
stocks then permit estimation of total carbon storage bymeasurement of carbon stocks of every tree. Thus, we suggestthat our methodology can be used to accurately estimate
the carbon stocks of Japanese cedar forests at a standscale. Periodic measurements will reveal changes in forest
carbon stocks.

Introduction
Accurate estimation of carbon stocks in forests is crucial tounderstanding the global carbon budget and climate change,
because forests are one of the most important carbon sinks
on Earth. However, because of the complex structure, variable
geography, and large area of forests, accurate estimation offorest carbon stocks is still a challenge. In many cases, forest
carbon stocks are estimated from limited site data. The
representativeness of site data is always uncertain becauseof the heterogeneity of forests. Consequently, remote sensing* Corresponding author phone: +81-3-5841-5340; fax: +81-35841-8175; e-mail: aomasa@mail.ecc.u-tokyo.ac.jp.
† The University of Tokyo.
‡ Beijing Normal University.
§ University of East Asia.
| Aero Asahi Co.
1198 9 ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 37, NO. 6, 2003

technology is expected to provide a solution to this challenge.
Remote sensing typically involves images from a passive
optical system, such as aerial photography or the Landsat
Thematic Mapper (1), or, to a lesser degree, active radar
sensors (2). These types of sensors have allowed extraordinary
advances in the modeling, mapping, and understanding of
ecosystems (2-4). However, they have significant limitations
for forest applications, because their sensitivity and accuracy
have repeatedly been shown to decrease as above-groundbiomass increases (2, 4). They are also limited by their ability
to produce only 2-dimensional images, which cannot fully
represent the 3-dimensional spatial features of forests.
Therefore, currently available remotely sensed data canprovide only a rough average result, and verification is always
a problem. Because of these reasons, the Kyoto Protocol
requires the establishment of methodologies for estimating
the carbon stocks of forests (Kyoto Protocol, Article 5).
Meanwhile, lidar (light detection and ranging) is an
emerging active remote sensing technology, and its applications to 3-D terrestrial observation are developing rapidly(5-7). Since the middle of the 1980s, the nonscanningairborne lidar has been applied to estimate the average heightof forest trees and forest biomass (8). In the middle of the
1990s, the scanning lidar became available and then thistechnology was applied for forest measurement (9-11).
Because of the low scanning rate or high flight speed, however,currently available scanning lidar systems with a small
footprint (laser spot on the ground) of laser beam cannot
cover the entire land surface (5, 10, 12). Airborne lidars witha large footprint and a large scan width are expected forforest remote sensing on a regional scale but these limit theimage resolution (9, 11, 13). As a result, comprehensive
information on individual trees in the woody forest cannot
be collected, and tree height is usually underestimated(9, 10).
Consequently, we assume that if the whole ground surface
is scanned by a laser beam with small footprint, the canopy
surface of individual trees in the woody forest can bemeasured at a high spatial resolution and the digital imageof canopy height can be represented in a small mesh size.
To achieve this goal, we designed a methodology and carriedout extensive experiments with a high-resolution scanninglidar system loaded in a low-flight-speed helicopter. These
efforts ensure that the entire canopy surface can be scanned
at high resolution. By these efforts, we have accurately
measured the canopy height of individual trees (14). The
object of this study is to further improve the spatial resolutionof canopy surface and to estimate the carbon stocks ofJapanese cedar at the stand scale by entire individual tree
measurements with the high-resolution 3-D scanning lidar.

Experimental Section
Field Sites. We studied a Japanese cedar (Cryptomeria
japonica) forest located in Akita prefecture, Japan, because
this type of forest covers a large area in Japan. The Japanesecedar trees were planted about 50 years ago. Because theundergrowth has been cleared away regularly, only Japanesecedar trees have grown in this forest.
Scanning Lidar Measurements. Surfaces of both the forest
canopy and the ground were measured from a helicopter byusing a high-resolution scanning lidar system (ALTM 1025
special model; Optech Co. and Aero Asahi Co.). This lidar
system had the following characteristics. (i) Almost all surface
area could be scanned by a laser beam of small footprint. (ii)
Precise grid data could be obtained by rectangular scan using
a garbomirror scanner. (iii) There were two operational
10.1021/es0259887 CCC: $25.00

 2003 American Chemical Society
Published on Web 02/15/2003

modes, first-pulse mode (FP-mode) for measuring the canopy
surface and last-pulse mode (LP-mode) for measuring groundsurface. By using a time interval meter, the elapsed time
(time-of-flight) between the emitted pulse and the returned
pulse was measured. At each measuring point, FP-mode had
the shortest elapsed time and LP-mode had the longest one.
During measurement, the flight speed was 50 km h-1, andthe flight height was 160-200 m. The footprint size on the
ground was 20-30 cm, and the distance between the centersof neighboring footprints on the ground was 10-15 cm forscan direction and 28 cm for flight direction (the scan width).
The geographic position was determined with a helicopterborne internal measurement unit (IMU) and high-resolution
Global Positioning Systems (GPSs) both in the helicopterand on the ground.
Ground Measurements. On the ground, an area in thelidar-scanning site was selected to measure tree heights, stem
diameter at 1.2 m height, and tree positions. This area wasisolated from other forested areas and the trees included are
fewer (710 m2, 62 standing trees). Consequently, the comparison between data measured on the ground and lidarderived data was much easier. The tree height was measured
by a portable range finder with accuracy of 5 cm (RIEGL,
FG21-HA). The stem diameter was measured using ameasuring tape.
Generation of FP-Mode DEM, DSM, and DCHM. Digital
elevation model (DEM, a mesh size of 10 × 10 cm) was
obtained by interpolation of measured lidar data using
software made by TopScan and modified by Aero Asahi Co.
The canopy surface was shown by a DEM made from FPmode data. The ground surface was estimated from a DEM
made from LP-mode data and was used as the digital surface
model (DSM). The digital canopy height model (DCHM),
which shows the woody canopy height, was obtained bysubtracting the DSM from the FP-mode DEM (14).
Analysis of DCHM. The DCHM images were analyzed toobtain tree height, canopy outline, and the total carbon stocksof each tree with software (such as ERDAS IMAGINE) writtenby the authors and others. The DCHM images usually
included spike noises, which could seriously affect theaccuracy of final results. To delete these noises, the image
was pretreated by a median filter with a mask size of 3 × 3
pixels. Our early study showed that compared with filters ofdifferent types and sizes, a median filter of 3 × 3 pixels was
suitable for tree-height estimation (14). After the medianfiltering, the tree height was automatically determined byfiltering for searching the highest point in the canopy surfaceof each tree. The canopy outline of each tree was calculated
by image processing for edge extraction from the DCHM
image.
Estimation of Carbon Stocks. The stem carbon stocks ofeach tree in the isolated area were estimated from measured
data of tree height and stem diameters at 1.2-m heights byusing a biomass table of Japanese cedar, and then biomass
was converted into carbon stocks by multiplying a ratio of
45% (15, 16). A regression equation for estimating the stem
carbon stocks from tree height was established using boththe field data and all other available data on Japanese cedar
in Japan (212 sets of data) (17). Another regression equationfor estimating the carbon stocks of branches, foliage, androots from tree height was made using data collected all overJapan (53 sets of data) (17). On the basis of these equations,the total carbon stock of each tree was estimated. The treeheights in these data sets ranged from 3 to 30 m.

Results and Discussion
Figure 1 shows a FP-mode DEM image at an area (about 90
× 50 m2) in the field site. The elevation of surfaces of canopy
and ground ranged from 85.0 to 110.0 m. Spike noises causedby lack of lidar scanning data were found. This figure shows

FIGURE 1. FP-mode DEM image at an area (about 90 × 50 m2) ina Japanese cedar (Cryptomeria japonica) forest. The canopy surfaceof each tree and the top were found clearly.

FIGURE 2. DSM image, ground surface estimated as a DEM, at thearea shown in Figure 1.

FIGURE 3. 3-D View of DCHM obtained by subtracting the DSM in
Figure 2 from the FP-mode DEM in Figure 1. The DCHM shows the
woody canopy height of Japanese cedar trees.
that the canopy surface of each Japanese cedar (Cryptomeria
japonica) tree and the top are detected clearly. Ground surface
is represented as the black area in the DEM image.
Figure 2 shows a DSM image of the same area. The groundsurface slopes down from the left to right and the elevation
varies from 81.0 to 84.0 m. Unevenness of the ground surface
and the undergrowth is found as patchiness with differencein height of several tens of centimeters.
Figure 3 shows a 3-D view of DCHM obtained bysubtracting the DSM in Figure 2 from the FP-mode DEM in
Figure 1. Spike noises are deleted by a 3 × 3 m median filter.
The ground surface is converted to a flat level and, consequently, the woody canopy height of Japanese cedar trees isrevealed three-dimensionally.
Figure 4 shows an image of the highest point (cross) ofeach tree overlapped on the DCHM image. Image processing
reveals the number of trees and tree heights. The trees in thisimage are Japanese cedars, a conifer. The position of thehighest point of the tree corresponds with the position of thetree stem. Analysis of this image detected 394 trees, 6 trees
were unfound, and 5 nonexistent trees are detected due tonoise in comparison with treetops found by human eye in
the DCHM image.
Meanwhile, in an isolated area (710 m2) near the area
shown in Figure 4, lidar-derived data are compared withground-measured data. Ground measurement shows that
there are 62 standing trees in the area. However, 3 of them
are not revealed by our lidar-derived data because these trees
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FIGURE 4. Highest point (cross) of each tree overlapped with the
DCHM image. The dark areas are uncovered ground surface. Unfoundtrees and noises are also shown.

FIGURE 5. Distribution of tree heights in the area shown in Figure
4. The tree height was determined from the DCHM image.

are growing under other large trees. Because this Japanesecedar forest has been managed in similar ways, this result
may be applicable to the entire area in the same forest. The
lidar-derived height shows that the estimated error ranges
from -25 to -42 cm with a root-mean-square error (RMSE)
of 37.5 cm, which corresponds to -1.0% to -2.3% of the treeheight measured by the portable range finder. This error
may be caused by the undetectable treetops with thinbranches and the unevenness of the ground surface andundergrowth shown in Figure 2. By the same lidar system,
we have shown errors of less than 47 cm (RMSE ) 19 cm)
for coniferous trees (including Japanese cedar) and 40 cm(RMSE ) 12 cm) for broadleaf trees in an other Japanese
woody area (14). The accuracy of the lidar measurement did
not depend on the tree height. Though this accuracy issatisfactory for many application purposes, we are going tofurther improve it in future work.
Figure 5 shows a histogram of tree heights in the forest
area shown in Figure 4. Heights range from 6.0 to 27.0 m.
The average height is 21.3 m, and most heights (90%) are in
the range of 18.5 to 26.0 m. This kind of information will be
helpful for understanding the structure and function of forest.
Analysis of our field data and of all other available dataon Japanese cedar in Japan (17) shows that the carbon stocks
of a tree stem (Cstem, kg C tree-1) can be well estimated by
Cstem ) 0.0119H2.9696 (R2 ) 0.933), and the carbon stocks ofbranches, foliage, and roots (CBFR, kg C tree-1) can be wellestimated by CBFR ) 0.0075H2.9516 (R2 ) 0.864), where H is treeheight (m). On the basis of these equations, the total carbon
stocks of each tree in the forest were calculated and are given
in Figure 6. The gray level inside each canopy outline
represents the total carbon stock of one tree and covers thearea occupied by that tree’s canopy. The maximum carbon
storage per tree is <300 kg, and most values lie in the rangeof 110 to 300 kg. The total carbon storage in the image area
(90 m × 50 m) is 69 300 kg, and the average carbon storage
is 175.9 kg C tree-1. Because the equations were established
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FIGURE 6. Total carbon stocks (stem, branches, foliage, and roots)of each tree in the area. Each gray level represents total carbon
stocks of one tree and covers the area occupied by that tree’s
canopy.

by using the data of 3-30 m tree height, using them toestimate carbon stocks for trees over 30 m may not be very
accurate.
Accurate measurement of tree height is important,because biomass and forest timber stocks are universallyestimated from tree heights or stem diameters (8, 11, 15).
However, the conventional methods of forest site surveys
measure only a limited number of trees. These limited data
are then used to estimate the heights of all trees in a forest.
Owing to the complex structure of forests and variable
geography, this method is inaccurate. On the other hand,mapping of topographic features is the largest and fastest
growing area of application for lidar remote sensing (5-7).
However, even the newest works on lidar remote sensing arestill not accurate enough to measure small individual trees
such as Japanese cedar trees because of low spatial resolution(12, 13). In contrast, our high-resolution lidar remote sensing
can provide accurate measurements of every tree in a
Japanese cedar forest, allowing measurements of individual
trees at stand level. Furthermore, we also determined theaccurate tree height by filtering for searching the highest
point in canopy surface of each Japanese cedar tree automatically.
Our results have revealed a fairly allometric relationshipbetween tree height and carbon stocks. This allometric
relationship permits estimation of total carbon storage bymeasurement of carbon stocks of every Japanese cedar tree.
Thus, we suggest that our methodology can be used toaccurately estimate the carbon stocks of forests at a standscale. Periodic measurement will reveal changes in carbon
stocks of the forest. However, we have not yet applied it forJapanese cedars over 30 m in height, other conifers, orbroadleaf forests. Our designed software for image analysis
is not powerful enough to analyze a large amount of images
for a regional area including various species of trees. With
the efforts of many scientists, we believe that these challenges
will be overcome gradually in the future.

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Received for review July 19, 2002. Revised manuscript received December 29, 2002. Accepted January 8, 2003.
ES0259887

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