Peer-Reviewed Articles
1339 Change Detection Techniques for Canopy Height
Growth Measurements Using Airborne Laser Scanner
Data
Xiaowei Yu, Juha Hyyppä, Antero Kukko, Matti Maltamo, and
Harri Kaartinen
Abstract Download Full Article
This paper analyzes the potential of airborne laser scanner
data for measuring individual tree height growth in a boreal
forest using 82 sample trees of Scots pine. Point clouds
(10 points/m2, beam size 40 cm) illuminating 50 percent
of the treetops were acquired in September 1998 and May
2003 with the Toposys 83 kHz lidar system. The reference
height and height growth of pines were measured with a
tacheometer in the field. Three different types of features
were extracted from the point clouds representing each tree;
they were the difference between the highest z values, the
difference between the DSMs of the tree crown, and the
differences between the 85th, 90th and 95th percentiles of
the canopy height histograms corresponding to the crown.
The best correspondence with the field measurements was
achieved with an R2 value of 0.68 and a RMSE of 43 cm. The
results indicate that it is possible to measure the growth of
an individual tree with multi-temporal laser surveys. We also
demonstrated a new algorithm for tree-to-tree matching. It is
needed in operational growth estimation based on individual
trees, especially in dense spruce forests. The method is based
on minimizing the distances between treetops in the N-
dimensional data space. The experiments showed that the
use of the location (derived from laser data) and height of
the trees were together adequate to provide reliable tree-to-tree matching. In the future, a fourth dimension (the crown
area) should also be included in the matching.
1349 Ground-based Laser Imaging for Assessing Three Dimensional
Forest Canopy Structure
Jason G. Henning and Philip J. Radtke
Abstract Download Full Article
Improved understanding of the role of forests in carbon,
nutrient, and water cycling can be facilitated with improved
assessments of canopy structure, better linking leaf-level
processes to canopy structure and forest growth. We examined the use of high-resolution, ground-based laser imaging
for the spatially explicit assessment of forest canopies.
Multiple range images were obtained and aligned during
both leaf-off and leaf-on conditions on a 20 m x 40 m plot.
The plot location was within a mixed species broadleaved
deciduous forest in western North Carolina. Digital terrain
and canopy height models were created for a 0.25 m square
grid. Horizontal, vertical, and three-dimensional distributions of plant area index, created using gap-fraction based
estimation, had 0.5 m resolution for a cubic lattice. Individual tree measurements, including tree positions and diameter at breast height, were made from the scanner data with
positions, on average, within 0.43 m and diameters within
5 cm of independent measurements, respectively. Our
methods and results confirm that applications of ground-
based laser scanning provide high-resolution, spatially-
explicit measures of plot-level forest canopy structure.
1359 Examining the Influence of Changing Laser Pulse Repetition
Frequencies on Conifer Forest Canopy Returns
Laura Chasmer, Chris Hopkinson, Brent Smith, and Paul Treitz
Abstract Download Full Article
The distribution of laser pulses within conifer forest trees
and canopies are examined by varying the rate of laser
pulse emission and the inherent laser pulse properties (laser
pulse energy, pulse width, pulse length, and roll-over or
trigger time). In this study, an Optech, Inc. ALTM 3100
airborne lidar is used, emitting pulses at 50 kHz and
100 kHz, allowing for changes in laser pulse characteristics
while also keeping all other survey parameters equal. We
found that:
1. Pulses and associated characteristics emitted at 50 kHz penetrated further into the canopy than 100 kHz for a significant number of individual trees.
2. At tall tree plots with no understory, pulses emitted at 50 kHz penetrated further into the canopy than 100 kHz for a significant number of plots.
3. For plots with significant understory and shorter trees, pulses emitted at 100 kHz penetrated further into the canopy than 50 kHz. We suspect that this may be due, in part, to canopy openness.
Laser pulse energy and character differences associated with different laser pulse emission frequencies are likely a contributing factor in laser pulse penetration through the canopy to the ground surface. Efforts to understand laser pulse character influences on canopy returns are important as biomass and vegetation structure models derived from lidar are increasingly adopted.
1369 Single Tree Segmentation Using Airborne Laser Scanner
Data in a Structurally Heterogeneous Spruce Forest
Svein Solberg, Erik Naesset, and Ole Martin Bollandsas
Abstract Download Full Article
In this study, we present a new method for single tree
segmentation and characterization from a canopy surface
model (CSM), and its corresponding point cloud, based on
airborne laser scanning. The method comprises new algorithms for controlling the shape of crown segments, and for
residual adjustment of the canopy surface model (CSM). We
present a new criterion that measures the success of locating
trees, and demonstrate how this criterion can be used for
optimizing the degree of CSM smoothing. From the adjusted
CSM segments, we derived tree height and crown diameter,
and based on all first laser pulse measurements within the
segments we derived crown-base height. The method was
applied and validated in a Norway spruce dominated forest
reserve having a heterogeneous structure. The number of
trees automatically detected varied with social status of the
trees, from 93 percent of the dominant trees to 19 percent of
the suppressed trees. The RMSE values for tree height, crown
diameter, and crown-base height were around 1.2 m, 1.1 m,
and 3.5 m, respectively. The method overestimated crown
diameter (0.8 m) and crown base height (3.0 m).
1379 Using Laser Altimetry-based Segmentation to Refine
Automated Tree Identification in Managed Forests of
the Black Hills, South Dakota
Eric Rowell, Carl Seielstad, Lee Vierling, LLoyd Queen, and
Wayne Shepperd
Abstract Download Full Article
The success of a local maximum (LM) tree detection algorithm for detecting individual trees from lidar data depends on stand conditions that are often highly variable. A laser
height variance and percent canopy cover (PCC) classification is used to segment the landscape by stand condition
prior to stem detection. We test the performance of the
LM algorithm using canopy height model (CHM) smoothing
decisions and crown width estimation for each stand
condition ranging from open savannah to multi-strata
stands. Results show that CHM smoothing improves stem
predictions for low density stands and no CHM smoothing
better detects stems in dense even-aged stands, specifically
dominant and co-dominant trees (R2 = 0.61, RMSE = 20.91
stems with smoothing; R2 = 0.85, RMSE = 46.02 stems with
no-smoothing; combined smoothed CHM for low density and
unsmoothed CHM for high density stands R2 = 0.88, RMSE =
28.59 stems). At a threshold of approximately 2,200 stems
ha-1, stem detection accuracy is no longer obtainable in any
stand condition.
1389 Using Tree Clusters to Derive Forest Properties from
Small Footprint Lidar Data
Zachary J. Bortolot
Abstract Download Full Article
This paper describes a new object-oriented small footprint
lidar algorithm in which the objects of interest are tree
clusters. The algorithm first thresholds the lidar canopy
height model (CHM) at two levels to produce tree cluster
grids. Next, two metrics are calculated based on these grids.
The metric values are used in a multiple regression equation
to predict the forest parameter of interest. To set the two
thresholds, an optimization algorithm is used in conjunction
with training data consisting of subsets of the CHM in which
the forest parameters are known through ground measurements. A test of the algorithm was performed using ground
and lidar data from a non-intensively managed loblolly pine
(Pinus taeda) plantation in Virginia. The accuracies of the
lidar-based predictions of density (0.01 R2 ≤ 0.80; 126
trees/ha ≤ RMSE ≤ 8,173 trees/ha) and biomass (0.04 ≤ R2 ≤ 0.62; 12.4 t/ha ≤ RMSE ≤ 316.5 t/ha) depended on
the combination of metrics used, whether trees with a
diameter at breast height < 10 cm were excluded from the
analysis, and the number of plots used for training and
testing. However, the fit between the ground measurements
and tree cluster-based predictions generally exceeded the fit
between ground measurements and the output from an
individual tree-based algorithm tested using the same data
(100 percent of comparable cases when density was predicted, 85 percent of comparable cases when biomass was
predicted, based on the coefficient of determination and RMSE).
1399 The Application of Lidar in Woodland Bird Ecology:
Climate, Canopy Structure, and Habitat Quality
Shelley A. Hinsley , Ross A. Hill , P.E. Bellamy , and Heiko Balzter
Abstract Download Full Article
Habitat quality is fundamental in ecology, but is difficult
to quantify. Vegetation structure is a key characteristic of
avian habitat, and can play a significant role in influencing
habitat quality. Airborne lidar provides a means of measuring vegetation structure, supplying accurate data at high
post-spacing and on a landscape-scale, which is impossible
to achieve with field-based methods. We investigated how
climate affected habitat quality using great tits (Parus major)
breeding in woodland in eastern England. Mean chick body
mass was used as a measure of habitat quality. Mean
canopy height, calculated from a lidar digital canopy height
model, was used as a measure of habitat structure. The
influence of canopy height on body mass was examined
for seven years during which weather conditions varied.
The slopes and correlation coefficients of the mass/height
relationships were related linearly to the warmth sum, an
index of spring warmth, such that chick mass declined
with canopy height in cold, late springs, but increased
with height in warm, early springs. The parameters of the
mass/height relationships, and the warmth sum, were also
related linearly to the winter North Atlantic Oscillation
index, but with a time lag of one year. Within the same
wood, the structure conferring “best” habitat quality differed
between years depending on weather conditions.
1407 Evaluating A Small Footprint, Waveform-resolving Lidar
Over Coastal Vegetation Communities
Amar Nayegandhi , John C. Brock , C. Wayne Wright ,
and Michael J. O’Connell
Abstract Download Full Article
NASA’s Experimental Advanced Airborne Research Lidar
(EAARL) is a raster-scanning, waveform-resolving, green-wavelength (532 nm) lidar designed to map near-shore
bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor records the time history of the
return waveform within a small footprint (20 cm diameter)
for each laser pulse, enabling characterization of vegetation
canopy structure and “bare earth” topography under a
variety of vegetation types. A collection of individual
waveforms combined within a synthesized large footprint
was used to define three metrics: canopy height (CH), canopy
reflection ratio (CRR), and height of median energy (HOME).
Bare Earth Elevation (BEE) metric was derived using the
individual small-footprint waveforms. All four metrics were
tested for reproducibility, which resulted in an average of 95
percent correspondence within two standard deviations of
the mean. CH and BEE values were also tested for accuracy
using ground-truth data. The results presented in this paper
show that combining several individual small-footprint laser
pulses to define a composite “large-footprint” waveform is a
possible method to depict the vertical structure of a vegetation canopy.