Lidar Detection of the Ten Tallest Trees in the
Tennessee Portion of the Great Smoky Mountains
National Park
Chris W. Strother, Marguerite Madden, Thomas R. Jordan and Andrea Presotto
Abstract
This paper describes a method for predicting the locations and
heights of the ten tallest trees in the Tennessee portion of the
Great Smoky Mountains National Park. Iterative computation
tools were utilized to process the data along with the lidar-
derived bare earth digital elevation models and digital surface
models to create canopy height models for the Tennessee por-
tion of the park. A height threshold of 51.8 meters was chosen
as the minimum value for a tree of extraordinary height. Ten
potential sites containing tall trees were identified using this
methodology, and seven of the top ten ranking trees’ heights
were field measured using accepted forestry methodology. The
trees detected using these methods are potentially the tallest
trees ever measured on the East Coast of the United States.
These methods show that unique tall trees can be successfully
detected in a large, heterogeneous forest area using lidar data.
Introduction
Lidar in Forestry
Airborne lidar (Light Detection and Ranging) data has been
used extensively in the past decades to obtain accurate mea-
surements of forest structure (Nilsson, 1996; Maune, 2001;
Jensen, 2007; Andersen
et al
., 2006). In the context of forestry,
height is defined as the vertical distance between the ground
and the tip of the tree crown (Husch
et al
., 1972). Research
conducted by the US Forest Service in western Washington
State produced sub-meter horizontal and vertical accuracies in
a mountainous, forested area dominated by Douglas fir using
airborne lidar data in a comparison study with field-collected
data (McGaughey
et al
., 2004). The maximum height of tree
plots was predicted with R
2
values for accuracy between 85
and 90 percent in a mixed forest area of Appomattox-Buck-
ingham State Forest in Virginia. (Popescu
et al
., 2002). More
recently, individual tree detection and characterization has
been achieved with some success. Popescu and Wynne (2004)
utilized local maxima to delineate and measure individual
trees. Sankey and Glenn (2011) fused lidar data fused with
Landsat-5
TM
imagery to estimate sub-pixel canopy heights
in the Western US. Li
et al
. (2012) segmented individual trees
from a lidar point cloud data set from the Sierra Nevada Moun-
tains in California. The methodology of subtracting the digital
elevation model (
DEM
) values from the digital surface model
(
DSM
) values to obtain canopy heights has been used by others
in measuring forested areas. (Naesset, 1997; Zimble
et al
., 2003;
Andersen
et al
., 2006). Specifically, lidar technology has been
utilized by Forestry Tasmania, a forest management organiza-
tion in Australia, to locate a unique eucalyptus tree nicknamed
Centurion which measured in at 99.6 m (Lawson, 2010).
Past studies such as Zimble
et al
. (2003) have pointed to
height measurement errors created in the lidar data collection
process created by the post spacing, or distance between height
measurements, that become apparent when ground measure-
ments are made to the highest peaks visible in the tree crown.
Ground-based Tree Height Measurement Procedures
Andersen
et al
. (2006) point out accurate direct measure-
ment of trees in the field is difficult. Crown overlap in dense
canopy as well as other factors such as slope can affect the
ground measurements. The US Forest Service (
USFS
) indicates
that the best height measurements are made using an instru-
ment such as a laser rangefinder with a built in clinometer
(
USFS
, 2005). This tool measures the horizontal distance to
the tree (
hd
) from a fixed location as well as angles to the base
of the tree (
Θ
) and the tip of the crown (
ρ
). The height (
h
) is
derived by the trigonometric equation:
h
=
hd
(tan
ρ
+ tan
Θ
)
Study Area
The 209,000 hectares of the Great Smoky Mountains National
Park (
GRSM
) straddle the border between the states of Tennes-
see and North Carolina (Figure 1). The
GRSM
receives over 10
million visitors a year, making it the most visited National
Park in the US. This area contains roughly 1,500 meters of
relief ranging from around 250 m at the western border of the
park to 2,025 m at Clingman’s Dome, the highest mountain in
Tennessee and third largest east of the Mississippi (
NPS
, 2012).
The park was created in 1934 from lands donated by Tennes-
see and North Carolina in an attempt to mitigate the devastat-
ing effects nineteenth century timber logging and subsequent
erosion. The park is part of the Appalachian Mountain range,
one of the oldest mountain ranges on Earth. It is also one of
the most biologically diverse areas on the planet, given its
Chris W. Strother is with the University of North Georgia - Lewis
F. Rogers Institute for Environmental and Spatial Analysis,
3820 Mundy Mill Rd. Oakwood, GA 30566; and formerly at
the University of Georgia, Geography Department - Center for
Geospatial Research, Athens, GA 30602 (
).
Marguerite Madden is with the University of Georgia,
Geography Department - Director, Center for Geospatial
Research, 210 Field St., Athens, GA 30602.
Thomas R. Jordan is with the University of Georgia,
Geography Department - Associate Director, Center for
Geospatial Research, 210 Field St., Athens, GA 30602.
Andrea Presotto is with the University of Georgia, Geography
Department - Center for Geospatial Research, 210 Field St.,
Athens, GA 30602.
Photogrammetric Engineering & Remote Sensing
Vol. 81, No. 5, May 2015, pp. 407–413.
0099-1112/15/407–413
© 2015 American Society for Photogrammetry
and Remote Sensing
doi: 10.14358/PERS.81.5.407
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
May 2015
407
