International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August - 01 September 2012, Melbourne, Australia
The objectives of this paper are to assess the ability of UAV plat-
forms for monitoring high resolution change within a Eucalyptus
Nitens plantation. This will be achieved by examining the capa-
bilities of a UAV-borne LiDAR system, carrying the same model
scanner as described in (Jaakkola et al., 2010), to resolve plot
level forest metrics and assess the repeatability of these metrics.
The effects of the spatial accuracy of these systems, varying beam
width, point density and scan angle will be assessed by altering
the system's altitude and then manipulating the resultant point
clouds to isolate the effects of each factor.
2 METHODS
2.1 Hardware
The capabilities of the TerraLuma UAV-borne LiDAR system de-
veloped at the University of Tasmania will be assessed in this
study (shown in Figure 1). The platform consists of a multi-
rotor UAV (OktoKopter Droidworx/Mikrokopter AD-8) which is
used to carry the sensor payload. This particular system is capa-
ble of carrying up to 2.8 kg for a duration of 3- 4 min which
is sufficient time to cover a plot sized area within 100 m of the
take off point. The system is equipped with an on-board autopilot
allowing predefined flight paths to be followed which ensure an
efficient use of this flight time.
Figure 1. The multi-rotor UAV platform used within this study.
The laser scanner on-board this system is an Ibeo LUX
automotive scanner.
The sensor payload is vibration isolated from the main platform
through 4 silicon mounts. This payload consists of a position and
orientation system (POS), a laser scanner and a data logging pc.
The POS consists of a MEMs based IMU, a dual frequency GPS
receiver and an HD Video camera. The high rate measurements
from the IMU are fused with observations of position and velocity
from the GPS and orientation from the camera to ensure high
accuracy observations of position and orientation are made for
use in the generation of a point cloud (as outlined in Wallace et al.
(2011)). This payload is stand-alone from the sensors used in the
auto-pilot and all processing is performed offline. The on-board
laser scanner is an Ibeo LUX automotive sensor which measures
points in four scanning layers and in doing so can record up to
22000 returns/s. The scanner has a measurement range of up to
200 m with a repeatability of 0.10 m. The beam divergence of
the Ibeo LUX laser scanner is 0.08 ^ across track and 1.6? along
track. The Ibeo LUX can record up to 3 returns per pulse and
records a pulse length measurement for each return.
500
Flight 1 2 3 4
Altitude (m) 30 50 70 90
points/m 77 45 19 10
Footprint Diameter 0.83 1.30 1.95 2.38
across(along) (m) (0.04) (0.07) (0.10) (0.12)
Motion 9975 2175 205 925
Angle (°)
Table 1. Flight conditions over the field measured pre-pruning
assessment plot.
2.2 Study Area and Data Collection
A 5 year old Eucalyptus Nitens plantation coup was chosen as
the study area. The coup is located near the town of Franklin in
Tasmania, Australia (Figure 2). The area has a mean elevation of
450 m and consists of terrain with a 20 ^ east facing slope. The
trees stand approximately 10 m tall and were due to be pruned
within 2 months of the LiDAR survey.
N
A
g 25 50 100
mm Kilo m ets rs
Figure 2. The state of Tasmania with a dot showing the location
of the study area.
UAV-borne LiDAR data was collected from four flights follow-
ing a 120 m transect in both forward and reverse directions. In
each flight this transect was flown in both forward and reverse
directions. Each flight was flown with an average velocity of
4.0 m/s at a constant height above the take-off point. Four
12.62 m radius circular plots were extracted from each of the
point clouds for use in this analysis. One of these areas is located
over a future pre-pruning assessment plot. This ground inven-
tory will be used in future analysis of the collected data. The
properties of the data acquisition are given in Table 1 based on
the above ground flying height over this ground inventory plot.
The slope of the terrain and constant flying height above take-off
allowed a variety of flying heights to be assessed over the remain-
ing plots. These four flying heights show the significant variation
in footprint diameter, point density and scan angle of the UAV
system. The footprint diameter at 30 m can be considered simi-
lar to some modern full scale data as used in (Yu et al., 2011) for
example. However, all other data is collected with a significantly
larger footprint. The lowest flying height of 30 m ensured safe
operating distance of approximately 10 m above the trees the top
of the slope.
Generating point clouds separately for the forward and reverse
transects allowed comparison both at the various flying height, as
