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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
ASSESSING THE FEASIBILITY OF UAV-BASED LIDAR FOR HIGH RESOLUTION
FOREST CHANGE DETECTION
L. O. Wallace *, A. Lucieer and C. S. Watson
Survey and Spatial Science Group
School of Geography and Environmental Studies
University of Tasmania
Hobart, Tasmania, Australia
Luke.Wallace Q utas.edu.au
KEY WORDS: Unmanned Aerial Systems, LiDAR, Forestry, Change Detection
ABSTRACT:
Airborne LiDAR data has become an important tool for both the scientific and industry based investigation of forest structure. The uses
of discrete return observations have now reached a maturity level such that the operational use of this data is becoming increasingly
common. However, due to the cost of data collection, temporal studies into forest change are often not feasible or completed at
infrequent and at uneven intervals. To achieve high resolution temporal LiDAR surveys, this study has developed a micro- Unmanned
Aerial Vehicle (UAV) equipped with a discrete return 4-layer LiDAR device and miniaturised positioning sensors. This UAV has
been designed to be low-cost and to achieve maximum flying time. In order to achieve these objectives and overcome the accuracy
restrictions presented by miniaturised sensors a novel processing strategy based on a Kalman smoother algorithm has been developed.
This strategy includes the use of the structure from motion algorithm in estimating camera orientation, which is then used to restrain
IMU drift. The feasibility of such a platform for monitoring forest change is shown by demonstrating that the pointing accuracy of
this UAV LiDAR device is within the accuracy requirements set out by the Australian Intergovernmental Committee on Surveying and
Mapping (ICSM) standards.
1 INTRODUCTION
Airborne Light Detecting and Ranging (LiDAR) data has become
an increasingly important tool for the scientific investigation of
forest structure. The use of discrete return observations have
reached a level of maturity which allows the accurate generation
of forest resource inventories for operational use to become in-
creasingly common (Woods et al., 2011). Limited multi-temporal
studies using LiDAR data have also shown potential for assess-
ing forest dynamics such as changes in biomass, gap fractions
(Vepakomma et al., 2008) as well as for assessing the uncer-
tainty in growth prediction models (Hopkinson, 2008). The use
of LiDAR data for multi-temporal forest surveys are, however,
restricted by the high cost of data collection as well as restric-
tions on flying seasons in some areas. Data collected from repeat
surveys are further complicated by the often large time periods
between surveys. As such these surveys are often performed us-
ing different sensor sets at different flying conditions. For exam-
ple, Vepakomma et al. (2008) used data from surveys with two
different sensors flown at different altitudes (700 m and 1000
m). It has been shown that these datasets are not directly com-
parable as different instruments produce data with different prop-
erties (Nasset, 2009). These restrictions make the assessment
of forest change using full scale airborne data difficult, restrict-
ing scientific investigation and making practical use for forestry
management infeasible.
Mini-Unmanned Aerial Vehicles (UAV) are a platform which can
be used within targeted very high spatial and temporal resolution
surveys at a low cost. The use of these systems in combination
with miniaturised laser scanners has been highlighted as a plat-
form which will allow high frequency multi-temporal forest stud-
ies to be performed with the same instrumentation set (Jaakkola
et al., 2010). The UAV-borne LiDAR system outlined in Jaakkola
et al. (2010), for example, highlights the key advantages of UAVs.
However, the effect of flight conditions for measuring forest met-
rics is yet to be thoroughly examined. The use of mini-UAVs
499
suggest that survey conditions will typically include lower fly-
ing heights, higher point densities, and a smaller survey areas.
Furthermore, the miniaturised laser scanner has been developed
for applications other than mapping (automotive and robotics ap-
plications for example) and are not as highly developed as laser
scanners used on-board full scale systems.
The effect of different flying conditions on the collection of dis-
crete return LiDAR data within forest has been well studied (Lovell
et al., 2005; Goodwin et al., 2006; Disney et al., 2010). Such stud-
ies have often been completed with the aim of determining opti-
mum flying conditions for LiDAR surveys. These studies have
shown that point density, beam divergence, scan angle as well as
the internal properties of the scanner, such as the triggering mech-
anism all have an effect on the derivation of tree metrics and that
these effects are more pronounced at finer measurement scales
(i.e. the individual tree level). Lovell et al. (2005), for example,
suggests that tree height measurements are improved in data sets
with higher point density due to the increased likelihood that the
tree top will be sampled. Furthermore, it has been shown that the
use of large scan angles will result in a reduction in the number
of lower canopy returns and effect canopy cover estimates (Mors-
dorf et al., 2006). The effect of survey conditions are important
to consider for UAV-borne LiDAR surveys. These systems offer
higher point densities and depending on the chosen survey con-
ditions and area of interest may require the use of higher scan
angles to capture an area of interest. Furthermore, the minia-
turised sensors on these systems typically have a higher beam di-
vergence, less sensitive diodes, different triggering mechanisms
and the ability to utilise higher scanning angles (up to 180 ^). As
such the optimum flying conditions, using these low-cost sensors
mounted on UAVs, for repeatable determination of forest met-
rics from LiDAR data requires further investigation. This analy-
sis can assume similar effects of flying height as shown in these
prior studies to provide an initial hypothesis for determining the
optimum conditions for performing UAV-borne surveys.
