Grassroots September 2016, Vol. 16, No. 3 | Page 25

Feature
2013) and grazing systems on plant biomass
(Sannier et al., 2002; Archer, 2004; Edirisinghe et
al., 2012) , biodiversity science (Turner et al.,
2003) and for assessing
essing drought events and the
relationship that exists between biophysical
biophysical-,
climate variables and vegetation indices (Yang et
al., 1998; Ji & Peters, 2003; Tadessa et al., 2005).
Therefore, UAV’s offer a range of new
opportunities in high resolution appli
applications in
rangeland research including:
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Species
identification.
Frequent
observations with a RPA can be used to
determine the spectral signatures (also
called reflectance curves) for indicator
plant species (Fairbanks et al., 2000;
Laliberte et al., 2010;; Laliberte et al.,
2011).
Biomass determination. Quantitatively
evaluating vegetation community structure
by accurately measuring canopy height
and volume (Kaneko &Nohara, 2014).
Conservation.
Monitor
and
detect
vegetation cover change (e.g. map
degraded areas by classifying rangeland
cover types) (Koh&Wich, 2012).
Plant health/stress analysis. Changes in the
vegetation health conditions can be
monitored by assessing the photosynthetic
activity of the vegetation layer (e.g.
vegetation indices such as NDVI and EVI)
(Figure 2).
Bush encroachment. Identify and monitor
shrub encroached areas (Figure 3);
Animal management and conservation.
Tracking and counting animals, perform
nest surveys and monitoring grazing and
migration patterns. Study spatiotemporal
dynamics
namics of individual organisms at close
range (Archer & Gaston, 2013);
Terrain
mapping.
Create
three
threedimensional
detailed
topographical
images.
Monitoring and evaluation. Impact
assessment
and
monitoring
of
management practices, veld fires, droughts
and floods
oods on vegetation conditions and
recovery rates (Laliberte et al., 2010).

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Low cost and versatile (i.e. lightweight
and easy to transport) compared to
manned aerial photography;
Low labour intensity as the RPA can be
operated by only one person;
Wide area coverage;
Map and monitor inaccessible areas;
Allow for frequent monitoring and
baseline assessments.

Challenges
 Limited flight time due to battery life;
 Air space restrictions and regulatory
environment;
 Big data analytics.
alytics. Processing platform
need to be able to process and analyse
large amounts of data.
The way forward
New and improved sensors are developed almost
on a routinely basis (Jensen, 2000). With the rapid
advancements in technologies; energy sources will
most certainly in the near future ensure longer
flight times (Koh&Wich, 2012). Satellite and
airborne remote sensing images were not always
able to meet the demands of research and
professional
communities
(Whitehead
&Hugenholtz, 2014). However, the use of RPA’s in
the military has been implemented quite
successfully already and is now rapidly expanding
in the commercial sector.
There has been much speculation on the
potential scientific applications that RPA’s hold
(Kerr &Ostrovsky, 2003; Hugenholtz et al., 2012).
The use of RPA’s in rangeland monitoring and
research in the South African environment is silent
and literature mainly addresses potential
applications. RPA’s together with the appropriate
multispectral sensors are emerging as essential
monitoring and quantitative research tools that have
the ability to enhance objective measurement of
rangeland dynamics
ics (Laliberte et al., 2010;
Whitehead & Hugenholtz, 2014).

Advantages and challenges of RPA technologies
From first-hand
hand account on the use of RPA
technologies in rangeland research, the following
advantages and challenges were experien
experienced;
Advantages
 Easy to acquire timely, hyper
hyper-resolution
and georeferenced aerial images at low
altitudes;

Grassroots

Figure 3: Mosaic image indicating individual woody
shrubs and trees (i.e. white dots) that can be
exploited to identify and monitor shrub encroached
areas as seen on the bottom
bott
left of the image.

September 2016

Vol 16 No. 3