Grassroots September 2016, Vol. 16, No. 3 | Page 24
Feature
requirements of spatial, spectral and temporal
resolution at budget cost (Dunford et al., 2013).
There are three general classes of RPA’s, close
range (± 50 km), medium range (±200 km) and
long range (>200 km) (Watts et al., 2012). Cost of
medium and long range PRA’s amount to multimulti
million Rand’s and may require complex and
expensive ground control stations. Close range
RPA’s provides lightweight, versatile and costcost
effective opportunities to act as carriers of a variety
of sensors, including NIR (near infra-red),
infra
RGB
(red, green and blue bands), RE (red edge), multimulti
and hyper spectral, LIDAR (Light Imaging,
Detection and Ranging) and temperature measuring
thermal sensors. Furthermore, different
dif
models of
RPA’s are advantageous for different applications.
Multi-copter
copter RPA’s are more suitable for
surveillance and mapping of small areas, while
fixed wing RPA’s are more suited for mapping
when extended flight times are required to cover
longer distances.
Potential applications of RPA’s in rangeland
research and monitoring
Figure 2: a) Remotely sensed image of a drainage
line running down the middle of the image, b)
Enhanced Vegetation Index calculated from Near
Nearinfrared image captured by a RPA indicating, in
white, photosynthetic activity of the vegetation layer
in and along the drainage lines.
With the introduction of affordable remotely
piloted aircrafts (RPA’s), also known as unmanned
aerial vehicles (UAV’s), one can now safely
acquire timely hyper-resolution
resolution aer
aerial images at
low altitudes (Whitehead et al., 2014; Giessel,
2015). Currently the National Aeronautics and
Space
Administration
(NASA;
http://www.nasa.gov/centers) as well as the
National Oceanic and Atmospheric Administration
(NOAA; http://uas.noaa.gov) have Unmanned
Aircraft Systems Programs. RPA’s provide low
operational complexity and costs, compared to
manned
aerial
photography
(Whitehead
&Hugenholtz, 2014). Remote sensing sensors
placed in RPA’s furthermore provides the capacity
to combine high spatial
al resolution and quick
turnaround times in order to meet critical
Grassroots
The RPA’s have the potential to bridge the gap
between ground-based
based surveys and remote sensing
data acquired from satellites or manned aircrafts
(Whitehead et al., 2014). Ground surveys provide
only the information required to develop high
resolution maps and allow monitoring of vegetation
changes in small areas. Remote sensing data
acquired from satellites are sufficient to produce
maps and monitor vegetation activity over areas of
a much larger extent; however, limitations arise in
terms of lower spatial resolution and operational
flexibility (Whitehead &Hugenholtz, 2014). It
becomes expensive to monitor features at a finerfiner
scale from satellite derived remote sensing images
image
on a routinely basis. However, with fully
autonomous GPS-guided
guided RPA’s, mapping and
monitoring changes on a routinely basis at an
intermediate spatial scale is possible (Koh&Wich,
2012; Whitehead et al., 2014). The RPA is capable
of producing high quality orthorectified and geogeo
referenced images (Figure 1) which can be used for
mapping purposes as well as a tool to verify course
scale satellite data in order to conduct ground
truthing on vegetation indexes calculated from
near-infrared
infrared images, such as; the Normalized
Difference Vegetation Index (NDVI) and Enhanced
Vegetation Index (EVI) (Figure 2; Laliberte et al.,
2010).
Satellite derived remote sensing has already
been used in various previous studies to depict
land-cover
cover change (Stow et al., 2004,
Shalaby&Tateishi,
by&Tateishi, 2007; Koh&Wich, 2012), the
impact of fires (Huesca et al., 2013; Wooster et al.,
September 2016
Vol 16 No. 3