2. METHODS 
  
2.1 Focal Species 
Buffel grass (Cenchrus ciliaris) is a C4 African perennial 
tussock grass hailed for its resistance to drought and 
heavy grazing in sub-tropical semi-arid rangelands 
throughout Australia and the Americas. However, it can 
rapidly invade non-target environments, increasing the 
frequency and intensity of wildfire threatening 
biodiversity conservation as well as residential areas. 
Efforts are now being made to prevent further spread of 
this highly invasive and versatile species. Buffel grass 
has highly varied morphological and physiological 
characteristics. It spreads by seed both sexually and 
asexually and vegetatively via rhizomes and stolons. The 
result of this is that Buffel grass has a range of forms and 
can be observed growing in dense monotypic stands as 
well as small clumps and lone tussocks throughout the 
landscape. Individual tussocks can live up to 20 years, 
reaching heights of between 20 — 150cm and produce 
inflorescence ranging in colour from beige to dark 
purple. Older plants tend to have a less vibrantly green 
leaves and typically hold dead leaf at the base of the 
tussock (Figure 1). 
  
  
Figure 1: LEFT Juvenile plant growing in creek line; 
RIGHT mature plant growing at roadside 
(Photographs by Victoria Marshall, northern South 
Australia) 
2.2 Study area 
Our study site is a 10*10 km area located one kilometre 
west of Alice Springs, in central Australia (Figure 2). 
Selected to represent the great diversity of landscapes 
present in central Australia, the scene covers 3-4 peaks of 
the MacDonnell Ranges, the townships of Larapinta, 
pastoral leases, dry creeks and wildlife protected areas. 
Vegetation types which dominate the scene include 
Witchetty Bush or Mulga woodlands, Ironwood Acacia 
woodlands and Spinifex grasslands. This sub-tropical 
arid region typically receives sporadic summer rains 
which can support dense infestations of Buffel grass. The 
grass was sown in and around Alice Springs Airport 
(Figure 2) in the early 1970's to prevent dust storms, and 
has spread out into the neighbouring regions. Locals have 
a strong understanding of its presence in the highly 
varied landscape. In this areas there are known dense 
infestations along watercourse, associated alluvial soils 
and roadsides; sparse infestation on foot hills, becoming 
sparser as it moves further up the hill face; fire affected 
regions where Buffel grass is emerging first on ash beds 
as well as protected sites where the grass is actively 
controlled. 
  
a “Ground validation sites 
  
  
Prodiond by Victarta Marstail. The Univeisity of Adelaide 
  
Figure 2: Study site 1km west of Alice Springs in central 
Australia. Worldview-2 imagery displayed in true colour 
covering the total extent of the study site. Ground 
validation sites are marked (black squares). 
2.3 Image acquisition and pre-processing 
The imagery was acquired on the 22 January 2011 in 
the middle of the wet season following approximately 
80mm of rain over the preceding month. The region had 
also been exposed to record high volumes of rain 
between August and November 2010 due to tropical 
cyclones and floods in Northern Australia. Thus, high 
densities of all ephemeral plants were expected. The 
cloud-free imagery was captured at 1:30 in the afternoon 
at an off-nadir angle of 13 degrees. We corrected for 
atmospheric effects using Fast- — Line-of-sight 
Atmospheric Analysis of Spectral Hypercubes 
(FLAASH) in ENVI 4.8. A Mid-Latitude Summer 
Atmospheric Model, Rural Aerosol Model and an Initial 
Visibility of 40km were applied. The Zenith Angle was 
calculated by taking the mean-off-nadir angle from 180. 
2.4 Image segmentation: Extracting vegetation 
Normalised Difference Vegetation Index (NDVI) was 
applied to the image based on Worldview-2 Red and 
NIR-2 bands. We adopted this traditional approach to 
vegetation extraction in response to the high levels of 
photosynthetically active vegetation present in the 
region. Based on NDVI values, a generous mask (NDVI 
values: 0.3- 2.5) was applied to extract vegetation 
components of land cover from the image. 
2.5 Principle Component Analysis 
To identify the key factors contributing to variation in the 
image a principal component analysis (PCA) was 
applied. This analysis linearly transforms correlated 
bands into uncorrelated components that represent 
variation in the data, reducing the redundancy in the data, 
while retaining all 8 bands. The result in this case is 8 
principal components, where the first three components 
represent approximately 9596 of the variation in the 
image (Figure 3). Based on eigenvectors we can see that 
principal component (PC) one, represents overall albedo, 
PC-2 captures green vegetation and PC-3 captures areas 
     
   
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