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DO ADDITIONAL BANDS (COASTAL, NIR-2, RED-EDGE AND YELLOW) IN
WORLDVIEW-2 MULTISPECTRAL IMAGERY IMPROVE DISCRIMINATION OF
AN INVASIVE TUSSOCK, BUFFEL GRASS (CENCHRUS CILIARIS)?
Victoria Marshall **, Megan Lewis *, Bertram Ostendorf *
? School of Earth and Environmental Sciences, The University of Adelaide, POB 1 Glen Osmond 5064, South Australia
(firstname.lastname@adelaide.edu.au )
Commission VIII, WG VIII/6
KEY WORDS: Vegetation, Mapping, Classification, Targets, Multispectral
ABSTRACT:
Our goals is to determine if Worldview-2 8-band multispectral imagery can be used to discriminate an invasive grass species
namely, Buffel grass (Cenchrus ciliaris) in the subtropical arid parts of central Australia and whether it offers a tangible
improvement on 4-band (visible and near infra red) multispectral imagery. A Worldview-2 scene was acquired for a
10*10km area just west of Alice Springs in central Australia following heavy rains of early Summer. Mixture Tuned
Matched Filtering was used to classify the image. Target and
from the image. Linear discriminate analysis (LDA) was us
target/ background spectra. The importance of the additiona
background spectra were selected in the field and extracted
d to examine the spectral separability of each group of the
1 spectral bands on the image classification was assessed by
running LDA for both 8 and 4 bands (red, green, blue and NIR). LDA did not indicate improved separability between
groups when additional spectral bands were applied. Preliminary classification results indicate that Buffel grass (Cenchrus
ciliaris) is detected with an omission error 44%, commission error of 11.8% and overall accuracy of 59.5%. We were
surprised that the additional spectral bands did not improve spectral separability and in part attribute this to the high degree
of variance we observed within groups of spectra, which was particularly observable in the NIR2 and Yellow bands. The
analyses may be significantly improved by acquiring imagery following the first big rains at the end of the dry season. At
this time, phonological differences between our focal species and the surrounding native vegetation should be maximised.
We suspect that Worldview-2 will offer even greater potential for the discrimination of Buffel grass under these conditions,
being able to fully utilise the yellow-band in particular.
1. INTRODUCTION
Grass invasions represent a significant threat to
biodiversity and in their aggregate may impact global
aspects of ecosystem function (D'antonio and Vitousek,
1992). This is largely due to their impact on native
wildfire regimes which typically increase in frequency
and intensity where grass was previously absent. Early
detection of new invasions fronts is critical for effective
control. Remote sensing presents as an ideal mode for
mapping and monitoring invasion as it affords a
landscape scale view of the invasion and can be cost
effective compared with laborious field work. However,
due to the often indistinct spectra of grasses and varying
sizes of stands, accurate detection using remote sensing
is challenging. It requires careful consideration of the
species distinctive features, smallest unit of invasion,
seasonal growth, and habit as well as characteristics of
the sensor employed.
Although successfully applied to species-level
discrimination where the target-species covered a broad
extent and possessed distinct phonological characteristics
(Arzandeh and Wang, 2003), aerial photography as well
as long-established multispectral sensors such as Landsat
and SPOT have been described as inadequate for
discriminating between grasses (Gray et al., 2008, Stitt et
al., 2006). Hyperspectral sensors have been proven to
deliver a high degree of accuracy for species-level
discrimination (Gray et al., 2009, Lass et al., 2002) but
the advantages of hyperspectral sensors do not always
justify the high cost and large volumes of redundant data
requiring expert interpretation; as a result it is impractical
for most weed management authorities to utilise this
imagery. The recently launched (January 2010) Digital
Globe Sensor Worldview-2 offers a middle ground
between high spatial and high spectral resolution which
has been lacking. It provides high spatial resolution (2 m
multispectral, 0.5 m pan-sharpened) as well as 8 spectral
bands specifically: short-wave blue (427-458 nm), blue
(478- 515 nm), green (546- 586 nm), yellow (608- 632
nm), red (659- 694 nm), red-edge (724- 749 nm), NIR-1
(833- 901 nm) and NIR-2 (949- 1043 nm). Our aim is to
determine if Worldview-2 imagery can be used to
discriminate an invasive grass species namely, Buffel
grass (Cenchrus ciliaris) in the subtropical arid parts of
central Australia and whether it offers a tangible
improvement on 4-band (visible and near infra red)
multispectral imagery.
