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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
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Wavelength (nm)
Graph 2. Electromagnetic spectrum and spectral reflectance
profiles for different species (adopted from the spectral library
of the Environment for Visualizing Images software
(ENVI, 2003)
The signal noise (s/n) ratio of scanners depends on the photon
flux received from the earth surface. This is influenced by
atmospheric conditions. Also reductions in spectral (band
width) and spatial (pixel size) resolution negatively influence
this ratio. Todays SPOT HRIV and Landsat TM scanners
maintain acceptable s/n ratios with pixel sizes in the range of 10
- 20 m for spectral resolutions in the order of 50 - 100 nm. A
Im resolution is obtained for panchromatic satellite imagery
such as IKONOS. In order to maintain acceptable signal noise
ratios for hyperspectral scanners one has the choice to either
reduce flying height (airborne instead of spaceborne) or
increase pixel size. Airborne hyperspectral scanners, therefore,
combine high spectral and spatial resolution. Spaceborne
hyperspectral scanners such as the MODIS, record high spectral
resolution information at pixel sizes of 250 meters.
2.3 Classification of invasive species
The data captured by remote sensing devices will be most
directly related to the properties of that canopy. We introduced
a classification of species based on their remotely sensed
canopy reflectance response (Figure 2). It is the canopy of an
ecosystem (be it vegetation or fauna) that reflects the electro-
magnetic radiation that is captured by remote sensing devices.
doa ae
Figure 2. Application of remote sensing in detecting individual
invasive species (may be an animal or plant) as represented in
black colour. Class I: Canopy dominating species (top row),
class II: Mixed canopy dominant species (second row), class III:
Invaders influencing canopy dominant species (third row) and
class IV: Understory species (bottom row)
Class I includes species dominating the canopy and forming
homogeneous single species stands. Class II includes species
that are members of a multi species canopy and directly reflects
671
electro-magnetic radiation. Class III includes species not
reflecting, but influencing the reflective properties of canopy
members belonging in class II and I. Class IV finally includes
all species that neither reflect light nor influence the reflective
properties of other species in class I and Il.
2.3.1 Canopy dominating species: Several invasive species
dominate the canopy of the earth surface forming homogeneous
single species stands that extend over larger areas. Included are
a large number of tree species such as Melaleuca
quinquenervia, Miconia calvescens, Tamarix ramosissima,
Acacia mearnsii, Ardisia elliptica, Cecropia peltata, Leucaena
leucocephala, Spathodea campanulata, Ligustrum robustum,
Morella faya, Pinus pinaster and Prosopis glandulosa. Canopy
dominance among invaders is not restricted to tree species, it
also occurs in grasses (e.g. Arundo donax, Spartina anglica),
floating water hyacinth (Eichhornia crassipes) and submerged
aquatic vegetation (Caulerpa taxifolia, Undaria pinnatifida,
Oscillatoria sp.) and among colonial animals such as zebra
mussels (Dreissena polymorpha). Detection of invasive
Prosopis glandulosa var. torreyana and P. velutina using TM
images (Harding & Bate, 1991), Gutierrezia sarothrae with
NOAA-10 low resolution spectral image (Peters et al., 1992),
Kalmia angustifolia (Franklin et al., 1994), Imperata cylindrica
with multispectral high-resolution visible (HRV) images
(Thenkabail, 1999), Carpobrotus edulis, Cordateria jubata,
Foeniculum vulgare and Arundo donax using high spatial
resolution (-4m) AVIRIS data (Ustin et al., 2002), Cynodon
dactylon with aerial video and colour-IR photographs (Everitt
& Nixon, 1985a), Populus tremuloides clones using hand-held
video (Stohlgren et al., 2000) are some of the examples of
mapping canopy dominating species.
Several of those studies have used aerial photography,
videography and multispectral scanners for identifying and
mapping invasive species. Everitt et al. (2001a), who used aerial
photographs to discriminate Acacia smallii, Tamarix chinensis,
Gutierrezia sarothrae and Astragalus wootonii, noted the
importance of differences in canopy architecture, vegetative
density and leaf pubescence for the mapping of invasive
species. Venugopal (1998) used SPOT multitemporal data to
monitor the infestation of Eichhornia crassipes (water hyacinth)
using Normalised Difference Vegetation Index (NDVI).
Shepherd & Dymond (2000) presented a method for correcting
AVHRR visible and near-infrared imagery which can be used in
detecting indigenous forest, exotic forest, scrub, pasture and
grassland. Anderson et al. (1993) mapped Ericameria
austrotexana infestation in a large homogenous area using
Landsat TM imagery. Anderson et al. (1996) found GIS and
remote sensing to be a powerful combination tools that
provided information about the extent and spatial dynamics of
significant association of leafy spurge with drainage channels.
Everitt & Nixon (1985a) applied airborne video and colour-IR
photographs to detect infestation by Acacia smallii and
Prosopis glandulosa. Everitt et al. (1992) applied airborne
video imagery, for distinguishing Tamarix chinensis,
Ericameria austrotexana and Aster spinosus. Everitt & Nixon
(1985b) used a multi-video system to assess ground conditions
infested with Stemodia tomentosa, Paspalum lividum and
Cynodon dactylon.
Some of the reported invasive species dominate submerged
aquatic ecosystems. For those ecosystems, remote sensing
methods described so far, are limited, because little light is
reflected back by submerged organisms. Budd et al. (2001) used
Advanced Very High Resolution Radiometer (AVHRR) remote
RR rues
