Full text: Proceedings of the Symposium on Global and Environmental Monitoring (Part 1)

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The advantages of the newer generations of 
airborne linear array systems include: high 
spatial resolution, good radiometric resolution and 
sensitivity, flexible wavelength choice and the 
ability to use narrow wavelength bands. Some 
linear array systems also offer the ability to 
produce stereo images from which tree and stand 
height estimates should be possible. 
Another technological advance is the 
incorporation of high qualify inertial navigation 
data with airborne linear array data to permit 
more efficient and accurate geometric correction to 
cartographic coordinates. Linear array data and 
forest interpretation can then be input directly 
into a cartographically accurate forest inventory 
database on a geographic information system. In 
fact, with stereo capability it may be feasible to 
produce more accurate base maps using geo- 
referenced imagery and digital terrain models 
created from stereo linear array data. 
The following sections describe in more 
detail the unique characteristics, advantages and 
disadvantages of airborne linear array sensor 
systems. 
2.1 Spatial Resolution 
The spatial resolution of airborne linear 
array data can be much higher then equivalent 
satellite-based systems and consequently airborne 
imagery can used as a viable alternative to 
medium-scale aerial photography. For forestry 
applications this means that stand-specific or even 
tree-specific information can be obtained from 
airborne imagery. 
The spatial resolution of these systems is 
determined by the field of view and the aircraft 
altitude. The MEIS II system, for example, can 
provide data at resolutions ranging from 0.25 to 
10 meters. For forestry applications where 
information is often required at a variety of scales, 
from reconnaissance mapping to detailed forest 
measurements, imagery can be acquired at spatial 
resolutions appropriate for each specific 
application. In addition, this flexibility to choose 
spatial resolution makes airborne linear array 
imagery an ideal data source for multistage or 
multiphase sampling purposes. 
2.2 Spectral Range 
For forestry applications where 
information on the vigour or condition of the 
vegetation is important there is often a need to 
use imagery acquired beyond the visible range in 
the middle-infrared portion of the electromagnetic 
spectrum. The MEIS sensor with a spectral range 
from 390 - 1100 nm can provide data in the 
important middle-infrared region. 
The FLI and CASI systems, on the other 
hand, were designed primarily for ocean 
applications and consequently are only able to 
provide data in the visible and near-infrared 
portions of the spectrum from 430 - 805 nm. 
There are plans to modify the CASI system to 
accommodate different sensor heads which would 
extend its spectral range farther into the infrared 
region (G.A. Borstad, personal communication) 
which would make these systems more suitable for 
forestry applications. 
2.3 Spectral Resolution 
Spectral resolution (the number and width 
of spectral bands that can be selected) is controlled 
in one-dimensional linear array systems (e.g. 
MEIS) through interchangeable optical filters and 
in two-dimensional systems (e.g. FLI and CASI) 
through diffraction gratings. 
The MEIS sensor acquires imagery in up 
to eight spectral bands. Various sets of spectral 
filters are available for the MEIS system which 
have been optimized for specific applications, such 
as SPOT and TM simulations, stereo applications 
and forestry. Of particular interest for forestry 
have been the filter sets for vegetation stress 
studies (incorporating passbands of 3 nm width 
located on the chlorophyll red reflectance edge) 
which have provided more accurate forest insect 
and disease damage assessments (Kneppeck and 
Ahem, 1989; Epp and Reed, 1986). 
The vegetative red reflectance edge, which 
occurs in the 650-800nm spectral region, has 
received increased attention during the past 
several years as a potential indication of vegetative 
stress (McColl et aL, 1983). The ability to produce 
filters which isolate spectral bands as small as 
3nm in this region provides the potential to detect 
very small spectral changes in the reflective red 
edge which could be important for early detection 
of vegetative stress resulting from insect or disease 
damage. 
The disadvantage of using optical filters to 
obtain spectral bands is the time required to 
determine the appropriate spectral range for each 
filter (usually accomplished by using data from 
non-imaging spectrometers) and the time and cost 
involved in manufacturing the appropriate filters. 
As imaging spectrometers, the FLI and 
CASI systems, have the ability to image 288 
bands. For the FLI system each band can be as 
close as 1.3 nm and as narrow as 2.5 nm (Buxton, 
1988). The CASI system can image 288 bands as 
narrow as 1.8 nm (Gower et al., 1987), when 
operating in its "spectral" mode. The spectral data 
from these bands can be used to examine and 
analyze the spectral signature of a target. The 
spectral signature can be important in helping to 
determine optimal spectral band width and 
positioning for use in acquiring high spatial 
resolution data. When acquiring data in the 
"spatial mode" eight spectral bands can be
	        
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