390 
for harvest scheduling and for managing control 
programs. Low resolution linear array imager 
data with optimized wavelength bands may provide 
suitable information. Change detection techniques 
using airborne imager data have tremendous 
potential for detection, delineation and 
quantification of insect and disease damage. 
MEIS II data has been successfully used 
to detect spruce budworm defoliation (Ahem et aL, 
1985; Epp and Reed, 1986; Ahem et aL, 1986). 
Ahem et aL, (1986) compared MEIS and airborne 
MSS systems and found that improved detection of 
defoliation caused by spruce budworm damage was 
obtainable with the MEIS imagery. The 
differences between the MEIS and airborne MSS 
performances was traced primarily to a difference 
between the widths and placements of their 
spectral bands, particularly the red band. The 
greater signal-to-noise ratio of MEIS compared to 
that of airborne MSS was also important. 
Epp and Reed (1986), conducted a 
comparison of MEIS and TM data for spruce 
budworm infestation detection and found that more 
accurate maps of damage could be obtained from 
these sensors when compared to traditional aerial 
sketch mapping. The ability to detect budworm 
infestation with the MEIS sensors was higher than 
TM due improved spectral band placement, narrow 
band widths, and greater signal-to-noise ratio. 
4.4 Sampling Systems 
Sampling of forest parameters is 
appropriate for acquiring quantitative data for 
forest inventory, forest change, and insect and 
disease damage. The flexibility of linear array 
imagers, particularly, their flexible resolution (e.g. 
from 0.25 to 10 m) and choice of spectral bands, is 
advantageous for forest sampling. The use of an 
inertial navigation (INS) or global positioning 
(GPS) system to locate sample areas for data 
acquisition and to geometrically correct the data to 
cartographic coordinates makes linear array imager 
data ern excellent tool for stratifying, sampling and 
quantifying forest parameters. Linear array imager 
data could be an integral part of an integrated 
forest monitoring system incorporating new and 
sophisticated satellite remote sensing techniques, 
multistage or multiphase sampling with airborne 
imagery, ground sampling, GIS technology, expert 
systems, and knowledge of forest management 
activity. 
4J5 Regeneration Assessment 
There are a number of possible roles for 
airborne linear array sensors for regeneration 
assessment, including site assessment for 
reforestation and monitoring juvenile stands for 
problems such as poor survival and excessive 
competition. Some of the first imagery acquired 
with the MEIS II was of a test regeneration area 
of the Petawawa National Forestry Institute in 
Ontario and showed considerable potential for 
softwood species discrimination (Leckie and 
Dombrowski, 1984). 
Kneppeck and Ahem (1987) found that 
trees as young as 6 years could be detected using 
1 m MEIS data. They also found that although 
the spatial resolution of MEIS data (1 m) was 
much coarser than 1:10,000 photography (0.19 m) 
the increased radiometric and spectral resolution 
of the MEIS data provided additional data which 
offset its lower spatial resolution. The MEIS data 
were able to detect regeneration at lower conifer 
densities than the colour photography and provide 
better separation into density classes. The MEIS 
data was able to separate regenerating stands into 
three meaningful conifer density and three 
meaningful brush density classes and was more 
sensitive to brush competition than conventional 
photography. 
These results indicate that MEIS data can 
be used to detect free-to-grow areas and areas 
with serious brush competition (NSR). The data 
can also be used to indicate conifer density and 
identify problems such as compacted soils. 
4.6 Waste Surveys 
Although little research has been done on 
the use of airborne linear array data for waste 
survey assessments the ability to obtain high 
spatial resolution data suggests that such data 
may be able to be used for such purposes. 
5.0 CONCLUSIONS AND 
RECOMMENDATIONS 
5.1 Conclusions 
Three airborne linear array systems 
available in Canada (MEIS, FLI and CASI) have 
been introduced and evaluated for their operational 
feasibility for a variety of forestry applications. 
Although these sensors are based on similar linear 
array technology the unique design of each system 
provides very different functionalities which makes 
each suitable for different applications. 
The MEIS II sensor was designed as an 
operational airborne system and consequently it 
incorporates advanced mapping capabilities such as 
inflight precision geo-referencing using inertial 
navigation data, stereo data acquisition to allow 
terrain correction from digital elevation models 
(OEM’s) and powerful inflight and post-flight data 
processing facilities to provide rapid turn-around 
from data acquisition to final product generation. 
The FLI and CASI systems, on the other 
hand, have not yet been developed to an 
operational level. These systems are currently 
used primarily for research-oriented applications. 
The two-dimensional design of these systems, 
however, represents a significant advancement in