617 
5.2 Colour infrared air photographs 
The colour infrared photographs depict terrain 
conditions during early spring, prior to the 
emergence of crons. Soil conditions are therefore 
better exposed than in the panchromatic air photos. 
The six major photomorphic units which were not 
clearly defined or identified in previous studies 
include;(^hoto 1): 
a. Linear features representing deposits and 
landforms associated with the paleocoastal environ 
ment of proglacial lakes: viz. beaches, sand bars, 
snits, troughs. 
b. Convoluted features representing ice-collapse 
glacio-lacustrine sediments. 
c. Elongate to irregularly shaped paleo-dunes, 
d. Contemporary flood-plain of the Thames River. 
e. Moraine ridges. 
f. Hummocky moraine pitted with kettles, 
5.3 Digital Imagery 
a. Selection of Optimal band triplet 
The selection of three ODtimal bands was achieved 
using a ranking technique suggested by Sheffield, 
(1985). The top ranked 3 bands are CH05 (456.5-517 
nm), CHOO (522-735 nm) and CHOI (793-893 nm). 
Imagery from these bands were subjected to contrast 
enhancement and spatial filtering prior to the 
visual interpretation of composite images. 
b. Contrast enhancements 
Histogram-equalization stretch enhancement provided 
the best results for visual analysis of displays 
of colour composites formed using the optimal band 
triplet. 
c. Spatial filtering 
Best results were obtained using high-boost filtering. 
The enhanced image was particularly useful for 
accentuating the convoluted textures of ice-collapse 
glaciolacustrine deposits and the boundaries of 
paleo-dunes. 
d. Principal component transformation 
A principal component transformation (Jenson and 
Waltz, 1979), provided discrimination of surficial 
material and geomorphology equal to that of the 
optimal three band colour composite. 
e. Band ratioing 
After elimination of the four highest correlated 
bands, the four remaining bands (CHOO, CHOI, CH02, 
CH05) were used to construct six unique band-ratio 
images. Best results for discrimination of 
surficial material, soil patterns and drainage 
features were obtained using band ratio CH02 (green)/ 
CH05 (blue). 
Enhanced digital images particularly the histogram- 
equalisation stretch and band ratioing contributed 
to better identification and image expression of 
photomornhic units and their boundaries. They have 
been particularly useful for verification of infor 
mation derived from the analysis of CIR photographs. 
The increased detail present in enhanced images 
does not always contribute positively to the recog 
nition of surficial material. Local features of 
conditions such as variations in moisture content, 
humus content, soil erosion, micro-relief and 
plowing, can cause additional information noise 
after enhancement, leading to large number of 
photomorphic units. This must be taken into account 
during geological interpretation. An increase in 
the apparent number of' photomorphic units does not 
necessarily represent the number of truly separable 
geologic units. 
In summary, the best analytical approach for 
surficial geology mapping and aggregate exploration 
was obtained through the analysis of colour infrared 
photographs complemented by MEIS-II multispectral 
data. Timing of the imagery acquisition, scale of 
the imagery and availability of ancillary data were 
important factors in subsequent data analysis, Such 
factors must be carefully examined when advanced 
remote sensing systems are considered as technical 
aids in similar studies. 
REFERENCES 
Chapman, L. J. & D. F. Putnam 1984. The physiography 
of southern Ontario. Ontario Geological Survey. 
Special, vol. 2, pg. 270. 
Jenson, S. K. & F. A. Waltz 1979. Principal 
component analysis and canonical analysis in 
remote sensing. Proc. of the American Society 
of Photogrammetry. 45th Annual Meeting. March 18- 
24. Washington. D C., pg. 337-348. 
Till, S. M., McColl, W. D. and Neville, R. A., 
1983. Development, field performance and evalua 
tion of the MEIS-II multi-detector electro- 
optical imaging scanner. Proceedings, Seventh 
International Symposium on Remote Sensing of the 
Environment. Ann Arbor, Michigan, preprint. 
Sheffield, C. 1985. Selecting band combinations from 
multispectral data. Photogrammetric Engineering 
and Remote Sensing. 51:681-687.