3. Continued halving the time series in this way until 
a time span of a week or so was reached. Images 
were then viewed sequentially by day, using the 
definite ice-off image for reference. 
Certain weather events helped and hindered 
lake ice classification. Recent snowfall helped 
greatly, showing a sharp distinction between ice- 
covered lakes and surrounding land (covered with 
highly-reflective fresh snow) and open water (having 
melted the newly-fallen snow). Cloud shadow 
hindered classification, by making lakes appear 
much darker than on the preceding cloudless day. 
Due to the uncertainty, we classified these 
cloud-influenced days as cloudy days. 
Some of the lakes were easily identifiable as 
snow-covered lakes, but difficult to identify as open 
water. They never appeared as dark as others, even 
months after ice-off on surrounding lakes. This 
phenomenon of unachieved "darkness" varied over 
the years for these lakes, and wasn't absolutely 
related to lake size, although it was more common 
on smaller lakes. A possible explanation is sensor 
falloff of the GOES with increasing latitude. 
2.5.2 Locational Control 
Consistent location of each of the eighty-one 
lakes selected for the study was critical. While 
interpreting the first few years of images, atlases 
containing sufficiently large-scale maps were relied 
on to ensure that the correct lake was being 
interpreted. After viewing a thousand images or so, 
locating lakes became easier, especially in relation to 
easily-identifiable lakes and lake-patterns in a 
region. Still, we referred to atlases in instances of 
any uncertainty. 
One potential difficulty in the interpretation 
was locating lakes when they had the same 
reflectance as surrounding land, and were thus hard 
tolocate in the image. This can be seen in Figure 2 
(previous page), where Trout Lake is unidentifiable 
in some of the images. This was overcome by 
overlaying the ambiguous image with a reference 
image where the lake is easily identified (ice-on or 
ice-off), using the multiple-window viewing capacity 
of Imagine. The two (or more) images were spatially 
matched using points identifiable on all images, 
usually angular shorelines of nearby lakes. 
90 
This simple overlay of images was possible 
due to the geostationary positioning of the GOES 
satellite. Rotation or scale changes in the GOES 
image resulted in differences of only a few pixels 
across the whole image from day to day, making 
2-dimensional translation the only necessary image 
transformation. However, cumulative changes over 
weeks necessitated a local fit (100-400,000 km? at a 
time) for overlaying temporally-disparate images. 
2.6 Classification Bias 
As we progressed with the interpretation, 
comparison of interpreted ice-off dates to reference 
ice-off dates from ground observation confirmed a 
tendency to interpret lakes as ice-off earlier than 
they actually were. This is probably due to the 
difficulty mentioned previously, in differentiating 
between bare ice and open water. This echoes 
similar findings by Maslanik and Barry (1987) and 
Wynne and Lillesand (1993). Figure 3 and Table 1 
(next page) show a comparison for the five lakes for 
which ground reference data were available. The 
mean absolute difference between interpreted ice-off 
and reference ice-off was 3.2 days and the mean 
difference was -0.4 days, meaning interpreted ice-off 
preceded actual ice-off on average. 
N o N a 
Mean Difference (Days) 
À 
  
-6 
1980 1982 1984 1986 1988 1990 1992 1994 
Year 
Figure 3 Mean Difference between GOES- 
Derived and Reference Ice-Off 
Dates for Subset of Study Lakes 
In light of this bias, we were faced with the 
decision whether to correct our interpretation bias 
during the interpretation, or “call them as we see 
them” and deal with any bias in the statistical 
analysis. We chose to do the latter, maintaining our 
  
1992 1993 1994 Abs. Mean Mean 
1987 1988 1989 1990 1991 
1986 
1984 1985 
1981 1982 1983 
1980 
Lake