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the construction of confidence limits. Subsequent work has 
attempted to revise this technique. 
Later methodological articles criticize the use of the 
normal approximation suggested by Hord and Brooner. Beyond 
the call for appropriate discrete distributions, such as the 
binomial, to construct confidence intervals, the recurrent 
issue is sampling design. Van Genderen and Lock (1978) 
suggest a procedure for picking sample sizes based on the 
number of errorless results needed to support assertions of 
confidence. Ginevan (1979) points out that errorless 
results are not the only ones which might support a given 
level of accuracy. The goal is to minimize sample size 
while minimizing both Type I and II errors. 
This line of research has refined statistical hypotheses 
about map accuracy, but these concerns do not coincide with 
most application needs. Hay (1979) provides a thorough 
criticism of the normal approximation for confidence 
intervals of proportions, but considers the revised method 
as only a starting point. The total proportion correct 
addresses merely the first of his five questions: 
I What proportion of decisions are correct? 
II What proportion of allocations to a category are correct? 
III What proportion of a true category is correctly 
allocated? 
IV Is a category overestimated or underestimated? 
V Are errors randomly distributed? (Hay,1979,p.529) 
Hay's questions lead towards the methods developed below. 
The use of percentage correct has been thoroughly criticized 
also by Turk (1979). He demonstrates that figures of 
percentage correct are inflated, even a random process would 
be expected to achieve a positive value. Turk's alternative 
involves the use of much more sophisticated statistical 
estimation discussed below. Alternatives that address bias 
correction problems have been developed in the crop 
estimation literature (such as Bauer and others, 1978), but 
they deserve broader application. 
CRITIQUE OF A SAMPLE APPLICATION 
In order to demonstrate the problems of the standard 
percentage correct approach, a sample application is needed. 
Attention will focus on an article by Todd, Gehring and 
Haman (1980) [hereafter TGH] in which they assess the 
accuracy of Landsat for mapping a wild area for the National 
Park Service. The choice of this study is fortuitous and 
does not imply that it is worse or better than many others. 
The TGH project began by developing a ten class map of the 
Shivwits Plateau by means of accepted remote sensing tools. 
The ten class map resulting was labelled with particular 
names combining physiographic features with vegetation type 
and degree of cover, but these names are tags assigned by 
human operators, not the basis for the classification. No 
matter what the pure or unpure multispectral nature of these 
classes, the use of the classification hinges on the