372 
TABLE 1 
Landsat Thematic Mapper Bands and Transformations Used in 
Statistical Analysis 
Band 1 
Band 2 
Band 3 
Band 4 
Band 5 
Band 7 
(TM1) Landsat TM Band 
(TM2 ) 
(TM3) 
(TM4) 
(TM5 ) 
(TM7) 
Band 4 - Band 1 
Band 4 - Band 2 
Band 4 - Band 3 
Band 4 - Band 5 
Band 4 - Band 7 
(BD1) Band Difference 
(BD2) 
(BD3) 
(BD5) 
(BD7) 
Band 4/Band 1 
Band 4/Band 2 
Band 4/Band 3 
Band 4/Band 5 
Band 4/Band 7 
Band 2/Band 3 
Band 3/Band 1 
Band 5/Band 7 
(R41) Simple Band Ratio 
(R42) 
(R43) 
(R45) 
(R47) 
(R23) 
(R31) 
(R57) 
(Band 4 - Band 
(Band 4 - Band 
(Band 4 - Band 
(Band 4 - Band 
(Band 4 - Band 
0.3037(TM1 ) + 
+0.5585(TM4) + 
-0.2848(TM1) - 
+0.7243(TM4) + 
0.1509(TM1) + 
+0.3406(TM4) - 
1) /(Band 4 + 
2) /(Band 4 + 
3) /(Band 4 + 
5)/(Band 4 + 
7)/(Band 4 + 
0.2793(TM2) + 
0.5082(TM5) + 
0.2435(TM2) - 
0.0840(TM5) - 
0.1973(TM2) + 
0.7112(TM5) - 
1) (ND1) Normalised Difference 
(ND2) 
(ND3) 
(ND5 ) 
(ND7) 
Band 
Band 2) 
Band 3) 
Band 5) 
Band 7) 
0.4743(TM3) 
0.1863(TM7) 
(TMB) 
0.5436(TM3) 
0.1 800(TM7) 
(TMG) 
0.3279(TM3) 
0.4572(TM7) 
(TMW) 
1 
Brightness Index 
1 
Greenness Index 
1 
Wetness Index 
First Principal Component (PC1 ) 
Second Principal Component (PC2) 
Third Principal Component (PC3) 
Source: 1. Crist (1983) 
and r=-0.77 for the June and August Austrian 
scene dates. These and all other regression 
relationships that exhibit at least a "fair" 
correlation (r > 0.50) are significant at 
greater than the 99 per cent level of pro 
bability . 
Two methods were used to rank the effec 
tiveness of the Thematic Mapper bands and 
transformations in discriminating metal 
stress in coniferous forests: the first ap 
proach involved the simple ordering of the 
Pearson product moment correlation coeffi 
cients (r-values) for each of the seven soil 
metal values and combinations (lead, zinc, 
copper, lead + zinc, lead + copper, zinc + 
copper, and lead + zinc + copper) and thirty- 
one bands and transformations for each of 
the four Landsat scene dates (a total of 28 
data sets), whereas the second approach con 
sisted of calculating the weighted frequency 
sums of the thirty-one bands and transforma 
tions for each of the 28 data sets to obtain 
a "rank sum value" for each TM band and 
transformation for each scene date. Both 
methods yielded essentially identical re 
sults in defining the individual rank posi 
tions of the TM bands and transformations 
and their groupings. TABLE 2 presents the 
results of this analysis. The division of 
the bands and transformations into four 
groupings is arbitrary and based solely on 
the similarity in the "rank sum values" of 
the group members. The range of values re 
presented by each of the four groups is 
approximately the same for each correspond 
ing scene date group. Only the top-ranked 
14 or 15 TM bands and transformations for 
each scene date are presented in TABLE 2, as 
it is from these that the best ten bands and 
transformations based on all four scene 
dates are compiled. 
The highest ranked TM bands and trans 
formations for both the June and August scene 
dates of Austria show a close correspondence 
to each other, which is not the case with 
respect to the January and August Spanish 
scene dates. 
The five TM bands and transformations 
comprising Group I of the combined Spanish 
and Austrian scene dates are ranked also 
within the top 14 or 15 bands and transfor 
mations of each of the four individual scene 
dates; those listed in Group II are repre 
sented in the upper ranks of only three of 
the four scene dates. The two top-ranked 
transformations in Group I (PC1 and BD1) are 
essentially identical in their discriminat 
ing power, as are the third and fourth ranked 
TMB and TM5. 
4. DISC 
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