Table 
2. SPOT Accuracy 
Assessment 
Error 
Matrix for Land use and 
SPOT CLASS IFIC ATI0M 
Land 
Cover 
Mapping 
Ground Wl 
Tru th 
W2 
w3 
Ul 
U2 
CFl 
MF 1 
CPI 
Al 
A 2 
FI 
F2 
F3 
F4 
F5 
Total 
Omission 
Accuracy 
UI 
1ST - 
0 
3 
—¡3— 
0“ 
“13— 
—a - 
0 
a— 
d 
0 
u 
0 
0 
161 
5.0 
95.0 
W2 
65 
0 
0 
0 
0 
0 
0 
0 
0 
0 
0 
0 
0 
0 
65 
0.0 
100.0 
W3 
0 
~TT 
29 
0 
0 
0 
0 
0 
0 
0 
0 
0 
0 
0 
0 
29 
0.0 
100.0 
Ul 
0 
0 
U 
44 
1 
0 
11 
0 
0 
0 
2 
1 
0 
0 
0 
59 
25.4 
58.7 
U2 
0 
0 
0 
u 
33 
2 
0 
1 
0 
0 
0 
0 
0 
0 
0 
36 
0.9 
86.8 
CFl 
0 
0 
0 
0 
U 
225 
0 
0 
0 
2 
0 
0 
0 
0 
0 
227 
1.1 
88.2 
NF1 
0 
0 
0 
4 
0 
42 
0 
0 
0 
0 
0 
0 
0 
0 
50 
16.0 
53.2 
CPI 
0 
0 
0 
0 
0 
2 
0 
104 
9 
15 
5 
0 
0 
5 
0 
140 
25.7 
65.4 
Al 
0 
0 
0 
0 
0 
0 
0 
O’ 
76 
0 
0 
0 
0 
4 
2 
32 
7.3 
77.6 
A2 
0 
0 
0 
0 
0 
20 
0 
0 
T 
148 
0 
0 
0 
0 
0 
158 
11.9 
80.0 
FI 
0 
0 
0 
3 
l 
0 
15 
2 
0 
~U 
139 
6 
0 
1 
0 
167 
12.0 
79.9 
F2 
0 
0 
0 
5 
0 
0 
3 
0 
0 
0 
-a 
570 
6 
1 
3 
538 
3.1 
94.7 
F3 
0 
0 
0 
0 
0 
0 
0 
0 
0 
0 
0 
5 
223 
0 
1 
230 
3.0 
94.5 
F4 
0 
0 
0 
4 
0 
0 
0 
16 
1 
0 
0 
1 
~U 
210 
4 
236 
10.2 
83.3 
F5 
0 
0 
0 
0 
0 
0 
0 
0 
6 
0 
0 
0 
0 
— 5 
188 
199 
5.5 
90.0 
Total 
153 
65 
37 
50 
35 
253 
71 
123 
92 
165 
146 
584 
229 
226 
198 
2437 
Commi ss ion 
0 
0 
0 
27.2 
12.3 
36.4 
58.0 
13. 
5 19.5 
10.1 
4.07 
2.4 
2.6 
6.8 
5.0 
% 
Overall Accuracy (2249;-2437 ) = 92.3% 
classification (disregarding human intervention errors), individual 
classes should be inspected for agreement with the ground truth data and 
the extent of the commissions determined. 
The deep to very deep water (Wl); moderately deep to deep water (W2); 
very shallow to shallow water (W3), sparse urban and barren, rocky land 
(U2); alluvial cultivated and eroded land (A2); sparse to moderately 
dense caatinga forest (F2); moderately dense to dense caatinga forest 
(F3); dense caatinga forest on undulating land (F4) and dense mixed 
caatinga forest on hills (F5) classes produced the best results in terms 
of high percentage agreement with ground truth data (80.0-100.0%) and 
relatively low percent commissions (0.0-12.3%). This shows that digital 
data of these classes are spectrally homogeneous and can be discriminated 
readily from other classes. Other classes such as dense urban area (U1), 
mixed cultivated and fallow land (NF1), and mixed cultivated and pasture 
(CPI) are more spectrally heterogeneous and explain the lower overall 
classification accuracies and high commission percentages. 
The cotton cultivated and fallow land (CF1) and alluvial land with dense 
shrubs/trees (Al) classes also yielded a high agreement relative to the 
ground truth data (88.2% and 77.6%). The corresponding percentage 
commissions, however, were higher at 36.4 % and 19.5%, respectively. 
Most commission errors for the cotton cultivated and fallow land and for 
alluvial land with dense shrubs/trees were due to confusion with the 
alluvial cultivated eroded land and the mixed cultivated and pasture 
classes. This was due to the spectral variability and sometimes 
similarity among these classes. 
The lowest classification agreement was for the dense urban area (Ul) 
(58.7%), mixed cultivated and fallow land (MF1) (53.2%), mixed cultivated 
and pasture (CPI) (65.4%), and for the sparse caatinga forestland (FI) 
(79.9%) classes. The percent commissions for sparse caatinga forest and 
rocky land was quite low (4.1%), whereas the percent omission was 
relatively high (12.0 %). The errors of commission for dense urban area 
354