In: Wagner W., Szekely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
433 
and visible red bands and positive correlations among the 
visible bands because the spectral characteristics of land use are 
such that as the vigour or tone of the feature increases, the red 
reflectance diminishes and the near-infrared reflectance 
increases. 
4.2 Landuse Classes 
Table 4, 5, and 6 contain summaries of the results accuracy 
assessment generated from the three images on the five land 
use. The overall, user as well as producer accuracies of 
individual classes were consistently high for the three 
imageries. The accuracies for Landsat, NigeriaSat-1 and SPOT 
were 66.5%, 81.2% and 82.8% respectively. The Kappa 
statistics were 0.87, 0.97 and 0.89 respectively. The user and 
producer accuracies of individual classes in Landsat ranged 
from 51.9% to 87.3%, whereas in NigeriaSat-1, they varied 
from 60% to 97.3% and in SPOT from 74.7% to 89%. On 
Landsat image for the ‘built-up area’ category of land use, the 
producer accuracy is 82.8% and the user is 87.3%. This means 
that more than 80% of the built-up area in the image was 
correctly defined and mapped. The other four land use classes 
i.e. bare rocks, farm land; secondary forest regrowth forest and 
water body had relatively low producer and user accuracies. For 
instance secondary forest regrowth has a producer accuracy of 
66.5% and user accuracy of 51.9%. The four categories are thus 
not as well defined as the built-up areas. The ‘built-up area’ of 
NigeriaSat-1 had the highest accuracy on producer accuracy 
(97.3%), it also had user accuracy of 96.9%. On the SPOT 
image, the statistics on built-up area category are 81.98% for 
producer accuracy and 91.58% for user accuracy. 
It appears that Landsat has lower value for accuracies than 
either SPOT or NigeriaSat-1. Different reasons may be 
responsible for this outcome. One reason may have to do with 
the intrinsic characteristics of the images. For instance Landsat 
has a spatial resolution of 30metres, NigeriaSat-1 32 metres and 
the SPOT lOmetres. Chen, et al., (2004) has shown that these 
can variously have effect on the levels of accuracies obtained 
from the images. Another reason could be that, spectral 
characteristics among the different land cover types (e.g. built- 
up, bare rock) are similar, while spectral variation within the 
same land cover type or even within the same image might be 
high (Cushine, 1987). 
TABLE. 4 ACCURACY ASSESSMENT OF LANDSAT TM IMAGERY 
Sat 
ellit 
Cla 
ssifi 
Reference Data 
Re 
f. 
Cl 
Nu 
mb 
PA 
% 
UA% 
Kappa 
e 
Ima 
ge 
ed 
Data 
Bu 
ilt- 
up 
Ar 
% 
Ba 
re 
Ro 
ck 
% 
Fa 
rm 
lan 
d 
% 
Se 
c. 
Fo 
res 
t 
% 
Wa 
ter- 
bod 
y 
% 
To 
tal 
To 
tal 
Cor 
rect 
% 
Lan 
Buil 
82. 
5.6 
4.6 
1.1 
0.6 
10 
94. 
82. 
82. 
87. 
1.00 
dsat 
t-up 
Area 
79 
0 
7 
5 
7 
0 
88 
79 
79 
26 
00 
Bar 
8.2 
58. 
12. 
8.2 
4.5 
10 
91. 
58. 
58. 
63. 
1.00 
e 
rock 
6 
84 
13 
1 
2 
0 
96 
84 
84 
98 
00 
Far 
7.0 
19. 
52. 
12. 
0.9 
10 
91. 
52. 
52. 
56. 
1.00 
mlan 
d 
2 
14 
15 
29 
0 
0 
50 
15 
15 
99 
00 
Sec. 
1.7 
9.4 
29. 
66. 
21. 
10 
128. 
66. 
66. 
51. 
0.86 
fores 
t re 
grow 
th 
9 
1 
21 
49 
14 
0 
04 
49 
49 
93 
01 
Wat 
0.1 
8.0 
1.8 
h. 
72. 
10 
94. 
72. 
72. 
76. 
1.00 
er 
body 
5 
2 
4 
87 
76 
0 
64 
76 
76 
89 
00 
Overall Landsat Classification Accuracy = 66.47% (i.e. 82.79+58.84+52.15+66.49+72.76 ), 
Overall Kappa Statistics = 0.8714 
501.02 
TABLE. 5 ACCURACY ASSESSMENT OF NIGERIA SAT-1 IMAGERY 
TABLE . 6 ACCURACY ASSESSMENT OF SPOT IMAGERY 
Land Cover Types 
Built-up Area 
Bare rock 
Farm land 
Sec forest regrowth 
Water body 
10 e Id 20 30 
Fig2: Classified print of the Landsat TM image