849 
Table 1. Portions of overbuilt and vegetated areas and mean values of the radiation temperature of different 
urban-land-cover-types in % of the total test area; area delineation and calculation by Karin Fera. 
Test area 
area 
in ha 
over 
built 
area 
vege 
tated 
area 
buil 
dings 
traf 
fic 
areas 
other 
overb. 
areas 
trees 
bushes 
mea 
dows 
mean 
radiat. 
temper. 
1 
Medieval inner city 
8,8 
88 
12 
56 
21 
11 
5 
1 
6 
26,03°C 
2 
Renaissance inner city 
8,3 
95 
5 
52 
33 
10 
3 
0 
2 
25,29°C 
3 
Old suburb buildings 
1,6 
73 
27 
42 
11 
20 
11 
3 
13 
25,57°C 
4 
House-blocks end 19th 
century 
3,6 
69 
31 
43 
4 
22 
15 
3 
13 
24,82°C 
5 
Better single-family- 
house area 
7,9 
33 
67 
14 
10 
9 
21 
11 
35 
22,90°C 
6 
House-blocks 1939/40 
12,0 
46 
54 
22 
11 
13 
14 
5 
35 
21,42°C 
7 
Simple single-family- 
house area 
5,1 
35 
65 
17 
10 
8 
24 
8 
33 
21,35°C 
8 
New suburban house- 
blocks area 
17,4 
34 
66 
12 
14 
8 
5 
2 
59 
22,66°C 
9 
Old village kernel with 
new single-family-houses 
7,9 
30 
70 
14 
6 
10 
18 
6 
46 
23,16°C 
only very few rules of thumb, no procedures and it is 
mostly left to the scientist's knowledge and luck to 
find the right mixture of these three things to get 
the desired results. 
3 RADIATION TEMPERATURE DISTRIBUTIONS OF DIFFERENT 
URBAN-LAND-COVER-TYPES 
Pure land use classes covering large areas like forest 
or fields are easy to delineate in thermal images 
because of their homogeneneous temperature distribu 
tions. Not so are the manyfold mixed structures in 
urban environment. To find out something about these 
complex classes nine test areas representing nine 
types of urban-land-cover were selected. With the help 
of largescale infrared aerial photographs the areas 
of the pure cover classes overbuilt areas (subdivided 
into buildings, traffic areas and other overbuilt 
areas) and vegetated areas (subdivided into trees, 
bushes and meadows or grass) were delineated and mea 
sured. The results are listed in table 1. On the other 
hand the same test areas were delineated in the thermal 
image and radiation-temperature-value-histograms 
aggregated into one degree temperature classes (30 
classes because the sensor was calibrated between 
10 and 40° C) and the arithmetic mean values were 
calculated (table 1). 
Applying cluster analysis (SPSS-X procedure Cluster 
and Quick Cluster) to group the nine test areas into 
urban structure types using three variable groups 
(temperature-value-histograms, percentage overbuilt 
and vegetated area, percentages of the six pure cover 
classes) no corresponding classification could be 
found (see table 2). This fact is due for the most 
part to the effects of shadows, different roof materi 
als and differing viewing angles. To the variable 
groups "percentage overbuilt vegetated area" and 
"percentage of pure cover classes" the three error 
reasons are not applicable. The differences in clus 
ter membership between these two variable groups are 
due to the varying percentages of the pure classes 
in the vegetated areas. In this example the level of 
generalization of the 30 temperature classes in the 
histogramm data, which were strongly influenced by the 
three error sources mentioned above, was not adequate 
to answer the question if it was possible to explain 
the overbuilt - vegetation proportion of urban-land- 
cover-types by the radiation temperature distribution 
of the same test area. Also the method (the cluster 
procedure) was not optimal. 
A better method and a better level of generalization 
to show such a relation is to use the arithmetic 
mean value of every test area and to correlate it 
with the proportions of the land-cover-classes. The 
results of this procedure are listed in table 3. We 
see that the proportions of overbuilt and vegetated 
Table 2. Clustermembership of the urban-land-cover- 
types named in table 1, using different variable sets 
for clustering into 4 groups. 
No. of 
temperature 
% overbuilt 
% of six 
ur-la- 
value-class 
and vegeta- 
pure land- 
co-type 
histogramms 
ted area 
cover types* 
1 
1 
1 
1 
2 
1 
1 
1 
3 
1 
2 
2 
4 
1 
2 
2 
5 
2 
3 
3 
6 
3 
4 
3 
7 
3 
3 
3 
8 
4 
3 
4 
9 
2 
3 
4 
* buildings, traffic areas, other overbuilt areas, 
trees, bushes, meadows. 
Table 3. Correlation between mean radiation tempera 
ture values of the 9 test areas and the 8 land-cover- 
class percentages (see table 1). 
Land-cover-class 
corr. 
coeff. 
R2 
signifi 
cance 
Overbuilt area 
0,86 
0, 74 
0,00145 
Vegetated area 
-0,86 
0,74 
0,00145 
Buildings 
0,86 
0,75 
0,00132 
Traffic areas 
Other overbuilt 
0,41 
0, 17 
0,13853 
areas 
0,49 
0,24 
0,09243 
Trees 
-0,53 
0,28 
0,07036 
Bushes 
-0,60 
0,36 
0,04349 
Meadows 
-0,72 
0,52 
0,01412 
areas in the test regions are highly correlated with 
the mean radiation temperature values. The six pure 
cover classes are one generalization step too fine 
to explain the mean temperature values in an optimal 
way. So we see that the optimal description parameters 
of the selected testareas and the affiliated level of 
spatial generalization are the mean radiation tempera 
ture values and the percentages of the rough urban- 
land-cover-types "overbuilt" and "vegetated".