V. BATTSENGEL ET AL. 245
ture and structure of the soil [3,6 ]. As it can be seen from
Table 1, soil with low moisture has lower values in
comparison with all other classes. This indicates lower
backscatter intensities caused by specular reflection due
to lack of some surface features, low roughness proper-
ties and low dielectric constant of the dry soil. In contrast
to the soil with low moisture, wet soil gives high back-
scatter return compared to the most of the classes be-
cau se o f the soil moisture content and increased dielectric
constant.
In most cases, open area will behave as a specular re-
flector, but in short wavelengths and at some specific
conditions where sufficient surface roughness is ob-
served, it will have some components of diffuse scatter-
ing. As seen from Table 1, at SAR wavelengths the open
area has very low average backscatter return compared to
almost all other classes and it has a high statistical over-
lap with soil with low moisture in X and L bands. Spe-
cifically, in L-band, its backscatter values are lower than
the water, which means that the selected site is totally
dominated by a specular reflection and there is very little
return signal toward the radar antenna.
Generally, in an urban environment, most of the avail-
able water resources will have specular reflection and
should appear very dark on images for all incident angles
except 0. To obtain some backscatter from a water sur-
face, it must by some mechanism, be made rough. The
principal mechanism for the roughening the water sur-
face is the generation of waves and in reality the waves
can be generated by strong wind. However, in the given
case, there is contextual influence of grass, green vegeta-
tion and small bush (from both sides of the river) due to
which there is increased backscatter return (especially in
X-band).
4. The Proposed Knowledge Representation
In general, urban areas are very diverse and create com-
plex systems that have very explicit characteristics. These
make the urban system possible to distinguish from all
other systems. For example, it is necessary to consider
the physical aspects such as size, structural aspects such
as composition, economic aspects such as cost, and en-
vironmental aspects such as relation with its env ironment
as well as the aspects connected to its operation (i.e.,
utilization by people, interaction with concerned users).
In everyday life, an organization or a municipality man-
ages an urban system and their work consists of arrang-
ing, planning and managing these urban systems [8]. There-
fore, development of the urban knowledge base requires
a complex approach that considers all urban aspects.
For development of a proper KBS used for the auto-
matic interpretation of such multi-frequency SAR images,
the above knowledge about backscattering properties of
different natural and artificial objects of urban environ-
ment can be represented in a most efficient way, for ex-
ample, using a rule-based approach. It is one of the most
commonly used knowledge representation technique, in
which different rules mainly containing the constraints
on expert-defined variables, spatial objects, external pro-
grams and other spatial models are constructed and used
for the hypothesis evaluation [9]. Thus, different para-
meters to be required might be formulated as a set of “IF
THEN” rules and the actual image processing can be done
on the basis of a forward chaining principle [10]. More-
over, the rule-based inference based on the forward chain-
ing principle can be mapped into neural network archi-
tecture. For this purpose, at first, data attributes should be
assigned to input nodes, final hypotheses should be as-
signed to output nodes and the hypotheses must be as-
signed to hidden units. Then, the initial domain rules
determine how the attributes and hypotheses are linked
and how the links are weighted.
5. Conclusion
The aim of this study was to conduct kn owledge acquisi-
tion through the analysis of the backscattering properties
of the urban land cover features in Mongolia using Ter-
raSAR X-band, Envisat C-band and Palsar L-band SAR
images. In case of equal calibration, it was possible to
compare the backscattering properties of the separate
radar bands. However, as the calibration of each SAR
image was different, a comparison was made among the
classes within the bands themselves. Within the frame-
work of the study, an appropriate technique, which is a
rule-based approach for the acquired knowledge repre-
sentation was proposed. Overall, the study demonstrated
that the multi-frequency radar images could be success-
fully used for the knowledge acquisition as well as for
the investigation of different urban land surface features.
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