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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B2. Istanbul 2004
4. COMPARISON OF MCE APPROACHES
The criterion maps were combined by logical operators such
as intersection and union in the Boolean approach. The
vulnerable area distribution in the flooded area was compared
with each other. To compare the methods (Ranking Method,
Pairwise Comparison Method, Boolean Method), the
percentages of the area in five classes namely; high, medium-
high, medium, low-medium, low were calculated. The
percentages gave a general idea about the vulnerability of the
basin to the flood. Which method represents the closer
zonation to the real flooded area? To answer these question
the 100-year flood depth and area obtained by Usul et. al.
(2002) was overlaid with the composite maps. According to
the overlays the percentages were not similar to each other. It
was obvious that the Boolean method was not suitable for
analyzing the flood vulnerable areas. Because flood
vulnerable areas, where flood was seen in the model outputs
could not be obtained by Boolean approach. The results
obtained with ranking method and especially with the
pairwise comparison method were more suitable. Because the
flooded area obtained by the model was also determined by
pairwise comparison method.
By using fuzzy logic the error due to the standardization and
classification of the values were reduced. The OWA method
is an extension and generalization of the WLC method based
on the uncertainty. It provides a consistent theoretical link
between the two common MCE logics of Boolean overlay
and WLC, and opens up the possibilities for aggregation of
criteria. The poor qualities can be compensated for. The
application of fuzzy measures in MCE in general and OWA
in particular require further research.
After the flood vulnerable areas were determined, the areas at
risk were obtained by overlaying the vulnerable areas with
the cadastral parcels (Figure 4.1 and Figure 4.2).
Determination of the areas at risk was needed for flood
warning and floodplain development control. In order to
represent the information of the parcel at risk, a database was
created. Block Number, Parcel Number, total arca of the
parcel, flooded area, owner name-surname, address had been
entered in the database.
5. CONCLUSION AND RECOMMENDATION
~The flood vulnerable areas in the study area were evaluated
in five classes. Since the methods take into account some
example conditions of the region, the results can be as
realistic only for this condition. When the characteristics
change, the results will show the different conditions. The
subjective numbers in the weights and the values of the
criteria can be changed according to the study area
characteristics and experts’ opinions. Performing the
sensitivity analysis on all the criterion weights, it was seen
that the accuracy in estimating weights should be examined
carefully. Sensitivity analysis helps to see if and how
attribute and weight uncertainties play a role. Geographical
sensitivity analysis is the study of how imposed perturbations
of the inputs of geographical analysis affect the outputs of
that analysis. The flood vulnerability maps can give planners,
insurers and emergency services a valuable tool for assessing
flood risk. Each of them needs to assess risk for more than
one scenario. A project including these vulnerability maps
Should be used on land planning, use and management
alternatives. The information in database should be obtained
with an interface. In future this interface should be automatic
in disaster related studies, because the amount of the
insurance is needed to be calculated with the area under risk.
The interface may be generated using a point-and-click
operation window, with a reference map to navigate and
highlight the area shown in the main map as in Sanders et al.
(2000).
Eg HIGH 1
MEDIUM 2|
LOW 3
Percent
Figure 4.1: Areas under risk according to the risk degree and
the percentage (Ranking Method).
EE HIGH 1
MEDIUM 2
LOW 3
0.7 a
Percent
Figure 4.2: Areas under risk according to the risk degree and
the percentage (Pairwise Comparison Method).
User interface allows users to evaluate and compare
weights/alternatives and to speed up the calculation. For this
kind of application, a required software program should be
developed, new tools should be generated in the interface and
the program with its interface and tools should be multi-user.
The interface should provide query and drive all the
necessary information. In the view of the total cost of flood,
Flood Insurance Studies (FIS) must be strengthened and
National Flood Insurance Program (NFIP) must be
established by the national flood insurance acts. Flood
Insurance Rate Map (FIRM) should be produced for the
private insurance industry and the state. This map should
provide the divides for the area studied into flood hazard
zones that are used to establish insurance rates.
Some arrangements must be developed and evaluated to deal
with the problems:
« The flood vulnerable areas should not be in the concept of
ownership. They should be in the authority and the
possession (use) of the state and counted as ownerless land
such as parks, arcas between the coast-edge lines.
* A wide region should be considered in the concept of rural
area arrangements. The arrangement should be done through
