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ANALYSING FLOOD VULNERABLE AREAS 
WITH MULTICRITERIA EVALUATION 
G. Yalein*, Z. Akyurek** 
* General Directorate of Land Registry and Cadastre, Photogrammetry and Geodesy Department, Ankara, TURKEY 
guleryalcin@vahoo.com, gyalcin(tapu.gov.tr 
**METU, Middle East Technical University, Geodetic and Geographic Information Technologies, Ankara, TURKEY 
zakyurck@metu.cdu.tr 
KEY WORDS: Floods, GIS, Analysis, Decision Support, Disaster 
ABSTRACT: 
Cell-based Multicriteria Evaluation (MCE) methods are used to analyse the flood vulnerable areas. Flood disaster has a very special 
place in natural hazards. Its effect area is not bounded; it is an unusual event of a river basin. The aim in integrating Multicriteria 
Decision Analysis (MCDA) with Geographical Information Systems (GIS) is to provide more flexible and more accurate decisions to 
the decision makers in order to evaluate the effective factors. Some of the causative factors for flooding in watershed are taken into 
account as annual rainfall, size of watershed, basin slope, gradient of main drainage channel, drainage density, land use and the type 
of soil. In this study two main MCE approaches employed in GIS are used, namely Boolean and Weighted Linear Combination 
(WLC), and the issues and problems associated with both are discussed. In MCE, two methods, namely Ranking Method and 
Pairwise Comparison Method, are used to calculate the weights of each factor. Pairwise Comparison Method is integrated in GIS. An 
interface for pairwise comparison is created in Visual Basic Application embedded in ArcView 8.1 which is a GIS software program. 
The different results obtained from these two methods indicate the importance of the decision maker in determining the weights and 
the proper method, and making the decision. Furthermore, the concept of uncertainty in standardized criteria with MCE is evaluated. 
The standardized values of the factors are considered as a fuzzy measure concept expressed as fuzzy set membership. Some regular 
weights that are determined using Ordered Weighted Averaging are combined with the standardized values using WLC to recast the 
vulnerable areas. Thus the distribution of the weights of the criteria and compensating for each criterion by another one are seen in 
the solution set. A case study of flood vulnerable areas determination in Bartin Basin in the West of Black Sea Region is employed to 
illustrate the different approaches. To store the existing flood vulnerable areas in decision support system of General Directorate of 
Land Registry and Cadastre will provide some advantages to able to get answer for the questions of “How much area is vulnerable to 
flood?, What amount of the total area belongs to the government, or the real or judicial person?, Is there any area to be able to 
exchange by the treasury goods? How much?, what are the needs and cost to move through the non-vulnerable areas?”. 
the flood vulnerable areas is important for decision makers 
for planning and management activities. 
1. INTRODUCTION 
Many nations experience fatalities and injuries, property 
damage, and economic and social disruption resulting from 
natural disasters. Natural disasters, such as earthquakes, 
hurricanes, flash floods, volcanic eruptions. and landslides 
have always constituted a major problem in many developing 
and developed countries. The natural hazards kill thousands 
of people and destroy billions of dollars worth habitat and 
property each year. The rapid growth of the world’s 
population has escalated both the frequency and severity of 
the natural disasters. Flood disaster has a very special place in 
natural hazards. Floods are the costliest natural hazard in the 
world and account for 31 per cent of economic losses 
resulting from natural catastrophes. Especially, river flooding 
has been a major natural hazard worldwide in recent events, 
€.g&., Easter in the UK in 1998, Eastern Europe in 1998 and 
1999, China in 1998, and Venezuela in 1999 (Sanders and 
Decision making is a choice or selection of alternative course 
of action in many fields, both the social and natural sciences. 
The unavoidable problems in these fields necessitate detailed 
analysis considering a large number of different criteria. All 
these criteria need to be evaluated for decision analysis. In a 
classification based on Boolean Logic, an area is either 
accepted or rejected based on a given threshold value. 
Besides the problems associated with the use of Boolean 
Logic, multi-criteria evaluation (MCE) methods have been 
applied. Since 80 per cent of data used by decision makers is 
related geographically (Malezewski, 1999a), Geographical 
Information System (GIS) may provide more and better 
information about decision making situations. GIS allows the 
decision maker to identify a list meeting a predefined set of 
criteria with the overlay process (Heywood et al., 1993) and 
the multicriteria decision analysis within GIS may be used to 
develop and evaluate alternative plans that may facilitate 
compromise among interested parties (Malczewski, 1996). 
more than four months, 20 million people were affected in 
socio-economic life, thousands of people died and it caused 
the physical loss of approximately 20 billion USA Dollars 
(Türkiye Müteahhitler Birligi, 1998). Lin et al. (1997) presented a GIS-based multicriteria 
evaluation for investment environment to provide investors 
and local government decision makers with more specific 
information on investment location. The aim of this study 
was to explain how to develop an analysis environment to 
support various investment researches and investors. 
Flood related problems and many other applications proved 
that these problems could be solved through planning studies 
and detailed projects about flood prone areas. Determining 
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