Journal of Spatial Analysis

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In advance crisis management of natural disasters, particularly earthquakes in urban areas is one of the necessities of urban planning. However, nowadays with the help of technology we can determine the risk of crisis in the urban areas and settlements. Due to population growth and increasing urbanization, the occurrence of natural disasters such as earthquake can cause terrible disasters in the cities. The need to reduce the vulnerability of the cities is one of the main objectives of physical planning of urban areas and city designing. The city of Kashmar in one of Iran's earthquake-prone areas (due to its adjacency to the Lut fault)  has  witnessed the sever destruction from  the September 25, 1903 earthquake (with a magnitude MS= 5/9) and Torbat Haidariye earthquake on 25 May 1923 (a magnitude MS= 5/8). It is very important to identifying vulnerable areas to earthquakes in advance. Accordingly the objective of this study is to identify the vulnerability of urban areas of  Kashmar city to the earthquake by using VIKOR model of urban planning. The vulnerability of the city was computed on several parameters among which the population density is the most important one.

     In order to carry out the research eleven population and other indices were used. These indices are as follows:

1. Building Materials;
2.  The quality of the building;
3. Old buildings;
4. Number of floors;
5. The materials of facades of building;
6. Compatibility of land uses;
7. Access to network passages;
8. Distance from the main fault;
9. The building density;
10. Numbers of population; and
11.   Relief and rescue centers.

 By using the VIKOR ranking model the vulnerability of the urban areas of the city was identified and classified. The correlation between the city vulnerability and each of these indices was calculated. The impact of the indices on the city vulnerability was calculated according to the AHP model.

      The results of the study showed that the zone 3 had the highest and the zone 8 had the lowest physical vulnerability in the model. Based on the results of the Spearman correlation, the impact of the population on the vulnerability was about .5866 which is relatively noteworthy.  This means that highest degree of vulnerability can occur in very populated areas of the city. All of the city was regionalized according to the degree of vulnerability to earthquake.

The lack of amenities and facilities such as health centers, fire stations, building materials and weak areas within the city will increase the losses and casualties. It is noteworthy that comprehensive city planning in the future must improve and the needed facilities should be provided. In addition providing services to the residents, especially in critical times after the earthquake should be provided.

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Identifying spatial patterns in vulnerability involves a comprehensive look at vulnerable points. And provides analytical power to the authorities. Therefore, it is necessary to recognize patterns of vulnerability so as to minimize the amount of damage to them in the event of a crisis. The city of Tehran, as the political and administrative center of the country, is faced with a variety of risks due to demographic burden and physical development. In this research, we tried to analyze the spatial distribution pattern of urban vulnerability to natural hazards in social and physical dimensions in Tehran's 7th region. The method of this descriptive-analytic study and the model used for trigonometric fuzzy logic. The results indicate that: According to the z score, the positive values are 1.96 up, which form the clusters of hot spots in the southeastern region of the arena; It is a sign of more vulnerability in these areas. Also, negative values of 1.96 and less, which are statistically significant and blue, have formed cold spots, And it is interpreted that low vulnerability zones are clustered in space and are mainly located in the northwest. Therefore, the lower the color range in the red and blue areas was less statistically significant  to the point where this positive net worth is 1.65 that in this situation, the spatial behavior of the vulnerability is considered to be non-significant in terms of hot or cold clusters with high and low values and spatial autocorrelation that the map is also displayed in yellow.