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Showing 4 results for Urban Vulnerability

Nahid Bagheri Maragheh, Mohammad Motamedi, Ezatollah Mafi,
Volume 22, Issue 64 (3-2022)
Abstract

Abstract
Explaining the relationship between resilience to natural disasters is in fact how social, economic, institutional and physical capacities affect the increase of resilience in societies. Accordingly, the purpose of this study is to investigate the resilience of Shirvan city in the face of earthquakes in which the research method is descriptive-analytical and the statistical population includes experts in the field of urban resilience for this group of 30 people. First, the indicators evaluated to assess the resilience of Shirvan city in the face of earthquake hazards using the ANP model, which were questioned by experts and elites, were 25 indicators in 4 physical, institutional, cultural, social and economic criteria. Paired comparisons were performed. Findings showed that the rate of resilience in Shirvan is low in 65.4% of the city and high in only 19.2% of the city. In other words, in 17 neighborhoods out of 26 neighborhoods of Shirvan city, the rate of resilience in the face of earthquake hazards is low and only in 5 neighborhoods of the city the rate of resilience is high. Therefore, the final results of resilience in Shirvan are 19.2% of the upper city, 15.4% of the average city and 65.4% of the lower city. In general, the results indicate that the resilience of Shirvan is in an unfavorable and unfavorable situation and the rate of resilience in this city is low in the face of earthquake hazards.
Dr Shahrivar Rostaei, Dr Rahim Heydari Chyaneh, Mr Ayoub Zoghi,
Volume 24, Issue 73 (6-2024)
Abstract

As cities become more physically in structure and demographically wider, the rate of crises is also increasing consequently, and cities become more vulnerable to natural disasters for a variety of reasons, including economic and cultural poverty, fault alignment and non-compliance to regulations of earthquake-related issues.  What matters is the level of community's preparedness and the degree of vulnerability of the city and its residents, which can be reduced to the lowest level if properly planned and principle policies are adopted.  In this research, considering the high potential of Sanandaj in terms of seismicity and the existence of many faults in the vicinity and around of the city, it is tried to gain an authentic understanding of the subject with identifying the factors affecting the earthquake and combining indicators using the  Classification Tree Analysis (CTA) model. The results indicate that a large area of   the city is in the category of moderate to high vulnerability.52% is in the middle vulnerability category, 16.5% is in the high vulnerability category and 1% of the city is considered to be in the very high vulnerability category, which exactly matches the same marginal, old and densely populated neighborhoods. This situation does not render a proper structure and needs more consideration in prospective development plans.
 
Dr Ahmad Aftab, Dr Ali Akbar Taghilo, Mr Akbar Houshmand,
Volume 24, Issue 74 (9-2024)
Abstract

The continuous and active presence of disciplinary centers has an important role in ensuring security and peace in cities.Therefore the fair and efficient distribution of law enforcement centers in urban areas is an important factor in meeting this basic need.Therefore, the present study aims to investigate the service of police stations on vulnerable areas of Urmia.The descriptive-analytical research method used in this study is applied.The results of the study show that the vulnerability zoning of the city of Urmia is in four categories from very high to very low. About 68 km2 of the whole area of the city is known to be highly vulnerable.Most of the northern (informal settlements of Region 2) and central (old districts of four region) settlements of Urmia are the most vulnerable areas due to the high density of population and housing,with most of the politically sensitive, commercial and administrative offices in these areas.The results of the network analysis based on standard time (12 minutes) indicate that the 28.9% (24 km2) of the Urmia Vulnerable Areas was not covered by the police stations.Within 12 minutes the police stations of Urmia city have quick access to 55 km2 of about 75 km2 area with high vulnerability and about 20 km2 of this area also without timely access. In terms of the police stations access to low vulnerability areas,the results also show that from about 15 km2 of these areas to 3 km2 have quick access, indicates that there is no quick access to these 12 km2
Dr Shahrivar Rostaei, Dr Rahim Heydari Chyaneh, Mr Ayoub Zoghi,
Volume 25, Issue 76 (3-2025)
Abstract

The occurrence of earthquakes and the losses and damages caused by it have always imposed a serious threat to the city, residents and assets, so that it has made planners and city managers to provide logical and scientific solutions to make cities safer. Securing cities against earthquakes will not be achieved only by creating strong structures, and we must take steps to reduce urban vulnerability through optimizing urban land use. The purpose of this study is to determine the optimal urban areas for the development of the city with the aim of reducing the vulnerability of Sanandaj. For this purpose, KNN method has been used as a model with relatively high accuracy to evaluate the optimal land use of Sanandaj city with an emphasis on earthquake risk. The obtained model output shows that about 32% of the city area is in optimal condition and district 2 with 42.78% equivalent to 406 hectares and district 4 with 50.85% equivalent to 658 hectares provide an optimal condition for the development of the city, towards reducing urban vulnerability and increasing urban land use optimization. The general condition of the city is not suitable in terms of optimality and the neighborhoods located in districts 1 and 2 are in a very inappropriate condition due to high population and residential density, very poor permeability and low adaptation of land uses. In evaluating the model, the value of the area below the curve is 0.951, which indicates the desirable performance of the model in examining the subject. 

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