نشریه مدیریت بحران
سال سوم شماره 1 (پیاپی 5، بهار و تابستان 1393)

Receiving rapid، accurate and comprehensive knowledge about the conditions of damaged buildings after earthquake strike and other natural hazards is the basis of many related activities such as rescue، relief and reconstruction. Fewer Restrictions by using high-resolution Images compared to terrestrial techniques turned it into the main source for damage assessment during these days. The present research aims at providing a damaged maps in a short time after the earthquake by using post-event high-resolution satellite Imagery. In this research، for all buildings، textural features for any candidate buildings، one by one، are extracted. Before extracting the features، optimum feature selection is done by genetic algorithm (GA). After selecting optimum textural features، buildings situation regarding to their destruction is evaluated using these features in two ''intact'' and ''Damaged'' classes by using the Maximum Likelihood and the Neural Network Algorithms. Finally، polygons of buildings classified in three different classes named ''Under 30%''، ''Between 30% and 70%'' and ''upper 70%'' based on the number of damaged pixels. The overall accuracy of classification evaluated about 81/04% by using an expert operator.

The capital of Iran، Tehran، has a major role in the political، economic، cultural and services at the regional، national and international scale. Occurrence of any disaster in the capital could cause tremendous consequences، especially on national security، politic، and economy of the country. In this article، the collapse of the buildings due to earthquakes is investigated. Generally، collapsing the buildings will lead to the largest physical damage as well as human loss during an earthquake. Investigating the collapse of buildings at one of the regions in Tehran after the earthquake not only makes a clear view of that region future after disaster، but also it helps urban managers prioritize different retrofitting measures. In this regard، uncertainties influencing the risk assessment of the collapse is originated from the type of structures، height of buildings، applied seismic design codes، and type of soil are considered in the study using logic tree method. Fragility curve is a factor for determining the percentage chance of stating the damage and consequently، the collapse. Developing fragility curves based on region’s conditions is a necessary task to justify the results of the study. In this paper، after introducing the local means of developing fragility curves، the studied region is divided into smaller cells based on soil characteristics and then the collapse risk of different buildings in each cell is studied separately based on a proposed algorithm. At the end، considering seismic analysis and collapse probability for existing buildings the most critical types of buildings would be determined based on the results of average and maximum collapse possibility. Furthermore، the results of collapse assessment are presented for two scenarios in order to evaluate retrofitting by enhancing of seismic design code.

Experiences of disastrous accidents in industrial complexes have led researchers to create a standardized management system in order to tackle such problems for better crisis management. Explaining the organizational patterns in emergency operation centers inside oil companies such as oil operational field of Cheshme Khosh could contribute the reduction of financial and life loss due to possible accidents in the future. If structure and organizational communication of Emergency Operation Center are defined correctly، it can perform perfectly in crisis management. Therefore، this research was conducted by field method، and its data collection tools were interviews and questionnaire survey، and its population included the employees of Cheshme Khosh oil operational field. According to hypotheses'' analysis critical spots in Cheshme Khosh region include the slop section of desalinization unit، separators، oil storage sinks، and oil and water pit. Sufficient instruction about crisis management is not provided to the employees. The most important elements in organizational pattern of the emergency operation center are suitable arrangement، suitable access، human resources and equipment. Moreover، the most suitable persons for the regional management center are the unit managers and HSE experts.

Nowadays، the performance of critical assets in the industrial and urban sites depends on network-based systems. With respect to this fact that an infrastructure (as a complex system) consists of several assets، it is clear that assets play a vital role in daily performance of the urban systems. This study developed a novel model to analyze the interdependency of critical assets in an industrial system. The most famous conventional method regarding the interdependency of the assets (Leontief) were considered، which suffer from some weaknesses. However، the new model was extended with new abilities. In the proposed model، the assets were classified into two states: resource and demander. The objective of this model is to estimate the interaction of assets using an innovative Operation Research (OR) framework in order to simulate the mechanism of dependency of assets. To obtain the criticality of assets، a new term entitled by “centrality” was introduced to select and to rank the assets. A notional example was provided to illustrate the application of the proposed model.

Measurement and assessment of the performance are considered as the top proprieties to acquire an efficient managerial strategy toward safety process، and also، to have continuous improvement. Furthermore، these indices help us to control the accident. In the system. The aim of this research is to determine the characteristics of a standard safety process with respect to the frequent accidents which may usually happen in the main natural gas pipelines. So quantity and quality indexes were selected and defined in order to assess the performance of the process. The experts’ opinions were also used to weigh the current options by which the process should be run. In the next step، the corresponding accidents of the basic events in the process were carefully detected. Finally، to assess the validity of the observations، a mixed data Evaluation Matrix was applied (EVAMIX). The results clearly indicates that، the occurrence of bursting in the pipelines with score of 0. 1279 is the most important accident. Moreover، the likelihood of gas leaking due to spring a leak in the pipes with score of 0. 0743 should be considered very low. To assess the process، severity and frequency should be consider as the most important indexes with the weight of 0. 1131، and the skill of the workers (0. 0208) is the least one. The present study helps the mangers to have better opportunity to assess the process based on safety factors and indexes in order to make decision wisely.

Iran is affected by the earthquake at a very high level، and it stands after China، India and Bangladesh. Although an earthquake is not a predictable، developed society can reduce its impacts by appropriate management and programming. So it is important to present a model which is organized and inclusive and can show the relationship between effective factors to reduce unwanted effects. This research used Interpretive Structural Modeling (ISM) to present a model which can explain the relationship between effective factors to control and reduce the damages of an earthquake. In this research، quantitative and qualitative methods were combined to make a model which may help managers in urgent situations to make good decision and prepare suitable programs. In this research Delphi method and Second Order Confirmatory Factors Analysis were employed to detect effective factors in reducing and controlling earthquake damages. After confirming these factors، by Partial Least Square software the opinions of 15 managers of Yazd Red Crescent Community were used to build the main model of the research. The results showed that those proposed factors can evaluate the exceptional concept of the research. According to the prepared model، “factors-related related values”، “managing and strategic factors” and “urbanity factors” are the basis of the model of reducing and controlling damages of the earthquake.

Nowadays، fires are the most common damaging factor of natural ecosystems after urban and agricultural human activities. The aim of this study is to identify the susceptible areas to fires using Discriminant Analysis and Adaptive Network Based Fuzzy Inference System in the Golestan National Park as one of the most important biosphere reserves. The required data and digital layers were prepared from associated sites، organizations and field surveys in the area of the study. After preparing the data by assuming the occurred fire، the most significant effective factors were identified using Discriminate Analysis. These factors were calculated as a weighted average and models were implemented by using K-Fold Algorithm with trapezoidal، Gaussian، triangular and bell membership functions in six stages. The best model was used for simulation. The fire hazard map was prepared with five classifications، very low، low، medium، high and very high. An accuracy assessment was performed using the relative operating characteristic. The results of the Discriminant Analysis showed the important factors، including presence of hunters and shepherds، distance from roads، average temperature، distance from the springs، rainfall during the growing season and slope. Validation trapezoidal membership functions showed best results with value of R2= 0. 534 and RMSE= 0. 283. The results of the accuracy assessment obtained with value of ROC= 0. 875. While the very High-risk area was 972 hectares، and High-risk area was 16879 hectares of 91895 hectares area. According to accuracy of the proposed map، it can be used to control the region fires in Golestan national park.

Desertification has turned into serious hazard for many countries especially developing ones such as Iran. The most suitable methods for desertification assessment intensity considered to be experimental models. Iranian desertification model، namely MICD، was used in this study to assess desertification hazard for Sabzevar region. For this purpose، work units map (geomorphologic faces) was created using slope، geology، vegetation cover، land use، Landsat 5 satellite imagery and Google Earth data. Accordingly، four units، 10 types and 96 faces were identified. Desertification map of the model was synthesized after rating the desertification indices in work units. For assessing desertification risk، firstly، the elements at risk were identified and classified. The risk map was developed with a combination of desertification hazard intensity and number of elements and degree of vulnerability maps using the total risk equation. Results showed that «continuity of wind blow (≥ 6 m/s as threshold wind velocity)» and «density of vegetation cover» in rangelands; «continuity of wind blow (≥ 6 m/s)» and «soil accumulation» in bare lands، and «Crop residue management» and «wind break situation around the field» in the farmlands are the most effective factors. Desertification map was created in four classes of low (II)، moderate (III)، high (IV) and very high (V). The vast area of the region is allocated to the moderate class (46. 45%). The highest and lowest elements fall into intensive (V) and very low classes (I)، respectively. Risk map of desertification was obtained in five classes which the largest part (46. 77 %) and the smallest part (9. 16%) of the region was associated with the high and very low classes respectively.