| چکیده انگلیسی مقاله |
Abstract The environmental hazards is always considered as a threat for human settlements. Their effects on rural areas and various regions of the country are different according to the type of hazards. According to various parameters such as geographical location of the villages, the physical-Spatial structure, and the risk-taking, rural settlements will experience the greatest crisis during the disasters. Identifying the vulnerability of rural settlements, regarding the variables and effective factors, is considered one of the prevention method, reduce damages and management of risks. The present study aims at prioritizing the villages of Khuzestan according to environmental vulnerability like the distance from the active geology fissures, soil texture, the features of geological structure, the distance from torrential plains, the distance from preserved regions and the degree of slope using fuzzy logic. The research method is based on descriptive-analytical one with practical goal and applicable in the region. Data analysis is designed and implemented based on fuzzy logic in geographic information system (GIS). The findings show that the Khuzestan province demands a lot of research in studies about prioritizing the vulnerability. According to the study on 1989 rural areas based on various scenarios including, relatively pessimistic scenario of 746 rural areas, relatively optimistic scenario of 3 the rural areas, balancing scenario of or the weighted linear combination of 98 point of rural areas, they have the value of standardized environmental vulnerability more than 0.5. Moreover, based on the pessimistic scenario, all rural settlements of the region have more than 0.75 standardized value of environmental vulnerability, while based on the optimistic scenario, all rural settlements have zero standardized value of environmental vulnerability. Extended Abstract 1- Introduction The environmental hazards is always considered as a threat for human settlements. Their effects on rural areas and various regions of the country are different according to the type of hazards. According to various parameters such as geographical location of the villages, the physical-Spatial structure, and the risk-taking, rural settlements will experience the greatest crisis during the disasters. Identifying the vulnerability of rural settlements, regarding the variables and effective factors, is considered one of the prevention method, reduce damages and management of risks. The present study aims at prioritizing the villages of Khuzestan according to environmental vulnerability like the distance from the active geology fissures, soil texture, the features of geological structure, the distance from torrential plains, the distance from preserved regions and the degree of slope using fuzzy logic. 2- Materials and Methods The method of present research is based on descriptive-analytical one based on practical goal and applicable in the region. Data analysis is based on fuzzy logic designed and implemented in geographic information systems (GIS). As a matter of fact, he specific characteristics of the available data, and he views of experts and previous studies, 7 variables were used to evaluate and prioritize the environmental vulnerabilities. They are active geological fissures, soil texture, features of geological profiles based on time, the distance from flood plains, the distance from preserved areas, the distance from the point of occurrence of landslides and the value of the slope. According to the census of Statistical Center of Iran in 2011, Khuzestan province with an area of 64,055 square kilometers, has a population of approximately 4.53 million people, with 27 city, 67 districts, 144 villages, 77 towns and 1989 villages. Besides, it is located within 42 minutes to 50 degrees 47 degrees 34 minutes east longitude and latitudes 29 degrees and 53 minutes to 32 degrees 59 minutes north. 3- Results and Discussion Based on the study, it turns out that Khuzestan Province needs a lot of research on prioritizing the vulnerability. Therefore, the basic data were identified and prepared, the maps for the prioritization of environmental vulnerability from several functions and fuzzy scenario were used and eventually the vulnerability of rural human settlements is taken. Using a relatively pessimistic scenario, it is a verifiable fact that all rural settlements of the area (about 746 rural settlements, or about 37.5 of the total rural settlements) have a standardized environmental vulnerability more than 0.5. Furthermore, about 28 rural settlements, or about 1.4 percent of the study area have a standardized vulnerability of rural settlements more than 0.8. It is also based on relatively optimistic scenario about a limited number of rural settlements study area (rural settlements, or about 0.1 percent of the total three rural settlements) that have a standardized environmental vulnerability more than 0.5. In addition, using the pessimistic scenario, all rural settlements of the area have a standardized environmental vulnerability more than 0.75. Besides, about 1,844 rural settlements, or about 92.7of the total rural settlements of the area have a standardized environmental vulnerability more than 0.9. Taking optimistic scenario, all rural settlements have a value of zero environmental vulnerabilities. Balanced scenario or the weighted linear function results also showed that the study area has a relatively limited number of rural settlements (about 98 rural settlements, or about 4.9 percent of the total rural settlements) with a standard amount of environmental damage-over0.5. 4- Conclusion Studying 1989 rural areas based on various scenarios including relatively pessimistic scenario of, , relatively optimistic scenario, balance scenario of or the weighted linear function, 746, 3, and 98 rural areas have the value of standardized environmental vulnerability more than 0.5 respectively. The findings show that the study is able enough to prioritize the environmental vulnerability of rural settlements throughout the region optimally. Besides, it presents multiple functions and fuzzy scenario of environmental vulnerability of rural settlements across the area of study using appropriate variables. It can not only design several function and scenario phases to prioritize environmental vulnerability, but also help and support the planners and decision-makers in planning, decision-making. |