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تهیۀ نقشۀ چندخطرۀ استان مازندران با استفاده از تحلیل تصمیم‌گیری چندمعیارۀ مکانی | ||
| مدیریت مخاطرات محیطی | ||
| مقاله 5، دوره 8، شماره 4، دی 1400، صفحه 395-411 اصل مقاله (1.29 M) | ||
| نوع مقاله: پژوهشی کاربردی | ||
| شناسه دیجیتال (DOI): 10.22059/jhsci.2022.332933.686 | ||
| نویسندگان | ||
| نرجس محمودی وانعلیا1؛ میثم ارگانی* 2؛ محمدرضا جلوخانی نیارکی3 | ||
| 1دانشجوی دکتری سنجش از دور و سیستم‌های اطلاعات جغرافیایی، دانشکدۀ جغرافیا، دانشگاه تهران | ||
| 2استادیار گروه سنجش از دور و سیستم‌های اطلاعات جغرافیایی، دانشکدۀ جغرافیا، دانشگاه تهران | ||
| 3دانشیار گروه سنجش از دور و سیستم‌های اطلاعات جغرافیایی، دانشکدۀ جغرافیا، دانشگاه تهران | ||
| چکیده | ||
| هدف اصلی این پژوهش، تولید نقشۀ چندخطرۀاستان مازندران با استفاده از ترکیب نقشه‌های مخاطرات سیلاب، زمین‌لغزش و آتش‌سوزی در نرم‌افزار ArcGIS است. معیارهای به‌کاررفته در این پژوهش با استفاده از روش تحلیل سلسلهمراتبی (AHP) وزن‌دهی شده و با به‌کارگیری روش چندمعیارۀ ترکیب خطی وزن‌دار (WLC) با یکدیگر ترکیب شدند. ارزیابی صحت نقشه‌های پتانسیل خطر به‌دست‌آمده نیز از راه مقایسۀ آنها با مخاطرات واقعی رخ‌داده انجام گرفت. در ادامه برای تولید نقشۀ چندخطرۀ استان مازندران از دو روش همپوشانی طبقات پرخطر نقشه‌های خطر و میانگین هندسی کل طبقات استفاده شد. در پایان، با مقایسۀ نقشۀ چندخطرۀ حاصل و نقشۀ جمعیت استان مازندران، میزان مساحت و جمعیت در معرض خطر بررسی شد. نتایج پژوهش نشان داد که روش همپوشانی طبقات پرخطر، تنوع بیشتری از مخاطرات تهدیدکننده را نسبت به روش میانگین هندسی شامل می‌شود. همچنین نتایج بررسی‌ها بیانگر این است که حدود 7/59 درصد از مساحت و 6/30 درصد از جمعیت استان مازندران در معرض مخاطرات طبیعی قرار دارند که سهم هر یک از مخاطرات آتش‌سوزی، زمین‌لغزش و سیلاب به‌ترتیب 4/18، 2/18 و 3/13 درصد از مساحت و 1/4، 5/6 و 9/17 درصد از جمعیت در معرض خطر است. | ||
| کلیدواژه‌ها | ||
| آتش‌سوزی؛ ترکیب خطی وزن‌دار؛ روش تحلیل سلسلهمراتبی؛ زمین‌لغزش؛ سیلاب؛ نقشۀ چندخطره | ||
| عنوان مقاله [English] | ||
| Multi-hazard potential mapping of Mazandaran province using multi-criteria spatial decision analysis | ||
| نویسندگان [English] | ||
| Narjes Mahmoody-Vanolya1؛ Meysam Argany2؛ Mohammadreza Jelokhani-Niaraki3 | ||
| 1PhD Student in Remote sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran | ||
| 2Assistant Professor of Remote sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran | ||
| 3Associate Professor of Remote sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran | ||
| چکیده [English] | ||
| Introduction In the recent years, the scale and frequency of natural hazards were increased, significantly [21]. Published data and reports on natural hazards show an increase in such disasters around the world [18, 5]. It's not possible to eliminate these risks, completely, but their negative effects can be minimized by using new methods and appropriate data in the decision-making process [12]. Many parts of the world are exposed to the events that involve more than one natural hazard [22، 10]. In natural hazards, any hazard can be associated with hazards or other processes, in which case, they are considered as multi-hazards [22، 6]. Floods, landslides and forest fires are among the most common natural hazards [16]. Floods are one of the most common and destructive natural hazards in the world, which has many social, economic and environmental consequences [24، 15، 14]. Landslides are known as one of the most common geological disasters that cause serious damage to the natural ecosystems and human infrastructure [20، 7]. 17% of all natural disasters occur due to landslides [19، 17]. Fire is also one of the main threats to the environment with many negative effects that in some cases the negative effects continue for more than 10 years after the occurrence of this phenomenon [3]. The financial and human damage of fires have increased significantly around the world in recent years [4]. Recent advances in GIS technologies for data collection and spatial analysis can provide practical tools to develop a hybrid approach and as a useful tool for spatial analysis in risk evaluation [23]. In this regard, GIS is an excellent tool for storing, analyzing and managing spatial data and combines different types of numerical and descriptive values with spatial data [11، 1]. Multi-criteria decision analysis (MCDA) methods have been widely used in integrating, identifying or ranking influential factors, especially in natural hazard analysis [2، 8، 9]. Materials and Methods Mazandaran province is located in north of Iran and includes part of the Alborz Mountain belt. There are about 3 million of people in Mazandaran province (4.9 percent of the population in Iran) with an area of about 23,756 square kilometers (1.46 percent of Iran). The first step of the research is the production of standard maps and their standardization. The second step is determining the weight and importance of each criterion by experts. In the third step, using the weighted linear combination (WLC) multi-criteria method, the weights produced by the AHP method and the standard benchmark maps are combined to create flood, landslide and fire hazard maps, separately according to the effective factors. The validity of these maps was assessed using two accuracy evaluation parameters and based on historical events. In the next step, according to the overlap and spatial distribution of the predicted high-risk areas, the final multi-hazard map is produced. Finally, by comparing the population map of Mazandaran province and the produced multi-hazard map, the amount of population and area at risk of each of the hazards were determined and evaluated. Discussion and Results In this research, using standard criterion maps, weight values assigned to the criteria and using WLC multi-criteria method, multi-hazard maps (flood, landslide and fire) of Mazandaran province were produced. AHP method was used to determine the weight of each criterion. Then, maps were prepared regarding the potential for flood, landslide and fire hazards. Each of these maps were classified into 5 different classes with very low, low, medium, high and very high risk in order to study the areas with potential risk. In the production of flood potential mapping, the criteria of distance from the drainage network, height and slope have the highest weight and importance according to experts. Most areas with flood risk potential are located in the northern parts of Mazandaran province. According to experts, the incidence of landslides is closely related to the type of land, the degree of slope and proximity to the road. In new Quaternary sediments and steep areas near to roads in Mazandaran province, landslides are most likely to occur. Forest lands near to roads and mountainous residential areas show the highest risk of fire. As a result, in this area, human factors can play a very important role in creating and occurring fires. In addition to using the degree of overlap of the fifth grade of each of the flood, landslide and fire potential hazard maps in the production of multi-hazard map, the geometric average of all hazard potential hazard map classes to produce the map multi-hazard has been used. The reason for using this method is to apply the concept of geometric mean and maintain the value of high-risk data and spatial locations in each of the potential hazard maps. In order to estimate the area and population at risk of each of the flood, landslide and fire hazards, the overlap of each of them were calculated using a multi-hazard map and the population map of Mazandaran province was done. Conclusion The aim of this study is to prepare a multi-hazard map of Mazandaran province and determine the area and population exposed to these hazards. The results of this study showed that many areas in Mazandaran province are exposed to more than one natural hazard. Multi-hazard interaction in an area can have much higher negative effects than the sum of the effects of several hazards alone. Therefore, to manage natural hazards and reduce their negative effects, using a multi-hazard approach and planning based on the results of this approach is very important. On the other hand, due to the fact that estimating the potential of each risk is affected by several spatial criteria, the use of multi-criteria spatial decision-making models can increase the accuracy of spatial modeling of multi-hazard maps. The results showed that about 0.04% of the population and 0.6% of the province are at risk of all three. These areas are located in the central strip of Mazandaran province. As a result, these areas are more sensitive than other areas of Mazandaran province. | ||
| کلیدواژه‌ها [English] | ||
| Multi-hazard, Mazandaran province, multi-criteria spatial, decision analysis | ||
| مراجع | ||
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