Abstract:
نوشتار پیش رو با هدف شناسایی عوامل مؤثّر بر کاهش گسترة جنگل و پهنهبندی خطر کاهش گسترة جنگل، در بخشی از جنگلهای حوضة آرمردة شهرستان بانه واقع در زاگرس شمالی با مساحت 9177 هکتار انجام شده است. با شناسایی عوامل تأثیرگذار بر کاهش گسترة جنگل، این عوامل در قالب سه معیار اصلی عوامل انسانی، طبیعی و فیزیوگرافی دستهبندی شدند. با تشکیل ساختار سلسلهمراتبی و انجام مقایسههای زوجی، ترتیب وزن و اهمّیت معیارهای اصلی و زیرمعیارها در مقایسه باهم مشخّص و با ترکیب نظرات کارشناسان، وزن نهایی هرکدام از زیرمعیارهای دهگانه استخراج شد؛ پس از تهیة نقشههای مربوط به هریک از زیرمعیارها، این نقشهها با استفاده از روش تبدیل مقیاس خطّی به نقشههای معیار استانداردشدة وزنی تبدیل شدند. در گام آخر با رویهمگذاری و تلفیق همة نقشههای زیرمعیارها، نقشة پهنهبندی مناطق مستعدّ وقوع تخریب در چهار گروه با خطر کم، خطر میانگین، خطر زیاد و خطر خیلیزیاد تهیه شد. براساس نقشة پهنهبندی بهدستآمده، 25/3% از محدودة مورد مطالعه در پهنة خطر خیلیزیاد؛ 92/55% در پهنة خطر زیاد؛ 45/40% در پهنة خطر میانگین و 38/0% در پهنة خطر کم قرار میگیرد. نتایج ارزیابی صحّت نقشة پهنهبندی براساس استفاده از نقشة واقعی کاهش گسترة جنگل، نشان داد که 81/77% از مناطقی که در نقشة واقعیّت زمینی تخریب شدهاند؛ در نقشة پهنهبندی در مناطق با خطر زیاد و خطر خیلیزیاد قرار دارند. این میزان صحّت، کارایی روشهای تصمیمگیری چندمعیارة مکانی در پهنهبندی خطر کاهش گسترة جنگل را تأیید میکند. پژوهشهای مشابه انجامشده نیز کارایی سیستمهای تحلیل تصمیم چندمعیاری و ارائة مدلهای مبتنی بر سیستم اطّلاعات جغرافیایی را در پهنهبندی خطر کاهش گسترة جنگل تأیید میکنند.
This study aimed to identify the most influential factors in deforestation using multi-criteria decision-making method in a part of northern Zagros forests in Iran with a total area of 9177 hectares. Identifying the most important factors affecting deforestation, these factors were classified into three main criteria: human factors, natural factors and physiographic factors. By establishing hierarchical structure and performing pairwise comparisons, we determined the weight and importance of the main criteria and the sub-criteria. The final weight of each of the ten sub-criteria was extracted by combining the opinions of experts. After preparing the maps related to each of the sub-criteria, these maps were converted into standardized scale maps using the linear scale conversion method. In the final step, with the overlapping and integration of all sub-criteria maps, the zoning map of areas susceptible to deforestation was prepared in four groups with low risk, medium risk, high risk and very high risk. According to the results, 3.25% of the territory was located in very high-risk, 55.92% in high-risk, 40.45% in moderate-risk and 0.38% in low-risk zone. Accuracy assessment was done by comparing the deforestation risk zoning map with real deforestation map of the study area. The results showed that 77.81% of the areas that has deforested in this period was located in high-risk and very high-risk zones. This amount of accuracy supported the efficiency of Multi Criteria Decision Making Method in deforestation zoning. Similar studies confirm the effectiveness of multi-criteria decision analysis systems and the presentation of GIS-based models in deforestation risk zoning. Keywords: Deforestation, Group Decision Making, Multi Criteria Decision Making, Zagros Forests Extended Abstract: Introduction: The zoning of areas susceptible to deforestation is very considerable to direct conservation and regeneration activities of natural resources planners and decision-makers in endangered zones. Hierarchical analysis process is one of the most common methods of multi-criteria decision analysis that is widely used in zoning high-risk areas. This study aimed to identify the most influential factors in deforestation using multi-criteria decision-making method in a part of northern Zagros forests in Iran. Materials and Methods: In the first step, the factors affecting deforestation were identified based on the opinion of experts and a literature review. These factors were classified into three main criteria: human factors (population density, livestock density, distance from residential areas, distance from roads, distance from farmlands and gardens), natural factors (forest density, distance from waterways) and physiographic factors (slope, aspect, evaluation). The maps of these criteria were prepared and each map was classified into several classes according to the range of maps and the opinions of experts. The maps of each sub-criteria were standardized using the linear scale conversion method. Establishing hierarchical structure and performing pairwise comparisons, we determined the weight and importance of the main criteria and the sub-criteria. The final weight of each of the ten sub-criteria was extracted by combining the opinions of experts. After preparing the maps related to each of the sub-criteria, these maps were converted into standardized scale maps using the linear scale conversion method. After multiplying the weights of each criteria by the standardized weight of each layer, standard weighted layers were created. Then the standardized maps of the criteria were overlayed and integrated. In the final step, medium risk, high risk and very high risk, the deforestation risk zoning map was prepared by standardizing the final map and classifying it into four classes with low risk. Comparing the deforestation zoning map with the ground truth map of deforestation in the study area, the accuracy assessment of deforestation risk zoning was done. Results and Discussion: The results showed that physiographic factors had the highest weight among the main criteria. The high importance of physiographic factors is due to the role and effect of this factor in limiting access to forest areas. After physiographic factors, human factors and natural factors are important in the next degrees, respectively. Among the physiographic factors, three sub-criteria of elevation, slope and aspect were examined, which according to expert’s opinion, the slope criterion is the most important. Among the sub-criteria of human factors that are of secondary importance, the sub-criteria of population density and distance from the road have the highest weight, respectively. Other researchers have also pointed to a significant relationship between population density and the rate of deforestation and emphasize the role of aggravating factors in forest access such as distance from residential areas and roads in the amount of forest cover. In the group of natural factors, which includes two sub-criteria of distance from drains and tree density (number of trees per hectare), the sub-criterion of distance from drains was more important than other sub-criteria of this group. According to the results, 3.25% of the territory was located in very high-risk, 55.92% in high-risk, 40.45% in moderate-risk and 0.38% in low-risk zone. Accuracy assessment was done by comparing the deforestation risk zoning map with real deforestation map of the study area. The results showed that 77.81% of the areas that has deforested in this period was located in high-risk and very high-risk zones. This amount of accuracy supported the efficiency of Multi Criteria Decision Making Method in deforestation zoning. Similar studies confirm the effectiveness of multi-criteria decision analysis systems and the presentation of GIS-based models in deforestation risk zoning. Conclusion: According to the present study, combining hierarchical analysis and GIS is an effective tool for deforestation risk zoning. According to the zoning map, about 60% of the total area is in a high and very high-risk zone. Therefore, the concentration of conservation activities in critical areas is very important to prevent the continuation of the process of deforestation. Easy access and low slopes areas are the most prone to landuse change. The problem of increasing population and thus increasing the demand for conversion of forests into agricultural lands and man-made areas can be considered as the most important reason for the degradation of easily accessible forests.
Machine summary:
پزوهشگران زيادي بـه کـاربرد فراينـد تحليـل سلسـله مراتبـي درزمينۀ ارزيابي جنگل زدايي، پهنه بندي خطر تخريب و شناسايي عوامل اصلي آسيب پـذيري جنگـل پرداختـه انـد 1- Quercus branti lindl 2- Kučas 3- Pokhriyal 4- Grashof-Bokdman 5- Gibbs 6- Tucker 7- Geographic Information System (GIS) 8- Multi-Criteria Decision-Making Analysis (MCDM) 9- Spatial Decision Support System 10- Chandio 11- Makropoulos 12- Drobne & Liesc 13- Malczewski 14- Analytical Hierarchy Process (AHP) (پوخريال و همکاران ، ٢٠٢٠؛ پيرباوقار١ و همکاران ، ٢٠١٩؛ کندور٢ و همکاران ، ٢٠١١).
براساس مطالب يادشده ، اهدافي که در نوشتار پيش رو دنبال ميشوند عبارت اند از: شـناخت عوامـل مـؤثر بـر تخريب جنگل در منطقۀ مورد بررسي و درک ترتيب اهميت و شدت و ضعف عملکرد هر عامل در مقايسه با سـاير عوامل و همچنين استفاده از تحليل سلسله مراتبي براي پهنه بندي خطر کاهش گسترٔە جنگل .
الف : موقعيت منطقۀ مورد مطالعه در ايران ؛ ب : استان کردستان ؛ ج : محدودٔە منطقۀ مورد مطالعه در تصوير گوگل ارث 1- Quercus persica 2- Quercus libani 3- Quercus infectoria 4- Ghazanfari 5- Gorte & Sheikh 6- Google Earth از ديگر عوامل مهم در تخريب عرصه هاي منابع طبيعـي، گسـترش نامتعـارف و نـاهمگون حـريم جـاده اسـت (نکوئيمهر و همکاران ، ١٣٨٥)؛ همچنين وجود جاده به مثابۀ عامل تسهيل کنندٔە دسترسي انسان به عرصۀ جنگلي و گسترش فعاليت هاي مخرب ميتواند مطرح باشد؛ به همين دليـل ، فاصـله از جـاده از معيارهـاي مهـم در بررسـي تغييرات پوشش منطقه درنظر گرفته ميشود و در جنگل هاي زاگرس نيز به نظر ميرسد تأثير مشابهي داشته باشد (پيرباوقار، ٢٠٠٥؛ پيرباوقار و همکاران ، ٢٠١٩).