پديد آورندگان :
مهدوي، علي دانشگاه ايلام - دانشكده كشاورزي - گروه علوم جنگل، ايلام , رنگين، سميه دانشگاه ايلام - دانشكده كشاورزي - گروه علوم جنگل، ايلام , مهدي‌زاده، حسين دانشگاه ايلام - كارآفريني و توسعة روستايي , ميرزايي‌زاده، وحيد دانشگاه ايلام، ايلام
كليدواژه :
مدل‌سازي تخريب , رگرسيون لجستيك , تغييرات پوشش , جنگل‌هاي زاگرس , ايلام
چكيده فارسي :
از آنجا كه تغيير كاربري اراضي و تخريب جنگل‌ها، نشان‌دهندۀ ارتباط مستقيم و متقابل انسان و محيط‌زيست طبيعي آن است، درك بهتر فرايندهاي اجتماعي و بيوفيزيكي كه ايجادكنندة تغييرات و تخريب اراضي هستند، مي‌تواند نقش مهمّي در سياست‌گذاري و اجراي اقدامات پيشگيرانه و تصميم‌ها داشته باشد. به‌منظور بررسي روند تخريب پوشش جنگلي شهرستان چرداول در استان ايلام، از تصاوير سنجنده‌هاي پيمايش‌گر چند طيفي و تصويربردار عملياتي زمين ماهوارة لندست مربوط به سال‌هاي 1366 و 1393 و روش مدل‌سازي رگرسيون لجستيك استفاده شد. براي بررسي عوامل تخريب، نقشة تغيير پوشش جنگلي با متغيّرهاي فيزيوگرافي (شيب، جهت و ارتفاع) و انساني (فاصله از جاده و فاصله از مناطق مسكوني) وارد مدل رگرسيون لجستيك شد. نتايج پژوهش نشان داد طي 27 سال، حدود 82/10332 هكتار از جنگل‌هاي شهرستان چرداولتخريب شده است كه نشان از كاهش سالانة 67/382 هكتار از سطح جنگل‌هاي منطقه دارد؛ همچنين، نتايج مدل‌سازي نشان داد كه متغيّر جهت دامنه با دارا بودن بيشترين ضريب تأثير (7267/0)، شايد مهم‌ترين عامل بيوفيزيكي تأثيرگذار بر تخريب جنگل در منطقة مورد مطالعه بوده است؛ پس از آن، به‌ترتيب متغيّرهاي شيب و ارتفاع از سطح دريا در تخريب احتمالي جنگل تأثيرگذار بودند. متغيّرهاي فاصله از روستا و فاصله از جادّه هم رابطة معكوس با مقدار تخريب در منطقة مورد مطالعه دارند. ارزيابي مدل رگرسيوني برازش‌داده‌شده با شاخص‌هاي ويژگي عملياتي نسبي (معادل 8493/0) وضريب تشخيص كاذب (معادل 2248/0) هم بيانگر قابليت بالاي مدل به‌منظور توصيف تغييرات و تعيين مناطق مستعد تغيير است.با توجّه به سرعت تخريب سالانة جنگل در اين منطقه كه بيشتر از متوسّط جهاني است، در صورت عدم برنامه‌ريزي پيشگيرانه توسّط برنامه‌ريزان استاني و كشوري، شايد در آينده‌اي نه‌چندان دور شاهد پديدة بيابان‌زايي در شهرستان چرداول باشيم.
چكيده لاتين :
Since land use change and forest degradation represent a direct and interrelated relationship between human and their natural environment, understanding the social and biophysical processes that cause land use change and degradation can play an important role in policing and implementing preventive measures and decisions. In order to investigate the forest cover degradation trends of Chardavol county in Ilam province, satellite images of MMS and OLI Landsat sensors for the years 1987 and 2014 and regression logistic modeling methods were used. To investigate the causes of degradation, forest cover changes map and physiographic (slope, aspect, altitude) and human (distance to road and distance to residential areas) variables were integrated into regression logistic model. The results of study showed that about 10332.82 ha of forest cover has been reduced in Holeilan division of Chardavol County during 27 years. This amount of forest cover reduction includes 382.68 ha annually. In addition, the results of modelling showed that aspect variable with the highest coefficient (0.7267) is probably the most biophysical factor affecting on deforestation in the study area. After that, slope and altitude variables probably affected deforestation, respectively. Distance to villages and road variables in study area are both inversely related to the amount of forest degradation. Assessment of regression model fitted with ROC (0.8493) and Pseudo-R2 (0.2248) indices indicated the ability of the model to describe the changes and to identify the areas prone to change. According to the annual rate of deforestation in the area, which is more than global average, in the absence of proactive planning by provincial and national planners, perhaps, we will see the desertification phenomenon in Chardavoul County in the near future.
Extended Abstract
1-Introduction
Zagros forests have long been the habitat of the inhabitants and nomads in these areas and have been exposed to many damage. The issue of degradation and reduction of Zagros forests has emerged as one of the crises in recent years. Destruction and land use /land cove changes represent a variety of social and environmental factors. Since land use change and forest degradation represent a direct and interrelated relationship between human and their natural environment, understanding the social and biophysical processes that cause land use change and degradation can play an important role in policing and implementing preventive measures and decisions.
2-Materials and Methods
Satellite images of MMS and OLI Landsat sensors for the years 1987 and 2014 and regression logistic modeling methods were used in order to investigate the forest cover degradation trends of Chardavol County in Ilam province. Image method with 46 ground control points was used to do the geometry correction of the images of 2014. In order to do the geometry correction of images of 1987, after correction of the image of 2014, the image to image method with 42 ground control points was used. The supervised classification method of support vector machines was used to classify the satellite images of the respective years. Conducting investigations in the studied area as well as reviewing past research in similar areas to identify the important factors of forest degradation in the region, it turned out that five factors (elevation to sea level, aspect, slope, distance to village, and distance to road) are more important and effective in destroying forests in the region. Then, forest cover changes map and physiographic (slope, aspect, altitude) and human (distance to road and distance to residential areas) variables were integrated into regression logistic model.
3-Results and Discussion
The results of the supervised classification in the studied area were compared and statistically analyzed for classification accuracy using general and Kappa reliability coefficients, as the images of years 1997 and 2014 had a total accuracy of 86.11 and 86.39%, respectively. The results of study showed that about 10332.82 ha of forest cover has been reduced in Chardavol County during 27 years which indicates an annual decline of 382.68 hectares or 0.37 percent of the initial level of forests in the area. This amount of forest cover reduction includes 382.68 ha annually. In addition, the results of modelling showed that aspect variable with the highest coefficient (0.7267) is probably the most biophysical factor affecting deforestation in study area. After that, slope and altitude variables probably affected deforestation, respectively. Distance to villages and road variables in study area are both inversely related to the amount of forest degradation. That means the greater the distance from the road and the village, the less the decline in forest cover or forest destruction is. The results of degradation in different aspects indicate that the flat areas in the area have the highest damages (4292.96 ha) and the west aspects had the least amount of destruction (278.42 ha). Assessment of regression model fitted with ROC (0.8493) and Pseudo-R2 (0.2248) indices indicated the ability of the model to describe the changes and to identify the areas prone to change. To further improve the model, the more variables such as socio-economic data (population, average income level and welfare of residential areas, number of livestock in residential areas) climate data and so on can be included in the prediction model.
4-Conclusion
Considering the comparison of the results of this study and the factors affecting the process of forest degradation in this region, further studies needed to investigate the factors affecting forest degradation in each region. Because the factors affecting forest degradation are often specific to each region and are different from other areas, even if the factors are common, their degree of importance will vary from region to area. According to the annual rate of deforestation in the area, which is more than global average, in the absence of proactive planning by provincial and national planners, perhaps, we will see the desertification phenomenon in Chardavoul county in the near future. Since spatial modeling is a good tool for better understanding of the causes of land use/land cover changes, it is hoped that the results of this research will be considered in future planning that is relevant to land-use /cover change.
