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مدلسازی مکانی احتمال وقوع آتشسوزی در جنگلها و مراتع با استفاده از مدل‌های نسبت فراوانی و وزن شاهد | ||
| تحقیقات حمایت و حفاظت جنگلها و مراتع ایران | ||
| مقاله 2، دوره 17، شماره 2 - شماره پیاپی 34، اسفند 1398، صفحه 125-144 اصل مقاله (1.09 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijfrpr.2020.121301 | ||
| نویسندگان | ||
| مرجان امیدی1؛ داود مافی غلامی* 2؛ بیت‌الله محمودی3؛ ابوالفضل جعفری4 | ||
| 1دانشجوی کارشناسی ارشد، گروه علوم جنگل، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد، شهرکرد، ایران | ||
| 2گروه علوم جنگل، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد | ||
| 3استادیار، گروه علوم جنگل، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد، شهرکرد، ایران | ||
| 4استادیار پژوهش، مؤسسه تحقیقات جنگلها و مراتع کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، تهران، ایران | ||
| چکیده | ||
| طی سالهای اخیر، تلاشهای زیادی برای مدیریت و مهار آتشسوزی در جنگلها و مراتع شده است. از مهمترین این اقدامات، مدلسازی احتمال وقوع آتشسوزی و تهیه نقشههای پهنهبندی در مناطق حساس به آتشسوزی است. در این تحقیق، قابلیت مدل‌های نسبت فراوانی و وزن شاهد در پیشبینی احتمال وقوع آتشسوزی در جنگلها و مراتعاستان کهگیلویه و بویراحمد بررسی شده است. فرایند مدلسازی و پیشبینی وقوع آتشسوزیهای آینده بر مبنای بررسی ارتباط بین 271 مورد آتشسوزی از دوره 1395-1381 و 10 عامل درجه شیب، جهت، ارتفاع، درجه حرارت، سرعت باد، کاربری اراضی، شاخص تفاضلی نرمال شده پوشش گیاهی (NDVI) و فاصله تا رودخانه، جاده و مناطق مسکونی انجام شد. طی فرایند مدلسازی، میزان تأثیر هر طبقه از عوامل بر وقوع آتشسوزی محاسبه شد. نتایج مدلها مبنای ساخت نقشههای حساسیت به آتشسوزی در سطح استان قرار گرفت. نتایج ارزیابی و مقایسه مدلها که با استفاده از روش منحنی مشخصه نسبی، میزان موفقیت، نرخ پیشبینی و آزمون مقایسه جفتی ویلکاکسون انجام شد، اختلاف معنیداری را در عملکرد دو مدل نشان داد. به‌طوری‌که مدل وزن شاهد با نرخ موفقیت و پیشبینی 862/0 و 821/0 عملکرد بهتری نسبت به مدل نسبت فراوانی در تحلیل دادههای آموزشی و پیشبینی آتشسوزیهای آینده داشت. بر‌اساس نتایج به‌دست آمده حدود 30 درصد از وسعت جنگلها و مراتع استان کهگیلویه و بویراحمد در طبقات حساسیت زیاد تا بسیار زیاد به آتشسوزی قرار میگیرد که نیازمند اقدامات پیشگیرانه و مدیریت صحیح برای کاهش مخاطرات ناشی از آتش است. | ||
| کلیدواژه‌ها | ||
| مخاطرات طبیعی؛ مدلسازی؛ آتش سوزی؛ پهنه بندی حساسیت | ||
| عنوان مقاله [English] | ||
| Spatial modeling the probability of wildfire occurrence using frequency ratio and weight- of-evidence models | ||
| نویسندگان [English] | ||
| M. Omidi1؛ Davood Mafi Gholami2؛ B. Mahmoodi3؛ A. Jafari4 | ||
| 2Department of forest science, faculty of natural resources and earth sciences, Sahrekord university, Sahrekord, Iran | ||
| چکیده [English] | ||
| In recent years, many attempts have been made to manage and control wildfires. Modeling and mapping wildfire probability across fire-prone landscapes is one of the most important measures. In the present study, the capability of frequency ratio and weight-of-evidence models for predicting the probability of wildfires occurrence in the Kohgiluyeh and Boyer-Ahmad province were investigated. The modeling process and prediction of future fires were based on an analysis of the relationship between 271 historical fires occurred during the 2002-2014 period and 10 predictor variables including slope degree, aspect, altitude, temperature, wind speed, land use, NDVI, and proximity to rivers, roads, and human settlement. During the modeling process, the significance of each variable class on wildfire occurrence was quantified. The model results were used to produce distribution maps of wildfire probability. The results of the evaluation and comparison of the models, which were carried out using the receiver operating characteristic method, success rate, prediction rate, and Wilcoxon test showed that the weight-of-evidence model with success and prediction rates of 0.886 and 0.821 performed better than the frequency ratio model in both training and validation datasets. Overall, the results revealed that approximately 30% of the forests and rangelands of the province fall within the high and very high probability to wildfire occurrence, which requires prudent management measures to mitigate the risk of fire. | ||
| کلیدواژه‌ها [English] | ||
| Natural hazards, Modeling, Wildfire, susceptibility mapping | ||
| مراجع | ||
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