مدل‌سازی مکانی احتمال وقوع آتش‌سوزی در جنگل‌ها و مراتع با استفاده از مدل‌های نسبت فراوانی و وزن شاهد

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد، گروه علوم جنگل، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد، شهرکرد، ایران

2 گروه علوم جنگل، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد

3 استادیار، گروه علوم جنگل، دانشکده منابع طبیعی و علوم زمین، دانشگاه شهرکرد، شهرکرد، ایران

4 استادیار 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


عنوان مقاله [English]

Spatial modeling the probability of wildfire occurrence using frequency ratio and weight- of-evidence models

نویسندگان [English]

  • M. Omidi 1
  • Davood Mafi Gholami 2
  • B. Mahmoodi 3
  • A. Jafari 4
2 Department 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
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