پیش‌بینی فرسایش خندقی با استفاده از سنجندة راداری Alos و مدل Maxent در حوضة الوند

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی آبخیزداری، دانشگاه علوم کشاورزی و منابع طبیعی ساری

2 استاد گروه مهندسی آبخیزداری، دانشگاه علوم کشاورزی و منابع طبیعی ساری

3 استادیار دانشگاه اصفهان

چکیده

شواهد نشان می‌دهد که سنجش از دور ارزش خود را به‌‌منزلة ابزاری قدرتمند در سراسر جهان تثبیت کرده است. سنجش از دور می‌تواند هزینه‌ها را کاهش دهد و زمان اجرای طرح‌ها را کوتاه کند؛ به‌ویژه با داشتن دیدی جامع از مناطق  بزرگ که دسترسی به آنها دشوار است. هدف از پژوهش حاضر پیش‌بینی فرسایش خندقی، با استفاده از داده‌های سنجش از دور و مدل مکسنت (Maxent) در حوضة الوند، در بخش غربی استان کرمانشاه است. حوضة الوند، به‌دلیل وسعت و آلوده‌بودن به مین و هم‌مرزبودن با کشورعراق، با مشکل دسترسی مواجه است. از سوی دیگر، قالب‌بودن اراضی مارنی و نبود پوشش گیاهی مناسب باعث چیرگی فرسایش خندقی در منطقه شده است. بر همین اساس، در پژوهش حاضر، با کار ترکیبی حاصل از بازدید میدانی و سنجش از دور که در محیط گوگل ارث انجام گرفت، لایة‌ تحلیل مکانی مورد نیاز مدل مکسنت تهیه و پهنة مناطق خندقی رقومی‌سازی شد و به‌صورت‌ متغیرهای مستقل، به مدل معرفی شد. همچنین، برای تجزیه و تحلیل سطح زمین، مدل رقومی ارتفاعی رادار سنجندة الوس به‌کار رفت و پانزده لایة محیطی با دقت تفکیک دَه متر به‌منزلة‌ متغیرهای وابسته تهیه شدند. با استفاده از این مدل کمی و آماری، سه هدف ذیل تحقق یافت: 1. میزان تأثیر هر لایة محیطی با استفاده از آزمون Jackknife به‌دست آمد؛ 2. روند بیشترین و کمترین تأثیر هر پارامتر، با استفاده از رگرسیون لجستیک، بررسی شد؛ 3. نقشة پتانسیل فرسایش خندقی برای کل منطقه تهیه شد. سپس اعتبار‌سنجی مدل، با استفاده از منحنی ROC و محاسبة مساحت زیرمنحنی(AUC) ، صورت گرفت. نتایج به‌دست‌آمده نشان داد مؤثرترین شاخص در ایجاد فرسایش خندقی مربوط به شاخص ارتفاع، فاصلة عمودی از سطح کانال و تجمع جریان است و اعتبارسنجی برابر  با AUC=0.899  است که سطح خوب نتایج را نشان می‌دهد. 

کلیدواژه‌ها

عنوان مقاله [English]

Prediction of Gully Erosion Using RADAR Sensor of Alos and Maximum Entropy Model in Alvand Basin

نویسندگان [English]

  • S Pirouzinejad 1
  • Solaimani, K Solaimani 2
  • M Habibnejad Roshan 2
  • R Zakerinejad 3
1 . M.Sc. Student of Watershed Eng. Dep., Sari Agricultural Sciences and Natural Res. University
2 Prof. of Watershed Eng. Dep., Sari Agricultural Sciences and Natural Res. University
3 Assistant Professor of Isfahan University
چکیده [English]

The evidences showing that remote sensing has a significant role as a powerful tool around the world, which can reduced the costs and time of projects, especially since they have a comprehensive view of the large areas where are difficult to access. This study has aimed to predict gully erosion using remote sensing data and Maxent model in Alvand basin located in the western part of Kermanshah province, Iran. Alvand basin with a difficulty accessing due to the extent of the minefield during the imposed war and interconnected with Iraq, on the other hand, the shape of Marne lands and absence of proper vegetation have led to acceleration of gully erosion. Therefore, in this study with a combination method of fieldwork and remote sensing which used in the Google Earth environment, then the essential spatial analysis layout has prepared by Maxent model and the zonation of the gully area has digitized as independent variables that introduced to model. In addition, for analysing the ground surface, a digital elevation model of the Alos data has used with 15 environmental layers of 10/m resolution were prepared as dependent variables. Three goals have attained based on this quantitative and statistical model. First, the effect level of each environmental layer has obtained using the Jackknife test. Second, trend of maximum and minimum effects of each parameter has investigated using logistic regression and finally, Potential map of gully erosion was prepared for the whole region. Then the model validation has performed using the ROC curve and the area under the curve (AUC). It has concluded that the most effective index in gully erosion creation related to elevation index, vertical distance from channel level and flow accumulation. The validation is calculated equal to AUC = 0.899, which shows a good level of results.

کلیدواژه‌ها [English]

  • Gully erosion
  • remote sensing
  • Maximum entropy model and Kermanshah
  • Iran

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