نشریه علمی - پژوهشی مرتع و آبخیزداری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری ژئومورفولوژی دانشگاه تربیت مدرس، تهران، ایران.‏

2 استادیار مرکز تحقیقات کشاورزی و منابع طبیعی استان اصفهان، اصفهان، ایران.‏

3 استادیار دانشکده منابع طبیعی، دانشگاه اردکان، یزد، ایران.‏

چکیده

هدف از این پژوهش شناسایی عوامل مؤثر در رخداد زمین‌لغزش و پهنه‌بندی حساسیت آن با استفاده از روش‌های ‏رگرسیون لجستیک و رگرسیون چند متغیره خطی است. بدین منظور در ابتدا با استفاده از تفسیر عکس‌های هوایی ‏با مقیاس 1:40000، نقشه‌های توپوگرافی، زمین‌شناسی و عملیات میدانی با استفاده از GPS‎، نقشه پراکنش زمین‌لغزش‌ها به‌صورت سطح به‌عنوان متغیر وابسته تهیه گردید. برای تعیین عوامل مؤثر در رخداد زمین‌لغزش از آنالیز ‏مقادیر عددی پارامترها با روش ماشین‌های بردار پشتیبان در محیط نرم‌افزار ‏Rapid Miner‏ استفاده گردید و از ۲۱ لایه ‏اطلاعاتی انتخابی، ۱۵ لایه اطلاعاتی انتخاب و جهت تهیه نقشه پهنه‌بندی به‌عنوان متغیر مستقل در محیط‎ ArcGIS ‎‎10.1‎‏ تهیه و رقومی گردیدند. پس از وزن دهی به لایه‌ها، نقشه پهنه‌بندی با استفاده از روش‌های انتخابی در ۵ کلاس ‏خیلی کم، کم، متوسط، زیاد و خیلی زیاد تهیه گردید. نتایج وزن دهی لایه‌ها نشان داد که در هر دو روش، کاربری اراضی ‏و جهت شیب بیشترین تأثیر را در وقوع زمین‌لغزش داشته‌اند. منحنی ‏ROC‏ و مساحت زیر منحنی ‏‎(AUC)‎‏ برای نقشه‌های پهنه‌بندی ترسیم و از ‏AUC‏ برای صحت سنجی استفاده گردید و مقادیر حاصل از آن نشان داد که مدل چند ‏متغیره خطی (‏‎ ‎‏۸۹۰/۰) دارای کارایی بالاتری نسبت به مدل لجستیک (۸۲۹/۰) جهت پهنه‌بندی خطر زمین‌لغزش است. بر اساس نتایج مدل برتر (چند متغیره خطی)، ‏۱/۱۶۰۴۶‏ هکتار (۱۳/۲۰ درصد) از منطقه در رده خطر زیاد ‏و ‏۲/۱۵۶۷۱‏ هکتار (۶۶/۱۹ درصد) از منطقه در رده خطر خیلی زیاد قرار گرفته است.

کلیدواژه‌ها

عنوان مقاله [English]

Assessment of logistic and multivariate regression Models for Landslide hazard zonation (Case Study: Marbor basin)

نویسندگان [English]

  • ALIREZA Arabameri 1
  • kourosh shirani 2
  • Mahdi Tazeh 3

1

2

3

چکیده [English]

Present study seeks to identify effective factors in landslide occurrence and landslide sensitivity zonation using logistic regression and multivariate linear regression. Accordingly, through the interpretation of arial photos with scale of 1:40000, geological, topographic maps, and field survey using GPS, landslide hazard map was prepared as dependent variables. For determination of effective factors in landslide occurrence, using Support Vector Machines in Rapid Miner Software, the numerical values of the parameters were analyzed and from 21 selective data layers, 15 data layers were selected and were prepared and digitized for zonation map as the independent variable in ArcGIS 10.1. After weighing the layers, zonation map was prepared using selective method in five classes: very low, low, moderate, high and very high. Result of weighting layers showed that in both methods, land use and aspect have the greatest impact on landslides. The ROC (Receiver operating characteristic) curves and area under the curves (AUC) for landslide susceptibility maps were constructed and the areas under curves was assessed for validation purpose and its values showed that multivariate linear regression model (0.890) has a higher efficiency than the logistic model (0.829) for landslide hazard zonation. According to result of superior model (multivariate linear regression), 16046.1 hectare (20.13%) of the region was found to be located in high risk class and 15671.2 hectare (19.66%) was in very high risk class.

کلیدواژه‌ها [English]

  • "Landslide"
  • "Zonation"
  • "Evaluation"
  • "MR Model"
  • "logistic regression model"
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