توسعه‌ی یک روش داده‌کاوی درخت تصمیم جهت شناسایی پارامترهای مؤثر در تعیین قدرت تخریب سیل

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشکده مهندسی عمران و نقشه برداری، دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته، کرمان، ایران.

چکیده

سیل یکی از بلایای ‌طبیعی می‌باشد که به زیر ساخت‌های شهری، زمین‌های کشاورزی و منابع طبیعی خسارات جبران ناپذیری وارد می‌نماید. لذا دست‌یابی به اطلاعات جامع در مورد عوامل مؤثر بر میزان قدرت تخریب سیل می‌تواند در برآورد میزان خسارت وارده مفید واقع شود. از این رو، در این تحقیق، هدف ایجاد پایگاه ‌داده پارامترهای تأثیر‌گذار در قدرت تخریب سیل به صورت موردی با بکارگیری تصاویر ماهواره لندست-7 با سنجنده ETM+ و داده‌های DEM ASTER می‌باشد که در آن از روش داده‌کاوی درخت ‌تصمیم استفاده شده است. در این تحقیق پارامترهای محیطی نظیر پوشش گیاهی، شیب طبیعی زمین و جهت شیب به منظور ارزیابی قدرت تخریب سیل در منطقه مورد مطالعه در نظر گرفته شده‌اند و مدل درخت تصمیم با استفاده از این معیارها ایجاد شد. در نهایت براساس این پارامترها، تعداد پیکسل­های تغییر یافته (بعد از وقوع سیلاب) در منطقه مورد مطالعه 692361 می‌باشد که بیانگر 62312/49 هکتار اراضی تخریب شده در منطقه مورد‌ مطالعه است. با توجه به یافته‌های تحقیق حاضر، اراضی با ویژیگی‌های پوشش گیاهی کم، به عبارت دیگر دارای شاخص پوشش‌ گیاهی تفاضلی نرمال شده (NDVI) بین 0/2 تا 0/4، شیب پایین 0 تا 45 درجه و جهت شیب جنوبی بیشترین تخریب ناشی از سیل را دارند. همچنین مناطقی که دارای NDVI متراکم، شیب زیاد و جهت شیب شمالی می‌باشند، کمترین تأثیر را از سیل می‌پذیرند. در نهایت، می‌توان نتیجه گرفت که روش داده‌کاوی درخت تصمیم با افزایش متغیرهای ورودی دقت و کیفیت بهتری در تعیین پارامترهای مؤثر در برآورد قدرت تخریب سیل ارائه می‌دهد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Developing a Decision Tree based on Data Mining Method for Detecting the Influential Parameters on the Power of Flood Destruction

نویسندگان [English]

  • Hadi Farhadi
  • Ali Esmaeily
  • Mohammad Najafzadeh
M.Sc. Student in Remote Sensing Engineering, Department of Surveying Engineering, Faculty of civil and surveying Engineering, Graduate University of Advanced Technology, Kerman
چکیده [English]

Floods, as one of the natural disasters, cause irreparable damages to the urban infrastructures, agricultural lands, and natural resources. Therefore, access to comprehensive information on influential factors the extent of flood damage can be useful in estimating the extent of the damage. In this way, this study investigates the creation of a database of effective parameters on flood destruction power using a case study of Landsat-7 satellite images with ETM+ sensor and ASTER DEM data using a decision tree. In the current research, environmental parameters such as canopy, natural slope, and slope direction were considered to evaluate flood degradation power in the study area and the decision tree model was created using these criteria. Ultimately, based on these parameters, the number of changed pixels (after the flood) in the study area is 692361 which indicates 62312.49 hectares of degraded land in the study area. According to the findings of the present study, lands with low canopy characteristics, namely normalized differential vegetation index (NDVI) between 0.2 and 0.4, low slope 0 to 45 degrees, and Southern slope direction caused the most damage caused by floods. Also, areas with dense NDVI, high slope, and northern slope orientation have a preventative influence on floods-caused damages. Overall, it can be found that the decision tree, as a data mining method, is capable of yielding better accuracy and quality in determining the effective parameters in estimating flood destruction power by increasing the input variables.

کلیدواژه‌ها [English]

  • Flood
  • Decision tree
  • Data mining
  • Change detection
  • Landsat-7
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