نشریه علمی - پژوهشی مرتع و آبخیزداری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دکتری علوم مرتع ، ادارۀ کل منابع طبیعی و آبخیزداری خراسان شمالی، ایران.

2 دانشیار دانشکدۀ منابع طبیعی، دانشگاه صنعتی اصفهان، ایران.

3 استادیار دانشکدۀ منابع طبیعی، دانشگاه صنعتی اصفهان، ایران.

چکیده

از میان فاکتورهای مدل اصلاح‌شده جهانی فرسایش خاک (RUSLE)، فاکتور پوشش و مدیریت (فاکتور C) یکی از عوامل مهم و اثرگذار بر میزان فرسایش خاک است. تعیین فاکتور C بر اساس روش‌های اصلی معرفی‌شده با توجه به فقدان اطلاعات دقیق در بسیاری از مناطق مشکل است. در این روش نقشۀ پوشش گیاهی می‌تواند در جهت برآورد فاکتور C مورد استفاده قرار گیرد، اما تهیۀ نقشۀ مناسب از درصد پوشش گیاهی در بسیاری از شرایط یک چالش است. درنتیجه در این مطالعه نقشۀ درصد تاج پوشش گیاهی تهیه شده با استفاده از الگوریتم نا پارامتریک k-NN، رگرسیون خطی و رگرسیون خطی گام‌به‌گام در حوضۀ آبخیز شیرین درۀ خراسان شمالی تهیه و مورد مقایسه قرار گرفت. در روش‌های رگرسیونی 17 شاخص گیاهی و محیطی تهیه و روابط آن‌ها بررسی شد. نتایج مقایسۀ نقشه‌های حاصل از 3 روش نشان داد که روش k-NN به دلیل دارا بودن بالاترین درصد صحت کلی (3/83 درصد) و ضریب کاپا (9/75 درصد) نسبت به دو روش رگرسیونی دیگر از نتایج مناسب‌تری برخوردار است، ازاین‌رو جهت تهیۀ فاکتور مدیریت و پوشش (C) مورداستفاده قرار گرفت. نتایج مطالعه نشان داد که روش نا پارامتریک k-NN دارای نتایج امیدوارکننده‌ای در جهت تهیۀ نقشه‌های درصد تاج پوشش گیاهی مراتع مناطق خشک و نیمه‌خشک است. در میان شاخص‌های گیاهی شاخص گیاهی NDVI بیشترین همبستگی (82/0) را با درصد پوشش گیاهی دارد. همچنین درروش k-NN معیار فاصلۀ اقلیدسی در نقطۀ 9=k نسبت به دو معیار دیگر ماهالانوبیس و فازی نتایج مناسب‌تری دارد و می‌تواند نقشه درصد پوشش گیاهی را با دقت بالاتری برآورد نماید.

کلیدواژه‌ها

عنوان مقاله [English]

Using k Nearest Neighbor (k-NN) algorithm as a suitable approach to estimate cover-management factor of RUSLE model in Shirin Dareh basin, North Khorasan

نویسندگان [English]

  • Emad Zakeri 1
  • Hamidreza karimzadeh 2
  • Seyed Alireza Mousavi 3

1 Ph.D. Range Management, Department of Natural Resources and Watershed Management of North Khorasan province, Iran

2 University of Isfahan Tecnology

3 Department of Natural Resources Isfahan /University of Technology /]Isfahan/Iran

چکیده [English]

Cover-management factor (C) is one of the most important influential factor on soil erosion using the Revised Universal Soil Loss Equation (RUSLE) model. C-factor is challenging to determine based on the proposed procedures due to lack of accurate information. Vegetation cover map can be used to estimate C-factor, but preparing a suitable mapping of vegetation cover is challenging in many situations. Therefore, in this study vegetation cover map was prepared and compared using the k Nearest Neighbor (k-NN) algorithm, linear regression (LR) and linear stepwise regression (LSR) in the study area. In regression methods, 17 vegetation and environmental indices were prepared and their relationships were investigated. The results of comparing the three methods showed that the k-NN method has better results than other regression methods due to its highest overall accuracy (83.3%) and kappa coefficient (75.9%) therefore, it was used to produce C-factor map. Results showed that the k-NN was very promising for mapping vegetation canopy cover in the arid and semi-arid areas. The results showed that among vegetation indices NDVI had the highest correlation (0.82) with percentage vegetation cover. Also, in the k-NN method, the Euclidean distance metrics in k = 9 has better results than the other two Fuzzy and Mahalanobis distances and can be used to estimation of vegetation cover map.

کلیدواژه‌ها [English]

  • Soil Erosion
  • Cover-management factor
  • Vegetation indices
  • GIS
  • nonparametric algorithms
  • k Nearest Neighbor
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