نشریه علمی - پژوهشی مرتع و آبخیزداری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 مربی گروه مرتع و آبخیزداری، دانشکدة منابع طبیعی، دانشگاه صنعتی خاتم‌الانبیاء(ص) بهبهان

2 استادیار گروه مرتع و آبخیزداری، دانشکدة منابع طبیعی، دانشگاه صنعتی خاتم‌الانبیاء(ص) بهبهان

3 استادیار گروه مرتع و آبخیزداری، دانشکدة منابع طبیعی، دانشگاه صنعتی خاتم‌الانبیا ء(ص) بهبهان

4 استادیار گروه مرتع و آبخیزداری، دانشکده منابع طبیعی، دانشگاه صنعتی خاتم الانبیاء(ص) بهبهان

چکیده

تهیۀ نقشۀ پوشش گیاهی از موارد اساسی در مدیریت مراتع می­باشد زیرا تیپ­های گیاهی واحدهای برنامه­ریزی در مدیریت مراتع می‌باشد. برای تهیۀ نقشۀ تیپ­های گیاهی مراتع با استفاده از الگوریتم­های مختلف طبقه­بندی تصویر ماهوارۀ لندست8 در مراتع در شهرستان بهبهان استان خوزستان انجام گردید. مراتع منطقه جزء مراتع نیمه­استپی قشلاقی می باشد. عمل تصحیح هندسی تصویر ماهواره­ای با استفاده از نقاط کنترل زمینی­ با خطای کمتر از یک پیکسل انجام شد. تصحیح اتمسفری تصویر با استفاده از از روش تفریق عارضه تاریک انجام شد. بازدیدهای صحرایی جهت تهیۀ نقشۀ تیپ­ها و برداشت نمونه­های تعلیمی انجام شد. طبقه­بندی نظارت شده با شش الگوریتم شامل متوازی السطوح (PP)، حداقل فاصله از میانگین (MD)، فاصلۀ ماهالانوبیس (MAH)، حداکثر احتمال (ML)، شبکۀ عصبی مصنوعی (NN) و ماشین بردار پشتیبان (SVM) انجام شد. نتایج نشان داد که الگوریتم ML دارای بیشترین صحت کلی (5/87 درصد) و ضریب کاپا (867)/0 و الگوریتم PP دارای کمترین صحت کلی (1/67) و ضریب کاپا (571/0) می­باشد. نقشۀ تیپ­های گیاهی حاصل از طبقه­بندی تصویر سنجنده OLI دارای صحت قابل قبولی است. پیشنهاد می شود در کنار روش­های رقومی طبقه­بندی تصاویر ماهواره­ای از تفسیر بصری جهت تدقیق مرز نقشۀ تیپ­های گیاهی حاصله استفاده شود.

کلیدواژه‌ها

عنوان مقاله [English]

Producing rangeland vegetation types map using different algorithms of satellite image classification

نویسندگان [English]

  • Shahram Yousefi khanghah 1
  • Damoon Razmjuee 2
  • Somayyie Dehdari 3
  • Nasim Arman 4

1   Behbahan Khatam Alanbia University of Technology

2 Assistant professor Rangeland and watershed management department, Faculty of natural resources, Behbahan Khatam-Alanbia University of Technology

3 Rangeland and watershed management department, Faculty of natural resources, Behbahan Khatam-Alanbia University of Technology

4 Rangeland and watershed management department, Faculty of natural resources, Behbahan Khatam-Alanbia University of Technology

چکیده [English]

To better managing of rangeland the vegetation map is one of major factors, because plant communities is planning units of rangeland management and vegetation map shows the current status of plant communities. This research was conducted to produce vegetation type's map using Landsat 8 image classification in Behbahan, Khuzestan province. Rangelands of the study region is warm semi steppe and winter grazing. Geometric correction of satellite image was performed by ground control points with an error of less than one pixel. Atmospheric correction of existing data using the dark object subtraction was done. Field visits for vegetation type's border controlling and sampling training area was conducted. Eight supervised classification algorithms included Parallelepiped (PP), Minimum Distance to mean (MD), Mahalanobis distance (MAH), Maximum Likelihood (ML), Neural Net (NN) and Support Vector Machine (SVM) was performed. The results showed that ML algorithm has the highest overall accuracy (87.5 percent) and kappa (0.867) and PP algorithm has the lowest overall accuracy (67.1 percent) and kappa (0.571). It is suggested that, along with digital methods of classification of satellite images, visual interpretation should be used to clarify the boundary of the obtained vegetation types map.

کلیدواژه‌ها [English]

  • Vegetation Type
  • Semiarid
  • Classification
  • Landsat
  • OLI
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