تلفیق الگوریتم CART و شاخص‌های پوشش گیاهی در تهیه نقشه اراضی جنگلی مانگرو با استفاده از تصویر لندست 8‌

نوع مقاله: علمی - پژوهشی

نویسندگان

1 دانشگاه صنعتی اصفهان

2 دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان،

3 گروه محیط زیست، دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان

4 گروه آموزشی محیط ریست، دانشکده منابع طبیعی، دانشگاه صنعتی اصفهان

چکیده

هدف از این پژوهش تلفیق الگوریتم CART و شاخص­های پوشش گیاهی برای ارتقاء صحت نقشه­سازی جنگل­های مانگرو با استفاده از تصویر ماهواره­ای لندست 8 است. در این پژوهش هفت شاخص پوشش گیاهی DVI، NDVI، NDII، IPVI، MNDWI، SAVI و OSAVI محاسبه شد. سپس با استفاده از الگوریتم CART در نرم­افزار R شاخص­های مهم و حد آستانه آن­ها­ شناسایی و سرانجام نقشه اراضی مانگرو و اراضی پیرامون آن با روش درخت تصمیم­گیری تهیه شد. نتایج ارزیابی صحت انجام­شده با استفاده از GPS و تصویر ماهواره­ای SPOT 6/7 نشان داد که نقشه حاصل دارای صحت کلی 97/80 درصد و ضریب کاپا 74/0 است. تهیه نقشه اراضی مانگرو با دقت بالا توسط تصاویر ماهواره­ای با قدرت تفکیک متوسط به­دلیل اثر بازتاب­های زمینه (آب‌وخاک) و وجود پیکسل­های مخلوط با توجه به شرایط محیط قرارگیری مشکل است. نتایج این پژوهش نشان داد که رویکرد معرفی­شده می­تواند اطلاعات مناسبی از وضعیت جنگل­های مانگرو را برای انجام برنامه­های مدیریتی و حفاظتی اکوسیستم­های مانگرو در اختیار سیاست­گذاران و برنامه­ریزان قرار دهد.

کلیدواژه‌ها


عنوان مقاله [English]

Incorporating CART algorithm and i for mapping Mangrove using Landsat 8 imagery

نویسندگان [English]

  • neda bihamta 1
  • Ali Reza Soffianian 2
  • Sima Fakheran 3
  • Saeied Pourmanafi 4
1 Department of Natural Resourcesو Isfahan University of Technology
2 Associate Professor , Isfahan University of Technology Department of Natural Resources
3 Assistant Professor Isfahan University of Technology Department of Natural Resources
4 Assistant Professor Isfahan University of Technology Department of Natural Resources
چکیده [English]

The purpose of this study is to introduce a method for improving the accuracy of mapping mangrove covers by integrating CART algorithm and vegetation indices using Landsat 8 imagery. In this study, 7 vegetation indices were calculated including DVI, NDVI, NDII, IPVI, MNDWI, SAVI, and OSAVI. The important indicators and thresholds were identified by the CART algorithm in R-software and then the Mangrove cover besides surrounding areas was mapped using the decision tree technique. The results of accuracy assessment based on comparing control points which recorded by GPS with SPOT 6/7 images showed that the resulted map had a general accuracy of 80.97% and a kappa of 0.74. Using moderate resolution satellite imageries for mapping mangrove is difficult due to background reflectance effect (e.g. water and soil) and mixed pixels considering environmental conditions. Results demonstrated that this approach could produce information about mangroves for decision-makers in order to conservation and management planning.

کلیدواژه‌ها [English]

  • CART Algorithm
  • Mangrove forest
  • Decision tree
  • Remote sensing
  • Vegetation indices
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