دوره 6، شماره 11 - ( بهار و تابستان 1397 )
جلد 6 شماره 11 صفحات 75-61 |
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Pourahmad M, Oladi J, Fallah A. (2018). Detection of Tree Species in Mixed Broad-Leaved Stands of Caspian Forests Using UAV Images (Case study: Darabkola Forest). Ecol Iran For. 6(11), 61-75. doi:10.29252/ifej.6.11.61
URL: http://ifej.sanru.ac.ir/article-1-240-fa.html
URL: http://ifej.sanru.ac.ir/article-1-240-fa.html
پوراحمد میلاد، اولادی جعفر، فلاح اصغر. شناسایی گونه‌های درختی در توده‌های پهن‌برگ آمیخته جنگل‌های خزری با استفاده از تصاویر پهپاد (مطالعه موردی: جنگل دارابکلا)
بوم شناسی جنگل های ایران (علمی- پژوهشی) 1397; 6 (11) :75-61 10.29252/ifej.6.11.61
1- دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری
چکیده: (7947 مشاهده)
تصاویر پهپاد، با توان تفکیک مکانی بالا، یک منبع اطلاعاتی باارزش برای تهیه نقشه پوشش زمین و اطلاعات موضوعی به ویژه تشخیص گونه های درختی هستند. هدف از این تحقیق بررسی قابلیت تصاویر پهپاد و روش شیءپایه در تشخیص گونه های درختی در جنگل های پهن‌برگ خزری است. به‌این منظور بخشی از پارسل 24 در سری یک دارابکلای مازندران انتخاب شد. نقشه واقعیت زمینی موقعیت گونه های غالب از طریق ثبت دقیق با الگوریتم تعیین مختصات جغرافیایی با استفاده از فاصله و آزیموت در نرم‌افزار متلب تهیه شد. پس از پردازش های مناسب بر روی تصاویر، طبقه بندی به روش شیءپایه بر روی مجموعه تصاویر در سه ارتفاع پروازی 100، 75 و 55 متری به دو صورت طبقه‌بندی یک مرحله‌ای و طبقه‌بندی سلسله‌مراتبی انجام شد. در روش شیءپایه از فن نزدیکترین همسایه برای طبقه بندی گونه ها استفاده شد. ارزیابی صحت
نقشه های حاصل ازطبقه بندی ها با استفاده از 50 درصد نمونه های واقعیت زمینی انجام گرفت. نتایج نشان داد که نقشه حاصل از طبقه بندی سلسله‌مراتبی به روش شیءپایه در ارتفاع پروازی 55 متر بهترین توانایی تشخیص گونه های درختی را در بین سه ارتفاع، با ضریب کاپای 81/0 و صحت کلی 87 درصد داراست.
نقشه های حاصل ازطبقه بندی ها با استفاده از 50 درصد نمونه های واقعیت زمینی انجام گرفت. نتایج نشان داد که نقشه حاصل از طبقه بندی سلسله‌مراتبی به روش شیءپایه در ارتفاع پروازی 55 متر بهترین توانایی تشخیص گونه های درختی را در بین سه ارتفاع، با ضریب کاپای 81/0 و صحت کلی 87 درصد داراست.
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