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شناسایی خشکیدگی توده‌های بلوط با استفاده از فن‌آوری سنجش از دور (مطالعه موردی: بخشی از جنگل‌های استان لرستان) | ||
| تحقیقات حمایت و حفاظت جنگلها و مراتع ایران | ||
| دوره 18، شماره 2 - شماره پیاپی 36، اسفند 1399، صفحه 244-253 اصل مقاله (918.12 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijfrpr.2021.352283.1451 | ||
| نویسندگان | ||
| افسانه محمدی1؛ مهتاب پیرباوقار* 2؛ نقی شعبانیان3 | ||
| 1دانش آموخته کارشناسی ارشد گروه جنگلداری، دانشکده منابع طبیعی دانشگاه کردستان، سنندج، ایران | ||
| 2نویسنده مسئول، دانشیار، گروه جنگلداری، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران | ||
| 3دانشیار، گروه جنگلداری، دانشکده منابع طبیعی، دانشگاه کردستان، سنندج، ایران | ||
| چکیده | ||
| بحران زوال یا خشکیدگی درختان بلوط در جنگل‌های زاگرس یکی از مشکلاتی است که در سال‌های اخیر با آن روبه‌رو بوده‌ایم. اولین گام در مدیریت این بحران، تهیه نقشه مناطق مبتلا و طبقه‌بندی شدت ابتلای جنگلها به پدیده خشکیدگی است. هدف این پژوهش بررسی قابلیت داده‌های سنجنده OLI ماهواره لندست8 در تهیه نقشه خشکیدگی توده‌های بلوط ایرانی در استان لرستان است. علاوه بر باندهای اصلی و باندهای ادغام شده با باند پانکروماتیک 15 متری سنجنده OLI، شاخص‌های گیاهی مناسب و مولفه‌های حاصل از تحلیل مولفه‌های اصلی نیز با استفاده از باندهای اصلی و ادغام شده، ایجاد شدند. به منظور ایجاد نقشه واقعیت زمینی، تعداد 150 قطعه نمونه مربعی در منطقه پیاده شد. طبقه‌بندی داده-ها به روش نظارت‌شده و با استفاده از الگوریتم‌های حداقل فاصله از میانگین، حداکثر احتمال و شبکه عصبی مصنوعی در ابتدا با پنج کلاسه خشکیدگی انجام شد. به دلیل تفکیک‌پذیری کم بین برخی از کلاسه‌ها، این کلاسه‌ها با هم ادغام شدند و طبقه‌بندی در گام دوم با سه کلاسه خشکیدگی و نهایتا با دو کلاسه (سالم، خشکیده) انجام شد. بالاترین صحت و ضریب کاپا با پنج کلاسه خشکیدگی به ترتیب معادل 53 درصد و 43/0، با سه کلاسه خشکیدگی معادل 75 درصد و 64/0 و با دو کلاسه خشکیدگی معادل 91 درصد و 71/0 با استفاده از باندهای ادغام شده و روش شبکه عصبی مصنوعی به دست آمد. نتایج به دست آمده بیانگر کارایی بالای داده‌های سنجنده OLI در تفکیک مناطق سالم و خشکیده و قابلیت کم تا متوسط آن در تفکیک شدت‌های مختلف زوال بلوط است. | ||
| کلیدواژه‌ها | ||
| زوال بلوط؛ سنجنده OLI؛ شاخص‌های گیاهی؛ طبقه‌بندی؛ واقعیت زمینی؛ جنگل‌های زاگرس | ||
| عنوان مقاله [English] | ||
| Detection of Oak Stands Dieback Using Remote Sensing (Case study: Some Parts of Lorestan Province Forests) | ||
| نویسندگان [English] | ||
| Afsaneh Mohammadi1؛ Mahtab Pir Bavaghar2؛ Naghi Shabanian3 | ||
| 1Department of Forestry, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran | ||
| 2Department of Forestry, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran | ||
| 3Department of Forestry, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran | ||
| چکیده [English] | ||
| The crisis of decline or drying of oak trees in the Zagros forests is one of the problems we have faced in recent years. The first step in managing this crisis is to map the affected areas and classify the severity of deforestation. The present study aimed to evaluate the Landsat OLI capability to map oak stands dieback in the Koohdasht city of Lorestan province. In addition to the main bands and fused bands with the 15-meter panchromatic band of the OLI sensor, suitable vegetation indices and the first components from PCA were also applied in the claasification. 150 square sample plots with dimensions of 30 × 30 meters were recorded to produce ground truth map. Data classification was done using minimum distance to mean, maximum likelihood and artificial neural networks classifiers in 5 classes of dieback and accuracy assessment was done using ground truth map. Because of the low separability of some classes, these classes were merged. Finally, classification with three and two classes (healthy, dieback) was performed. The highest overall accuracy of 53%, 75% and 91% and Kappa coefficient of 0.43, 0.64 and 0.71 was obtained using fused bands and artificial neural networks classifier for five, three and two dieback classes, respectively. The results demonstrated high performance of Landsat 8-OLI for mapping of healthy and oak dieback areas, but low to moderate functionality for identification of the intensity of oak decline in the study area. | ||
| کلیدواژه‌ها [English] | ||
| oak dieback, OLI sensor, vegetation indices, classification, ground truth, Zagros forests | ||
| مراجع | ||
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