تهیۀ نقشه تراکم تاج پوشش جنگل‌های زاگرس با استفاده از تصاویر لندست 9 و عکس‏برداری نیم‏کره ‏ای

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دکتری جنگلداری، گروه مهندسی جنگل، برنامه‌ریزی مدیریت جنگل و اندازه‌گیری‌های زمینی، دانشکده جنگلشناسی و مهندسی جنگل، دانشگاه براشوف، براشوف، رومانی

2 کارشناسی ارشد جنگلداری، دانشکدۀ منابع طبیعی، دانشگاه ارومیه، ارومیه، ایران.

3 دکتری جنگلداری، دانشکدۀ منابع طبیعی، دانشگاه ارومیه، ارومیه، ایران

4 دانشجوی دکتری جنگلداری، دانشکده منابع طبیعی دانشگاه ارومیه، ارومیه، ایران.

چکیده

هدف از این پژوهش ارزیابی مدل تراکم تاج پوشش جنگل (FCD) و نرم‏افزار تلفن همراه GLAMA در تخمین تراکم تاج پوشش جنگل‏های زاگرس در شهرستان سردشت است. بدین منظور داده‏های ماهواره‏ای لندست 9 مربوط به سال 1401 مورد استفاده قرار گرفت. برای اجرای مدل، چهار شاخص شامل: 1) شاخص پوشش گیاهی پیشرفته، 2) شاخص خاک لخت، 3) شاخص سایه، و 4) شاخص حرارتی محاسبه شدند. سپس با ترکیب و سنتز این شاخص‏ها، شاخص‏های سایه پیشرفته و تراکم گیاهی محاسبه و در نهایت با ادغام این دو شاخص، نقشه مدل FCD تهیه شد. برای اعتبارسنجی مدل تهیه­شده از عکس‏برداری نیم‏کره‏ای تحت نرم‏افزار GLAMA استفاده شد. بدین منظور تعداد 100 قطعه‏نمونه مربعی شکل در سطح شهرستان سردشت با تاج پوشش‏های مختلف انتخاب و عکسبرداری از تاج پوشش در پنج نقطه از هر قطعه‏نمونه انجام شد. ارزیابی قابلیت طبقه‏های مختلف مدل FCD تهیه شده برای شهرستان سردشت، نشان‏دهندۀ صحت کل 76 درصد و مقدار ضریب کاپای 697/0 بود. همچنین نتایج همبستگی بین میانگین مقادیر شاخص تاج پوشش محاسبه شده توسط عکس‏برداری نیم‏کره‏ای و مقادیر به‏دست‏آمده توسط مدل FCD همبستگی بالا (985/0=R2) و معنی‏داری (0001/0 >= p-value) را نشان داد. از این‏رو، می‏توان بیان داشت که مدل FCD تهیه شده با استفاده از داده‏های ماهواره‏ای لندست 9 و نرم‏افزار تلفن همراه GLAMA دارای کارایی بسیار مناسبی در جنگل‏های زاگرس در تخمین درصد تراکم تاج پوشش اراضی جنگلی هستند.

کلیدواژه‌ها


عنوان مقاله [English]

Forest cover density mapping of Zagros forests using Landsat-9 imagery and ‎hemispherical photographs

نویسندگان [English]

  • Hadi Beygiheidarlou 1
  • Asma Karamat Mirshekarlou 2
  • Samira Sasanifar 3
  • Bakhtear Khezryan 4
1 PhD of Forestry, Department of Forest Engineering, Forest Management Planning and Terrestrial Measurements, ‎Faculty of Silviculture and Forest Engineering, Transilvania University of Brasov, Brasov, Romania
2 MSc of Forestry, Faculty of Natural Resources, Urmia University, Urmia, Iran.
3 Ph.D. of Forestry, Faculty of Natural Resources, Urmia University, Urmia, Iran
4 Ph.D. student of forestry, Faculty of Natural Resources, Urmia University, Urmia, I.R. Iran‎
چکیده [English]

The goal of this study is to see how well the forest canopy density (FCD) model and the GLAMA mobile ‎app estimate the canopy cover density of Zagros forests in Sardasht province. Landsat 9 Operational Land ‎Imager-2 (OLI-2) in 2022 was employed for this purpose. Four indices were created to run the model: 1- Advanced ‎Vegetation Index, 2- Bare Soil Index, 3- Shadow Index, and 4- Thermal Index. The Scaled Shadow Index and Vegetation Density index were then computed by integrating and synthesizing indices one and two, as well as indices three and four, and the FCD model map was created by combining these two indices. The created model was validated using GLAMA mobile app and ‎hemispherical photographs. For this purpose, 100 square sample plots in Sardasht city with varying canopy ‎cover were chosen, and photographs of the canopy cover were taken at five positions on each sample ‎plot. The overall accuracy of the FCD model generated for Sardasht Province was 76%, with a Kappa ‎coefficient of 0.697. Furthermore, the correlation results demonstrate a strong (R2‎ = 0.985) and significant ‎‎(p-value = <0.0001) correlation between the average canopy cover index values estimated by ‎hemispherical photography using GLAMA software and the values acquired by the FCD model. According ‎to the findings of this study, the FCD model developed using Landsat 9 satellite data and the GLAMA ‎mobile app performs very well in estimating forest land canopy density in Zagros forests.

کلیدواژه‌ها [English]

  • Canopy cover
  • GLAMA mobile app
  • Hemispherical photography
  • Landsat 9
  • Zagros
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