شناسایی گونه های درختی پلت و ممرز با استفاده از مشخصه های هندسی و آماری به‌دست‌آمده از داده های لیدار هوایی

نوع مقاله: علمی- پژوهشی

نویسندگان

1 دانشجوی دکتری جنگل‌داری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس

2 استاد، گروه جنگل‌داری و اقتصاد جنگل، دانشکده منابع طبیعی، دانشگاه تهران

3 استاد، گروه جنگل‌داری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس

4 دانشیار، دانشکده جنگل‌داری، دانشگاه علوم کشاورزی و منابع طبیعی گرگان

چکیده

در این پژوهش امکان استفاده از مشخصه­ های هندسی و آماری به‌دست‌آمده از داده­ های لیدار برای شناسایی پایه­ های درختی پلت (Acer velutinum) و ممرز (Carpinus betulus) در سری یک جنگل‌ آموزشی- پژوهشی شصت­ کلاته گرگان بررسی شد. برای این منظور داده­ های لیدار درختان نمونه از کل ابر نقاط لیزر منطقه مورد مطالعه با استفاده از مختصات مرکز تنه و قطر تاج (برداشت­ شده در زمین) جداسازی شد. در عملیات میدانی، 80 پایه درختی از دو گونه پلت و ممرز که در آشکوب چیره واقع بودند و یا تداخل تاجی با پایه­ های مجاور نداشتند، به­ عنوان درختان نمونه انتخاب شدند. ارتفاع درختان نمونه با استفاده از دستگاه Vertex IV و شعاع تاج آنها در چهار جهت جغرافیایی به کمک فاصله­ یاب لیزری Leica Disto اندازه­ گیری شد و موقعیت مرکز آنها با استفاده از سیستم موقعیت ­یاب جهانی تفاضلی (DGPS) و نیز به روش فاصله و آزیموت با استفاده از دوربین توتال استیشن برداشت شد. ویژگی‌های مختلف آماری و هندسی از داده­ های لیدار درختان نمونه استخراج و برای تفکیک گونه پایه­ های درختی در تابع تحلیل تشخیص مورد استفاده قرار گرفت. نتایج نشان داد که متغیرهای انحراف‌معیار ارتفاعی نقاط لیزر در بالای 0/8 ارتفاع درخت و شیب تاج بهترین ترکیب متغیرها بودند که با صحت کلی 80/3 درصد دو گونه را از یکدیگر تفکیک کردند. این درحالی است که میانگین این دو ویژگی در ممرز بیشتر از پلت بود. به­ طور کلی، از یافته­ های پژوهش استنتاج می­شود که مشخصه­ های هندسی و آماری به‌دست‌آمده ازداده ­های لیدار نقش مهمی در شناسایی این دو گونه دارند.

کلیدواژه‌ها


عنوان مقاله [English]

Individual Carpinus betulus and Acer velutinum tree species delineation by geometrical and statistical characteristics derived from airborne LiDAR data

نویسندگان [English]

  • Remazan Ali Khorrami 1
  • Ali Asghar Darvishsefat 2
  • Masoud Tabari Kochaksaraei 3
  • Shaban Shataee Jouibary 4
1 Ph.D. Student, Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran
2 Prof., Faculty of Natural Resources, University of Tehran, Karaj, Iran
3 Prof., Faculty of Natural Resources, Tarbiat Modares University, Noor, Iran
4 Associate Prof., Faculty of Forestry, Gorgan University of Agriculture Sciences and Natural Resources, Gorgan, Iran
چکیده [English]

In this research, the possibility of application of LiDAR-derived characteristics has been studied for discrimination amongst common hornbeam (Carpinus betulus) and Persian maple (Acer velutinum) trees.  LiDAR data of individual sample trees were separated in laser point clouds using their measured center coordinates and crown diameter in the field. In district 1 of Shast-Kolate Education and Research Forest in Gorgan, 80 individual A. velutinum and C. betulus tree samples were selected. The trees were either located in dominant storey or were not overlaid by adjacent tree crowns. Tree heights were measured using Vertex 1V GPS device. Crown diameter was measured in four cardinal directions using Leica Disto lasermeter. Center coordinates of the sample trees were determined using both DGPS and distance/azimuth measurement by Total Station device. Different geometrical and statistical metrics of sample trees were extracted from LiDAR data. The results of discriminant analysis suggested the height standard deviation of laser points over 80% of tree height and crown slope as the selected metrics to differentiate the tree species (accuracy=80.3%). The mean of those two metrics showed larger values for hornbeam than maple. The selected LiDAR metrics were ascribed to represent the shape and height variation of returned crown laser points. It is therefore concluded that geometrical LiDAR-derived attributes could successfully helo by differentiating between the two tested tree species.

کلیدواژه‌ها [English]

  • Acer velutinum
  • Discriminant analysis
  • identification of individual tree species
  • LiDAR
  • Carpinus betulus
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