کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6458214 | 158307 | 2016 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Determining woody-to-total area ratio using terrestrial laser scanning (TLS)
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
علم هواشناسی
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چکیده انگلیسی
Accurately determining woody-to-total area ratio (WTA) is a key step to indirectly retrieve leaf area index (LAI) from terrestrial laser scanning (TLS) data. In this work, we first collected both individual tree and forest plot point cloud data (PCD) from broadleaf and coniferous tree species and leaf characteristics using both side-lateral and full field-of-view TLS field setups with scan distances between 2.5 to 28Â m. Using a local geometrical feature-based algorithm, the generated PCD were automatically classified into three different categories including photosynthetic canopy components, non-photosynthetic canopy components, and bare earth. To convert each classified point into a surface area, we then developed and validated a novel approach that considers sampling space, laser incidence angle, and leaf orientation information. The estimated surface areas from this approach showed strong agreements with validation datasets for single leaf (91.44%), photosynthetic (95.64%), and non-photosynthetic canopy components (89.60%) of an artificial tree and stems of an old-growth coniferous tree (93.53%), two individual broadleaf trees (98.31% and 97.46%) and a broadleaf forest plot (90.26%). By doing this, we computed the parameter WTA for an individual artificial tree (10.90%), an old-growth coniferous tree (29.97%), two individual broadleaf tree (14.83% and 4.27%) and four natural forest stands ranging from 7.74%-15.57%, respectively. The proposed method can effectively improve the accuracy of retrieving true LAI by removing the effects of woody components and converting each point into a surface area.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Agricultural and Forest Meteorology - Volumes 228â229, 15 November 2016, Pages 217-228
Journal: Agricultural and Forest Meteorology - Volumes 228â229, 15 November 2016, Pages 217-228
نویسندگان
Lixia Ma, Guang Zheng, Jan U.H. Eitel, Troy S. Magney, L. Monika Moskal,