|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|81353||158311||2016||16 صفحه PDF||سفارش دهید||دانلود رایگان|
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• A coarse-to-fine registration of TLS scans in forest measurements is proposed.
• Only a terrestrial laser scanner and a reflector are needed in the registration.
• DBH derived from registered TLS scans compared well with field measurements.
• Our registration method offers high accuracy and improves scanning efficiency.
Terrestrial Laser Scanning (TLS) plays an increasing role in acquiring 3-dimensional forest structure information. Obstructions and stem density often need multiple scans, making the registration procedure vitally important. Since natural features are difficult to find, traditional registration methods often use artificial reflectors as tie points in forest areas. However, the placement of reflectors reduces the scanning efficiency, especially in forest stands with severe obstructions. In this paper, an efficient registration method using a coarse-to-fine strategy is proposed to overcome the challenge of placing artificial targets so as to improve the scanning efficiency. The coarse registration step utilizes the backsighting orientation approach to form a coarse alignment. Unlike other backsighting research used in urban areas, we solely rely on a TLS system with an internal compass and a built-in inclination sensor. In the fine registration step, stem center locations are calculated in each individual scan. Then, corresponding stem center pairs are found between adjacent scans with the help of the coarse registration results. They are used as tie points to perform a rigid-body transformation for the fine registration. The proposed coarse-to-fine registration method was tested at two forest sites in northeast China. The registration accuracy is approximately 1.5 cm. Results also show that the diameters at breast height (DBHs) extracted from registered TLS data sets are highly correlated with field-measured DBHs (coefficient of determination (R2): 0.92, root mean square error (RMSE): 0.27 cm). Considering both the scanning efficiency and accuracy, the proposed coarse-to-fine registration method provides a feasible and effective way for forest measurements.
Journal: Agricultural and Forest Meteorology - Volume 225, 15 September 2016, Pages 8–23