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Tree Stem and Height Measurements using Terrestrial Laser Scanning and the RANSAC Algorithm

机译:使用地面激光扫描和RANSAC算法测量树木的茎和高度

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Terrestrial laser scanning is a promising technique for automatic measurements of tree stems. The objectives of the study were (1) to develop and validate a new method for the detection, classification and measurements of tree stems and canopies using the Hough transformation and the RANSAC algorithm and (2) assess the influence of distance to the scanner on the measurement accuracy. Tree detection and stem diameter estimates were validated for 16 circular plots with 20 m radius. The three dominating tree species were Norway spruce (Picea abies L. Karst.), Scots pine (Pinus sylvestris L.) and birch (Betula spp.). The proportion of detected trees decreased as the distance to the scanner increased and followed the trend of decreasing visible area. Within 10 m from the scanner, the proportion of detected trees was 87% on average for the plots and the diameter at breast height was estimated with a relative root-mean-square-error (RMSE) of 14%. The most accurate diameter measurements were obtained for pine, which had a RMSE of 7% for all the full 20 m radius plots. The RANSAC algorithm reduced noise and made it possible to obtain reliable estimates.
机译:陆地激光扫描是一种用于自动测量树干的有前途的技术。这项研究的目的是(1)开发和验证一种使用霍夫变换和RANSAC算法检测,分类和测量树茎和树冠的新方法,以及(2)评估距扫描仪的距离对树冠和树冠的影响。测量精度。对半径为20 m的16个圆形样地的树木检测和茎径估计进行了验证。三种主要的树种是挪威云杉(Picea abies L. Karst。),苏格兰松树(Pinus sylvestris L.)和桦木(Betula spp。)。随着到扫描仪的距离的增加,被检测树木的比例降低,并且遵循可见面积减小的趋势。在距扫描仪10 m的范围内,该地块的树木平均检测率为87%,估计的乳房高度直径为14%的相对均方根误差(RMSE)。对于松树,获得了最准确的直径测量值,对于所有20 m半径图,其RMSE为7%。 RANSAC算法减少了噪声,并有可能获得可靠的估计。

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