基于机载激光雷达点云的雪道坡度提取算法

Slope extraction algorithm of ski tracks based on airborne LIDAR point cloud

  • 摘要: 滑雪场的雪道坡度信息不仅是雪场规划和建设所需的必要内容,也是滑雪运动员提高成绩、减少运动损伤的重要数据。传统的手动测量方式费时费力,且雪场的低温环境不利于测量人员长时间作业。为了解决滑雪场的雪道坡度计算问题,提出了一种基于激光雷达点云的雪道坡度自动提取算法。使用投影高程差滤波、聚类分割等算法对雪场点云进行预处理,获取雪道边缘特征数据。提出了一种自适应阈值的拟合算法,用于雪道中线的提取,该算法可根据点云数量信息及坐标信息,自动选择阈值拟合雪道中线,消除了实际应用中部分点云数据稀疏或缺失对中线拟合带来的不利影响。数据处理结果表明,该方法计算所得坡度值与多次手动测量平均值之间的相对误差为2.2%。这一方法对激光雷达在雪场目标上的应用、雪场测绘中雪道坡度计算等具有参考意义。

     

    Abstract: The slope information of ski resort is not only a necessary content for planning and construction of ski resort, but also an important data support for skiers to improve performance and reduce sports injuries. The traditional manual measurement method is time-consuming and the low temperature environment of the ski resort is not conducive to the long-time operation of the surveyors. In order to solve the problem of calculating the slope of ski tracks, an automatic slope extraction algorithm of ski tracks based on LIDAR point cloud was proposed. The projection difference of elevation filtering, clustering segmentation and other algorithms were used to preprocess the ski resort point cloud and obtain the feature data of ski tracks edge. An adaptive threshold fitting algorithm was proposed for the extraction of the center line of ski tracks. This algorithm could automatically select the threshold to fit the center line of ski tracks according to the point cloud quantity information and coordinate information, which eliminated the negative effect of the data sparse or missing of point cloud on the center line fitting. The data processing results show that the relative error between the slope value calculated by this method and the average value of multiple manual measurements is 2.2%. This method is of reference significance to the application of LIDAR in the target of ski resorts and to the calculation of slope of snow tracks in the mapping of ski resorts.

     

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