This paper introduces five new density and accuracy metrics for aerial point clouds that address the complexity and objectives of modern, dense laser scans of urban scenes. The five metrics describe (1) vertical surface density (points per area on vertical surfaces); (2) vertical density as a function of horizontal density; (3) vertical surface accuracy; and a decomposition of error into (4) within-pass and (5) cross-pass components. Specifically considered is vertical surface coverage and the practice of overlapping flight passes to reduce the occlusions and achieve the vertical density needed for twenty-first-century use cases (e.g. curb and window detection). The application of these metrics to a quartet of recent urban flyovers demonstrates their relevance by establishing (1) the efficacy of considering sensor position and wall height when predicting point density on vertical surfaces; (2) that cross-pass registration accounts for a disproportionate amount of the vertical surface error (but not horizontal) and provides a meaningful parameter to compare high-density, urban point clouds; and (3) that compared to horizontal density and accuracy, the vertical counterparts are disproportionately impacted (positively for density and negatively for accuracy) by modern, optimized flight missions.

本文介绍了针对空中点云的五个新的密度和精度指标，这些指标解决了现代密集的城市场景激光扫描的复杂性和目标。这五个指标描述（1）垂直表面密度（垂直表面上每个区域的点数）；（2）垂直密度与水平密度的函数关系；（3）垂直面精度；并将误差分解为（4）通道内和（5）通道内组件。特别考虑的是垂直表面覆盖率和重叠飞行通行证的做法，以减少遮挡并达到二十一世纪使用情况（例如路缘和窗户检测）所需的垂直密度。将这些指标应用到四方最近的城市高架桥中，可以证明它们的相关性：（1）在预测垂直表面上的点密度时考虑传感器位置和壁高的功效；（2）交叉通过配准解决了垂直表面误差（但不是水平）的不成比例的问题，并提供了有意义的参数来比较高密度的城市点云；（3）与水平密度和精度相比，现代优化的飞行任务对垂直对应物的影响不成比例（对密度为正，对精度为负）。（2）交叉通过配准解决了垂直表面误差（但不是水平）的不成比例的问题，并提供了有意义的参数来比较高密度的城市点云；（3）与水平密度和精度相比，现代优化的飞行任务对垂直对应物的影响不成比例（对密度为正，对精度为负）。（2）交叉通过配准解决了垂直表面误差（但不是水平）的不成比例的问题，并提供了有意义的参数来比较高密度的城市点云；（3）与水平密度和精度相比，现代优化的飞行任务对垂直对应物的影响不成比例（对密度为正，对精度为负）。