ABSTRACT The increasing availability of highly detailed and accurate three-dimensional (3D) geospatial data are currently pushing the 3D change detection analysis towards a new 3D mapping frame. In this paper, medium-term changes (8 years) at a coastal rocky cliff are quantified using and comparing 2.5D and 3D methods to estimate the volume of rockfalls and three datasets: one Terrestrial Laser Scanner (TLS) acquired in 2010 and two coincident Unmanned Aerial Vehicles (UAV: multirotor and fixed-wing) datasets acquired in 2018. Advantages and limitations of these techniques, platforms and methods are discussed and the role of Ground Control Points (GCPs) distribution was analysed. Maps of 3D changes were produced by means of the Multiscale-Model-to-Model Cloud-Comparison algorithm (M3C2). The volume of the eroded-deposited material was estimated using two 2.5D and one 3D approaches: 1) rasterizing M3C2 distances using a conventional top-view perspective, 2) rasterizing the M3C2 distances rotated and orientated with the z vector normal and, 3) for the largest rockfalls, the volume was estimated using the Poisson Surface Reconstruction (PSR) algorithm (3D). The 3D models produced using both UAV platforms showed cm-level accuracies with Root Mean Square Error (RMSE) of 0.02 and 0.03 m for the multirotor and the fixed-wing, respectively, and faithfully represented cliff geometry. GCP configuration analysis showed that, at least, two stripes of GCPs evenly distributed at different heights are necessary, but three are recommended. The spatial pattern of change between the TLS and the two UAVs datasets was similar. The quantification of the volume of the eroded-accumulated material (using the M3C2 distances and the two UAV datasets) resulted in significant differences as the fixed-wing underestimated the values calculated using the multirotor dataset. The 2.5D strategies used to quantify the volume of change underestimated the eroded volume of the largest rockfalls (compared to the PSR 3D method), which provided the most accurate volume estimates.

中文翻译：

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使用两个无人机平台（多旋翼和固定翼）和三种不同的方法来测量海岸悬崖以估计体积变化

摘要 高度详细和准确的 3D (3D) 地理空间数据的可用性日益增加，目前正在将 3D 变化检测分析推向新的 3D 映射框架。在本文中，使用和比较 2.5D 和 3D 方法来估计落石量和三个数据集：一个在 2010 年获得的陆地激光扫描仪 (TLS) 和两个重合的2018 年获得的无人机（UAV：多旋翼和固定翼）数据集。讨论了这些技术、平台和方法的优点和局限性，并分析了地面控制点 (GCP) 分布的作用。3D 变化图是通过多尺度模型到模型云比较算法 (M3C2) 生成的。侵蚀沉积材料的体积是使用两种 2.5D 和一种 3D 方法估计的：1) 使用传统的顶视图对 M3C2 距离进行光栅化，2) 使用 z 向量法线旋转和定向的 M3C2 距离光栅化，以及，3)对于最大的落石，体积是使用泊松表面重建 (PSR) 算法 (3D) 估算的。使用两种无人机平台生成的 3D 模型显示出厘米级精度，多旋翼和固定翼的均方根误差 (RMSE) 分别为 0.02 和 0.03 m，并忠实地代表了悬崖几何形状。GCP 配置分析表明，至少需要在不同高度均匀分布的两条 GCP 条带，但建议使用 3 条。TLS 和两个无人机数据集之间的空间变化模式相似。侵蚀累积材料体积的量化（使用 M3C2 距离和两个无人机数据集）导致显着差异，因为固定翼低估了使用多旋翼数据集计算的值。用于量化变化量的 2.5D 策略低估了最大落石的侵蚀量（与 PSR 3D 方法相比），后者提供了最准确的体积估计。