UAS Photogrammetry for Precise Digital Elevation Models of Complex Topography: A Strategy Guide

M. Elias, S. Isfort, A. Eltner, Hans-Gerd Maas
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Abstract

Abstract. The presented research investigates different strategies to acquire high-precision digital elevation models (DEMs) of complex and inaccessible terrain using Structure-from-Motion and Multi-View Stereo applied to data of an unoccupied aerial system (UAS) equipped with real-time-kinematic (RTK)-GNSS. The survey scenarios are taken from real-life situations and thus, in comparison to many previous studies, provide information on how to operate under challenging conditions in difficult terrain. Among others, the study examines the influence of different flight configurations (parallel axes and cross-grid), flight altitudes (relative to ellipsoid or terrain) and associated variations in ground sampling distance, image orientations (nadir and oblique), advanced camera self-calibration techniques and georeferencing strategies in image block processing (direct and integrated) on the overall accuracy of the resulting DEMs. Random and systematic errors, including spatial patterns such as doming and bowling, are quantified using check points and differences between DEM calculations and independently acquired surface data from laser scans. This comprehensive analysis contributes valuable insights for UAS-based analysis of complex terrain with improved accuracy in DEM generation and subsequent applications like change detection.
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无人机系统摄影测量用于复杂地形的精确数字高程模型:战略指南
摘要所提交的研究调查了在复杂和难以进入的地形中使用结构-运动和多视图立体获取高精度数字高程模型(DEMs)的不同策略,这些策略应用于配备实时运动学(RTK)-全球导航卫星系统(GNSS)的无人驾驶航空系统(UAS)的数据。调查场景取自现实生活中的情况,因此,与之前的许多研究相比,它提供了如何在困难地形的挑战条件下进行操作的信息。除其他外,该研究还审查了不同飞行配置(平行轴和交叉网格)、飞行高度(相对于椭球面或地形)以及地面采样距离的相关变化、图像方向(正中线和斜线)、先进的相机自校准技术和图像块处理(直接和综合)中的地理参照策略对所生成的 DEM 整体精度的影响。随机误差和系统误差,包括穹顶和弓形等空间模式,均通过检查点和 DEM 计算结果与独立获取的激光扫描表面数据之间的差异进行量化。这项综合分析为基于无人机系统的复杂地形分析提供了宝贵的见解,提高了 DEM 生成和后续应用(如变化检测)的精度。
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