ACCURACY ANALYSIS OF TERRAIN POINT CLOUD ACQUIRED BY "STRUCTURE FROM MOTION" USING AERIAL PHOTOS

doi:10.3969/j.issn.0253-4967.2015.02.024

Abstract

Abstract:

The need to acquire high-quality digital topographic data is evident throughout geoscience research. The use of these data elevates the research level of geosciences. Airborne and terrestrial light detection and ranging(LiDAR)are currently the most prevalent techniques for generating such data, but the high costs and complex post processing of these laser-based techniques restrict their availability. In the past few years, a new stereoscopic photogrammetry mapping method called Structure from Motion(SfM)has been applied in geoscience, in which the 3D digital topography is reconstructed using feature matching algorithms from overlapping photographs of multiple viewpoints. SfM only needs a series of overlapping images with no special requirements about the camera positions, orientations and lens parameters, making it possible to use images collected from an affordable SfM platform to rapidly generate high-quality 3D digital topography. This paper summarizes the basic principles and the SfM workflow, and shows that SfM is a low-cost, effective tool for geoscience applications compared to LiDAR. We use a series of digital aerial photos with~70% overlap collected at one-thousand-meter height to produce a textured(color)SfM point cloud with point density of 25.5/m². Such a high density point cloud allows us to generate a DEM with grid size of 0.2m. Compared with LiDAR point cloud, statistical analysis shows that 58.3% of LiDAR points deviate vertically from the closed SfM point by <0.1m and 88.3% by <0.2m. There is different SfM accuracy in different landforms. The SfM accuracy is higher in low dips and subdued landforms than in steep landforms. In consideration of relative vertical error of 0.12m in LiDAR data, SfM has a higher measuring accuracy compared with LiDAR.

Key words: Structure from Motion(SfM), LiDAR DEM

摘要：

地形数据的质量(精度和分辨率)影响着地球科学的研究水平。LiDAR测量是目前获取高分辨率地形数据的有效技术方法之一, 但是其高昂的测量成本和相对复杂的后期数据处理限制了LiDAR技术的大众化应用。近年来, 一种被称为SfM(Structure from Motion)的适合大众化使用的新的高精度3维地形数据获取技术开始引起人们的注意。这种新型数字摄影测量技术可以利用高效的图像特征匹配算法从多视角照片中提取重叠区域的3维地形数据。由于SfM技术仅需要目标物体的照片, 而且对相机拍摄位置、图像尺度及拍摄焦距没有要求, 因此利用简单测量平台采集地面照片就可以获取高质量的3维地形数据。与LiDAR技术相比, 大大降低了获取高精度数据的成本, 使得高精度3维地形数据的使用大众化。文中介绍了SfM技术的基本原理和流程, 展示了SfM技术获取高精度3维地形数据的简单而有效的特性, 特别适合于植被稀少的区域。文中利用近千米高空拍摄的、具有约70%重叠度的一套随LiDAR飞行采集的数字航空照片生成具有真彩色的高密度SfM点云数据, 点密度高达25.5个/m², 可生成分辨率0.2m的DEM(数字高程模型)。对比相同区域的LiDAR点云数据, 统计分析表明58.3%的LiDAR数据与SfM数据的垂直偏差<0.1m, 88.3%的LiDAR数据的垂直偏差<0.2m; 而且发现不同地貌的SfM数据精度存在差异, 平缓地形的SfM数据精度高于陡峭地形的SfM数据精度。文中还介绍了以氦气球作为拍摄平台的SfM测量系统, 可以快捷地获取高精度的3D地形数据和正射影像, 比目前常用的差分GPS测量具有更高的效率和数据精度。

关键词: Structure from Motion(SfM), LiDAR DEM

CLC Number:

P208

WEI Zhan-yu, Arrowsmith Ramon, HE Hong-lin, GAO Wei. ACCURACY ANALYSIS OF TERRAIN POINT CLOUD ACQUIRED BY "STRUCTURE FROM MOTION" USING AERIAL PHOTOS[J]. SEISMOLOGY AND GEOLOGY, 2015, 37(2): 636-648.

魏占玉, Arrowsmith Ramon, 何宏林, 高伟. 基于SfM方法的高密度点云数据生成及精度分析[J]. 地震地质, 2015, 37(2): 636-648.

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