基于SfM方法的高密度点云数据生成及精度分析

地震地质 ›› 2015, Vol. 37 ›› Issue (2): 636-648.DOI: 10.3969/j.issn.0253-4967.2015.02.024

• 新技术应用 • 上一篇下一篇

基于SfM方法的高密度点云数据生成及精度分析

魏占玉¹, Arrowsmith Ramon², 何宏林¹, 高伟¹

1. 中国地震局地质研究所, 活动构造与火山重点实验室, 北京 100029;
2. 亚利桑那州立大学, 地球与空间探索学院, 美国, 菲尼克斯85287

收稿日期:2014-04-10 修回日期:2014-05-13 出版日期:2015-06-20 发布日期:2015-08-19
作者简介:魏占玉,男,1981年生,2010年于中国地震局地质研究所获构造地质学博士学位,研究方向为活动构造与构造地貌,电话:010-62009031,E-mail:weizhanyu@gmail.com。
基金资助:
中国地震重点监视防御区活动断层地震危险性评价项目(201308001)资助

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

WEI Zhan-yu¹, Arrowsmith Ramon², HE Hong-lin¹, GAO Wei¹

1. Key Laboratory of Active Tectonics and Volcano, Institute of Geology, China Earthquake Administration, Beijing 100029, China;
2. School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA

Received:2014-04-10 Revised:2014-05-13 Online:2015-06-20 Published:2015-08-19

摘要/Abstract

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

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

中图分类号:

P208

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.

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.

参考文献

Arrowsmith J R, Zielke O. 2009. Tectonic geomorphology of the San Andreas Fault zone, from high resolution topography: An example from the Cholame segment 【J】. Geomorphology, 113: 70—81.
Arko L, Steven M, Darren T. 2013. Mapping landslide displacements using Structure from Motion(SfM)and image correlation of multi-temporal UAV photography 【J】. Progress in Physical Geography, 38(1): 97—116.
Baltsavias E P, Favey E, Bauder A, et al. 2001. Digital surface modeling by airborne laser scanning and digital photogrammetry for glacier monitoring 【J】. The Photogrammetric Record, 17: 243—273.
Bird S, Hogan D, Schwab J. 2010. Photogrammetric monitoring of small streams under a riparian forest canopy 【J】. Earth Surface Processes and Landforms, 35: 952—970.
Crosby C J, Arrowsmith J R. 2007. Application of LiDAR data to constraining a late Pleistocene slip rate and vertical deformation of the Northern San Andreas Fault 【D】. Fort Ross to Mendocino, California.
Doleire-Oltmanns S, Marzol I, Peter K, et al. 2012. Unmanned Aerial Vehicle(UAV)for monitoring soil erosion in Morocco 【J】. Remote Sensing, 4: 3390—3416.
Fonstad M A, Dietrich J T, Courville B C, et al. 2013. Topographic structure from motion: A new development in photogrammetric measurement 【J】. Earth Surface Processes and Landforms, 38: 421—430.
Frankel K L, Dolan J F. 2007. Characterizing arid region alluvial fan surface roughness with airborne laser swath mapping digital topographic data 【J】. Journal of Geophysical Research, 112(F2): 20—25.
Harwin S, Lucieer A. 2012. Assessing the accuracy of georeferenced point clouds produced via multi-view stereopsis from unmanned aerial vehicle imagery 【J】. Remote Sensing, 4: 1573—1599.
Hilley G E, DeLong S, Prentice C, et al. 2010. Morphologic dating of fault scarps using airborne laser swath mapping(ALSM)data 【J】. Geophysical Research Letters, 37(4): 367—370.
Hu Y. 2003. Automated extraction of digital terrain models, roads and buildings using airborne LiDAR data 【D】. Department of Geomatics Engineering, the University of Calgary, Calgary, Alberta, Canada.
James M R, Robson S. 2012. Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application 【J】. Journal of Geophysical Research, 117. doi: 10.1029/2011JF002289.
Johnson K, Nissen E, Saripalli S, et al. 2014. Rapid mapping of ultrafine fault zone topography with structure from motion 【J】. Geosphere, 10(5): 969—986.
Kondo H, Toda S, Okamura K, et al. 2008. A fault scarp in an urban area identified by LiDAR survey: A case study on the Itoigawa-Shizuoka Tectonic Line, central Japan 【J】. Geomorphology, 11: 731—739.
Langridge R M. 2013. Developing sub 5-m LiDAR DEMs for forested sections of the Alpine and Hope faults, South Island, New Zealand: Implications for structural interpretations 【J】. Journal of Structural Geology, 64: 53—66.
Lin Z, Kaneda H, Mukoyama S, et al. 2013. Detection of subtle tectonic geomorphic features in densely forested mountains by very high-resolution airborne LiDAR survey 【J】. Geomorphology, 182: 104—115.
Lowe D. 2004. Distinctive image features from scale-invariant keypoints 【J】. International Journal of Computer, 60: 91—110.
Matthews N A. 2008. Aerial and close-range photogrammetric technology: Providing resource documentation, interpretation, and preservation 【D】. Technical Note, Bureau of Land Management, Denver, Colorado.
Meigs A. 2013. Active tectonics and the LiDAR revolution 【J】. Lithosphere, 5: 226—229.
Niethammer U, James M R, Rothmund S, et al. 2012. UAV-based remote sensing of the Super-Sauze landslide: Evaluation and results 【J】. Engineering Geology, 128: 2—11.
Oskin M E, Arrowsmith J R, Corona A H, et al. 2012. Near-field deformation from the El Mayor-Cucapah earthquake revealed by differential LiDAR 【J】. Science, 335: 702—705. doi: 10.1126/science.1213778.
Prentice C S, Mann P, Crone A J, et al. 2010. Seismic hazard of the Enriquillo-Plantain Garden Fault in Haiti inferred from palaeoseismology 【J】. Nature Geoscience, 3(11): 789—793.
Snavely N. 2008. Scene reconstruction and visualization from Internet photo collections 【D】. University of Washington, USA.
Verhoeven G. 2011. Taking computer vision aloft: Archaeological three-dimensional reconstructions from aerial photographs with PhotoScan 【J】. Archaeological Prospection, 18: 67—73.
Westoby M J, Brasington J, Glasser N F, et al. 2012. "Structure-from-Motion" photogrammetry: A low-cost, effective tool for geoscience applications 【J】. Geomorphology, 179: 300—314.
Zielke O, Arrowsmith J R, Grant-Ludwig L B, et al. 2012. High resolution topography-derived offset along the 1857 Fort Tejon earthquake rupture trace, San Andreas Fault 【J】. Bulletin of the Seismological Society of America, 102(3): 1135—1154.
Zielke O, Arrowsmith J R, Ludwig L G, et al. 2010. Slip in the 1857 and earlier large 747 earthquakes along the Carrizo Plain, San Andreas Fault 【J】. Science, 327: 1119—1122.

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