SEISMOLOGY AND GEOLOGY ›› 2022, Vol. 44 ›› Issue (2): 524-540.DOI: 10.3969/j.issn.0253-4967.2022.02.015

• Focus: Mechanical understanding of the surface ruptures of the 2021 Madoi earthquake • Previous Articles     Next Articles

RAPID EXTRACTION OF FEATURES AND INDOOR RECON-STRUCTION OF 3D STRUCTURES OF MADOI MW7.4 EARTHQUAKE SURFACE RUPTURES BASED ON PHOTOGRAMMETRY METHOD

WANG Wen-xin1)(), SHAO Yan-xiu1),*(), YAO Wen-qian1), LIU-ZENG Jing1,2), HAN Long-fei1), LIU Xiao-li3), GAO Yun-peng1), WANG Zi-jun1), QIN Ke-xin1), TU Hong-wei4)   

  1. 1) Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
    2) State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing 100029, China
    3) Key Laboratory of Earthquake Geodesy, Institute of Seismology, China Earthquake Administration, Wuhan 430071, China
    4) Qinghai Earthquake Agency, Xining 810001, China
  • Received:2022-01-25 Revised:2022-03-19 Online:2022-04-20 Published:2022-06-14
  • Contact: SHAO Yan-xiu

基于摄影测量技术对玛多MW7.4地震地表破裂特征的快速提取及三维结构的室内重建

王文鑫1)(), 邵延秀1),*(), 姚文倩1), 刘静1,2), 韩龙飞1), 刘小利3), 高云鹏1), 王子君1), 秦可心1), 屠泓为4)   

  1. 1)天津大学, 地球系统科学学院, 表层地球系统科学研究院, 天津 300072
    2)中国地震局地质研究所, 地震动力学国家重点实验室, 北京 100029
    3)中国地震局地震研究所, 地震大地测量重点实验室, 武汉 430071
    4)青海省地震局, 西宁 810001
  • 通讯作者: 邵延秀
  • 作者简介:王文鑫, 男, 1995年生, 现为天津大学地球系统科学学院环境科学专业在读博士研究生, 主要从事地表侵蚀与地貌演化方面的研究, E-mail: wenxinwwx_1995@tju.edu.cn
  • 基金资助:
    国家自然科学基金(U1839203);国家自然科学基金(42011540385);地震动力学国家重点实验室开放基金(LED2020B03);青海省科技计划项目(2020-ZJ-752)

Abstract:

Exact characteristics of surface rupture zone are essential for exploring the mechanism of large earthquakes. Although the traditional field surface rupture investigation methods can obtain high-precision geomorphic data in a local area, it is difficult to rapidly get an extensive range of high-precision topographic and geomorphic data of the entire fault due to its limited measurement range and low efficiency. In addition, manual measurement is of tremendous workload, high cost, time-consuming and laborious, and the subjective differences in the judgment standards during the manual operation process may also cause the measurement results to be inconsistent with the actual terrain characteristics. In recent years, the development of photogrammetry technology has provided another more effective technical means for the rapid acquisition of high-precision topographic and geomorphic data, which has dramatically changed the way of geological investigation, improved the efficiency of fieldwork. At the same time, it also makes it a reality to reproduce the 3D tectonic features of field tectonic deformation indoors.
Structure from Motion(SfM)multi-view mobile photogrammetry technology is widely concerned for its convenience, fast and low-cost acquisition of high-resolution 3D topographic data in a working area of tens-kilometers scale. The emergence of this method has greatly improved the automation degree of photogrammetry. The technology obtains image sets by motion cameras, uses a feature matching algorithm to extract homonym features from multiple images(at least three images), determines the relative positional relationship of cameras during photography, and continuously optimizes by the nonlinear least square algorithm. Finally, the pose of cameras is automatically solved, and 3D scene structure is reconstructed. The technology can restore the original 3D appearance of the object in the computer by a set of digital images with a certain degree of overlap. In the applications of terrain mapping, this technology only needs to combine a small number of ground control points(GCPs)to quickly establish digital orthophoto maps(DOMs)and digital elevation models(DEMs)with high-precision. In this way, low altitude remote sensing platforms such as small and medium-sized UAVs have provided a foundation for SfM photogrammetry technology.
After the Madoi MW7.4 earthquake occurred on May 22, 2021, our research team rushed to the site as soon as possible and conducted the rapid photogrammetry of the entire coseismic surface rupture zone in a short period with the use of the CW-15 VTOL fixed-wing UAV. We completed the collection of topographic data in an area with ~180km length and ~256km2 area and collected 34302 aerial photographs. We used Agisoft PhotoScan TM software to process the images and generate DOMs quickly. The DOM resolution of the entire surface rupture was 2~7cm/pix, most of which were 3~5cm/pix. Then we used GIS software to vectorize the surface rupture. The centimeter-scale high-resolution DOMs could clearly display the coseismic surface rupture’s spatial distribution and the relative width. On this basis, the surface rupture could be accurately interpreted, and related parameters such as coseismic offsets could be extracted. In this study, the horizontal offsets measured by orthophoto images were basically consistent with the field measurement results, which proved the authenticity and reliability of the data obtained by the UAV photogrammetry method.
In order to obtain more detailed surface rupture vertical offset data, we used DJI Phantom 4 Pro V2.0 UAV to collect terrain information of several areas with the most significant rupture deformation. The DEM resolution obtained could reach centimeter-scale, and the accuracy was greatly improved. The high-resolution topographic and geomorphic data obtained by this method could accurately identify tiny fault features, clearly display sub-meter-level vertical offset features, significantly improve the accuracy of offset measurement, and achieve high-resolution 3D reconstruction of fault geomorphic.
In addition, we selected typical surface ruptures in the field, such as compressional stepovers, tensional cracks, and pressure ridges, and collected their 3D structural features using the iPhone 12 Pro LiDAR scanner. The 3D Scanner application was used to optimize the image, completely restore the “real object” in 3D to realize the indoor reconstruction of the 3D structure of surface ruptures and pressure ridges. The augmented reality(AR)imaging models could truly reflect the characteristics and details of surface ruptures, forming the same effect as field observations. This technology, which creates 3D models of close-range environments without any prior preparation, provides a novel, economical, and time-saving method to rapidly scan morphological features of small and medium-sized landforms(from centimeters to hundreds of meters)at high spatial resolution. This is the fastest and most convenient way to collect 3D models in field geological investigation without using external equipment, which provides a new idea for future geological teaching and scientific research.
Although photogrammetry technology still has some limitations, such as the short flight time of the flight platform, being easily affected by factors such as weather and altitude, and unsatisfactory aerial photography in densely vegetated areas, it is believed that these problems will be solved with the advancement of technology. Once solved, photogrammetry will become an essential technical means in quantitative and refined research on active tectonics.

Key words: Madoi MW7.4 earthquake, surface fracture, photogrammetry method, UAV, augmented reality

摘要:

掌握精确地震的地表破裂带特征是探讨大地震破裂特征和发震机理的重要基础。摄影测量技术为快速获取高精度、 高分辨率地表破裂带的空间展布提供了有力支撑。文中以玛多 MW7.4 地震为例, 详细介绍了摄影测量技术在震后快速准确地进行地表破裂解译及相关特征参数提取中的应用。通过无人机摄影测量技术, 在较短时间内获得了地震全段地表破裂的数字正射影像以及多个形变复杂区域厘米级分辨率的数字高程模型, 可满足震后快速获取同震地表破裂带特征的需要。对正射影像测量的地表破裂水平位错结果与野外实地测量结果进行对比, 可证明无人机摄影测量技术所得数据的真实性和可靠性。利用移动智能设备搭载的LiDAR传感器, 结合增强现实技术(Augmented reality, AR), 实现了如挤压鼓包等复杂地表破裂的室内重现, AR成像模型与实景高度融合, 为地质教学及科研工作提供了一种新的方法和思路。研究结果显示, 摄影测量技术在活动构造定量化、 精细化研究中具有巨大的应用潜力。

关键词: 玛多MW7.4 地震, 地表破裂, 摄影测量技术, 无人机, 增强现实技术

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