地震地质 ›› 2014, Vol. 36 ›› Issue (3): 794-813.DOI: 10.3969/j.issn.0253-4967.2014.03.019

• 空间对地观测与地壳形变 • 上一篇    下一篇

基于LiDAR数据开展活动断层填图的实验研究——以新疆独山子背斜-逆冲断裂带为例

魏占玉, 何宏林, 高伟, 徐锡伟, 甘卫军, 卫蕾华   

  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
  • 收稿日期:2014-03-10 修回日期:2014-07-17 出版日期:2014-09-30 发布日期:2014-09-30
  • 作者简介:魏占玉|男|1981年生|2010年在中国地震局地质研究所获得构造地质学博士学位|现主要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:

    我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

EXPERIMENTAL STUDY ON GEOLOGIC MAPPING OF ACTIVE TECTONICS BASED ON LIDAR DATA—A CASE OF DUSHANZI ANTICLINE-REVERSE FAULT ZONE IN XINJIANG

WEI Zhan-yu, HE Hong-lin, GAO Wei, XU Xi-wei, GAN Wei-jun, WEI Lei-hua   

  1. Key Laboratory of Active Tectonics and Volcano, Institute of Geology, China Earthquake Administration, Beijing 100029, China
  • Received:2014-03-10 Revised:2014-07-17 Online:2014-09-30 Published:2014-09-30

摘要:

机载LiDAR技术为描绘活动构造相关构造地貌和最新的地表形变提供更精确的基础数据。如何将LiDAR新技术、新数据应用于活动构造填图和活动断层地震危险性评价等方面,是今后活动构造研究领域的一个重要的发展方向。文中以新疆天山北麓的独山子背斜-逆冲断裂带为试验区,开展了基于LiDAR数据的活动构造填图实验研究。首先,采用机载LiDAR技术进行数据采集,获得点云密度为6.6个/m2、平均点间距为0.39m的LiDAR原始数据;其次,利用试验区内12个测量精度可达mm级的GPS静态测量点评估LiDAR的相对垂直精度为0.12m、均方差值为0.078m;最后,对密度为6.4个/m2的地面点云数据进行DEM最佳分辨率评估,利用反距离权重算法获得0.5m分辨率的数据高程模型(DEM)。该分辨率的DEM数据足以完成独山子背斜-逆冲断裂带的精细构造地貌特征的确定以及高精度的空间解译。文中仅使用DEM可视化工具从不同虚拟的视角、不同色度或其他处理方式来识别微构造地貌、划分地貌面和确定断层位置等,宏观上获得与前人通过航片解译和野外调查一致的断裂分布特征,微观上较前者具有更高的精细程度。此外,数据采集、数据质量检验、数据处理及数据应用等技术和方法适用于其他能够获得LiDAR地形数据的活动断裂研究工作。

关键词: LiDAR, 独山子逆冲-背斜带, 活动断层填图

Abstract:

Airborne LiDAR (Light Detection And Ranging) provides a more advanced technique and more accurate basic data to describe geomorphological features and the latest surface deformation associated with active tectonics. How to apply this new technique and dataset to mapping of active fault and seismic hazard assessment is an important trend in the field of active tectonics. Taking the Dushanzi anticline-reverse fault zone in Xinjiang as test area, we made an experimental study on geologic mapping of active tectonics based on the LiDAR data. Firstly, we collected raw data using the airborne LiDAR technique, and obtained a raw point-cloud with a point density of 6.6 points/m2 and an average space of 0.39m between any two points. Secondly, using twelve ground control points(GCP)which is acquired by static GPS measurement with accuracy up to millimeter, we evaluated the vertical error of the ground point-cloud data with density of 6.4 points/m2, and the result shows a vertical error of 0.12m, mean square value 0.078m. Finally, using the inverse distance weighting algorithm, we obtained the digital elevation model(DEM)of 0.5m-resolution. The resolution of the DEM is high enough to describe and analyze spatially the fine feature of tectonic landform of the Dushanzi anticline-reverse fault zone. In this paper, we identify the fine tectonic landforms using merely the DEM visualization tools based on different virtual perspectives, different shades or different treatment methods. The active tectonics and their distribution identified based on the high resolution DEM derived from LiDAR are not only consistent with previous results identified from air-interpretation and field investigation, but also finer and more precise than the latter. In addition, these methods of data acquisition, quality inspection and data processing introduced in this paper are also applied to other active fault researches in which LiDAR data have been acquired.

Key words: LiDAR, Dushanzi anticline-reverse fault zone, mapping of active fault

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