Structural Analysis of the Hero Range in the Qaidam Basin, Northwestern China, Using Integrated UAV, Terrestrial LiDAR, Landsat 8, and 3-D Seismic Data

被引:10
作者
Chen, Ninghua [1 ]
Ni, Nina [1 ]
Kapp, Paul [2 ]
Chen, Jianyu [3 ]
Xiao, Ancheng [1 ]
Li, Hongge [4 ]
机构
[1] Zhejiang Univ, Dept Earth Sci, Hangzhou 310027, Zhejiang, Peoples R China
[2] Univ Arizona, Dept Geosci, Tucson, AZ 85721 USA
[3] State Ocean Adm, State Key Lab Satellite Ocean Environm Dynam, Inst Oceanog 2, Hangzhou 310012, Zhejiang, Peoples R China
[4] China Natl Petr Corp, Inst Bur Geophys Prospecting, Zhuozhou 072751, Peoples R China
基金
中国国家自然科学基金;
关键词
Landsat 8 (L8); structural analysis; terrestrial light detection and ranging (LiDAR); unmanned aerial vehicle (UAV); Qaidam Basin (QB); TIBETAN PLATEAU; GEOMORPHIC INDEXES; GEOLOGIC MAPS; NW CHINA; EVOLUTION; SEDIMENTATION; MULTISCALE; AIRBORNE; REGIONS; EROSION;
D O I
10.1109/JSTARS.2015.2440171
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Quantitative structural analysis is a useful approach for studying geologic structures. It is particularly important in remote and complex fold-thrust belts where outcrop data and high-quality seismic reflection images are challenging to obtain. In this study, we integrated terrestrial light detection and ranging (LiDAR), unmanned aerial vehicle (UAV), and Landsat 8 (L8) data to extract high-resolution topographic and surface geologic information and constrain interpretations of three-dimensional (3-D) seismic reflection data in the Hero Range of the Qaidam Basin (QB) in northwestern China. UAV images were used to obtain a digital elevation model (DEM) and to measure the orientation of sedimentary bedding. Terrestrial LiDAR data were used to generate high-resolution digital outcrops and to evaluate the accuracy of the UAV-based DEM. L8 images were used to distinguish different stratigraphic units. The random sample consensus (RANSAC) algorithm was adopted to ascertain the best-fit plane of bedding. The results show that UAV images can be used to construct a DEM with <1m resolution and orthophotos with 0.15-m resolution. Collectively, these data improve the ability to identify and measure small exposures of bedding surfaces. The RANSAC algorithm improves the accuracy of measuring bedding orientations by removing erroneous selection points and facilitating the recognition of second-order variations in bedding orientation. The integrated analysis of remotely sensed and 3-D seismic data indicates that, of the three anticlines within the Hero Range, two are fault-propagation folds (the Shizigou and Youshashan anticlines) and one is associated with a pop-up structure (Ganchaigou anticline).
引用
收藏
页码:4581 / 4591
页数:11
相关论文
共 51 条
[1]   Remote surface mapping using orthophotos and geologic maps draped over digital elevation models: Application the Sheep Mountain anticline, Wyoming [J].
Banerjee, S ;
Mitra, S .
AAPG BULLETIN, 2004, 88 (09) :1227-1237
[2]   High-resolution spatial rupture pattern of a multiphase flower structure, Rex Hills, Nevada: New insights on scarp evolution in complex topography based on 3-D laser scanning [J].
Baran, Ramona ;
Guest, Bernard ;
Friedrich, Anke M. .
GEOLOGICAL SOCIETY OF AMERICA BULLETIN, 2010, 122 (5-6) :897-914
[3]   Digital outcrop models: Applications of terrestrial scanning lidar technology in stratigraphic modeling [J].
Bellian, JA ;
Kerans, C ;
Jennette, DC .
JOURNAL OF SEDIMENTARY RESEARCH, 2005, 75 (02) :166-176
[4]   GIS as an aid to visualizing and mapping geology and rock properties in regions of subtle topography [J].
Belt, K ;
Paxton, ST .
GEOLOGICAL SOCIETY OF AMERICA BULLETIN, 2005, 117 (1-2) :149-160
[5]   Ground-based and UAV-Based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology [J].
Bemis, Sean P. ;
Micklethwaite, Steven ;
Turner, Darren ;
James, Mike R. ;
Akciz, Sinan ;
Thiele, Sam T. ;
Bangash, Hasnain Ali .
JOURNAL OF STRUCTURAL GEOLOGY, 2014, 69 :163-178
[6]  
BERGER Z, 1992, AAPG BULL, V76, P101
[7]  
Bilotti F, 2000, AAPG BULL, V84, P727
[8]   3D terrestrial lidar data classification of complex natural scenes using a multi-scale dimensionality criterion: Applications in geomorphology [J].
Brodu, N. ;
Lague, D. .
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2012, 68 :121-134
[9]   Terrestrial laser scanning in geology: data acquisition, processing and accuracy considerations [J].
Buckley, Simon J. ;
Howell, J. A. ;
Enge, H. D. ;
Kurz, T. H. .
JOURNAL OF THE GEOLOGICAL SOCIETY, 2008, 165 :625-638
[10]   Terrestrial lidar and hyperspectral data fusion products for geological outcrop analysis [J].
Buckley, Simon J. ;
Kurz, Tobias H. ;
Howell, John A. ;
Schneider, Danilo .
COMPUTERS & GEOSCIENCES, 2013, 54 :249-258