Advances in Earth Science ›› 2017, Vol. 32 ›› Issue (9): 996-1005. doi: 10.11867/j.issn.1001-8166.2017.09.0996

Special Issue: 青藏高原研究——青藏科考虚拟专刊

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Data Assimilation and Three-dimensional Visualization of Lithospheric Structures of the Eastern Margin of the Tibetan Plateau


  1. 1. School of Earth Sciences and Engineering, Sun Yat-sen University, Guangzhou 510275, China
    1. Guangdong Provincial Key Laboratory of Geological Processes and Mineral Resources Survey, Guangzhou 510275, China
  • Received:2017-04-04 Revised:2017-07-20 Online:2017-09-20 Published:2017-09-20
  • Supported by:
    Project supported by the National Natural Science Foundation of China “Numerical modelling of crustal deformation and dynamics in the east margin of Tibetan Plateau”(41574087)

Various three-dimensional (3D) geophysical and geological data are increasingly available with the advanced technology in the recent years. New challenges emerge frequently in visualizing 3D data due to data variety and the specific display requirement. In this study, we presented a solution of the data assimilation and visualization of lithospheric structures in the eastern margin of the Tibetan Plateau. Three typical datasets were assimilated in the model: ①seismic velocity to the depth of 100 km, ②fault geometry in the upper-and mid-crust and ③topographical data on the surface. The S and P wave velocities in the study area obtained from a high-density portable seismic array were interpolated into regular blocks of the size of 1 km×1 km×2 km and written in RAW format. The major active faults were digitalized and their 3D geometry was generalized by using striking and trending angles, and then organized into unstructured VTK format. The surface topographical DEM data were also converted into unstructured VTK format. In order to integrate and visualize the data, an open source multi-platform software package Paraview was used. It offered various visualization schemes; in particular, volume rendering technique provided stunning static/dynamic images of the structures and highlighted the anomalies in the 3D space. This solution can be applied to other types of 3D geophysical and geological data.

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