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Proceedings Paper

A hybrid 3D data model based on multi-DEMs and QTPVs and its application in geology modeling
Author(s): Penggen Cheng; Xingquan Liu; Jianya Gong; Shaohua Liu
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Paper Abstract

3D spatial data model and modeling method is the core of 3D GIS application in different domains. There have been many 3D data models or data structures investigated in the past years. In geology exploration domain, most stratums are stratified and can be modeled by using multi-DEMs. In terms of a ore deposit, it is necessary to model its inner structures. For achieving this purpose, a modeling method based on Quasi Tri-Prism Volume (QTPV) can be adopted, which has the advantage of close integrating with samples data. Therefore, it is a feasible modeling method that adopting hybrid 3D data model based on multi-DEMs and QTPVs in the 3D modeling of geology body. In this paper, a hybrid 3D spatial data model based on multi-DEMs and Quasi Tri-Prism Volume (QTPV) is proposed. The proposed model is composed of six primitives and six objects. The primitives are vertex, segment (edge, triangle side), triangle, side quadrilateral, QTPV and DEMs, and the objects are point, line, face, solid, complex and spatial object. Data structures and topological relations of the six primitives and two geological objects are designed in detail. Two modeling methods, which are based on samples points and interpolation points, are designed separately. A set of simulation data and a set of real borehole sample data are used to verify the prototype system developed in VC++ program language by us. The research results show that the proposed model has better abilities of describing the surface and the inner structure of spatial objects, and it is suitable for 3D modeling in geology exploration field.

Paper Details

Date Published: 28 October 2006
PDF: 7 pages
Proc. SPIE 6420, Geoinformatics 2006: Geospatial Information Science, 642003 (28 October 2006); doi: 10.1117/12.712614
Show Author Affiliations
Penggen Cheng, Central South Univ. (China)
East China Institute of Technology (China)
Xingquan Liu, Central South Univ. (China)
Jianya Gong, Wuhan Univ. (China)
Shaohua Liu, Yangtze Univ. (China)

Published in SPIE Proceedings Vol. 6420:
Geoinformatics 2006: Geospatial Information Science
Jianya Gong; Jingxiong Zhang, Editor(s)

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