RESEARCH ON THE VISUALIZATION EXPRESSION OF THE INVISIBLE DISPERSIVE FEATURE

J. Guo, Z. Tian, F. Cheng

Dalian Naval Academy, Department of Hydrographic Surveying and Charting, Dalian, China

Guojia828@163l.com

Abstract: It is known to all that 3D GIS is the recent trend in GIS technique, and modeling of 3D data (i.e. spatial data) is the key problem of 3D GIS. 3D data model includes surface data model and volume data model, the modeling methods includes facial modeling and volumetric modeling. The facial modeling method emphasizes particularly on the surface of the geographic entity, for example, the landform, the stratum, the outline of the construction and so on. The volumetric modeling method emphasizes particularly on the interior of the geographic entity, such as water bodies, orebody, mineral lines and so on. Recently, with the development of volume visualization, volume data model becomes one of the most important ways to express the spatial data, it has being used in geology, medicine, meteorology and remote sensing.

In this paper, we discuss the visualization expression of the invisible dispersive feature (such as temperature, density, salinity of sea water and so on). By analyses, we find what the difference between this invisible feature and the visible feature mentioned in the last paragraph (such as orebody and mineral lines) is that the former one is invisible. So we try to express the invisible dispersive feature by the volumetric modeling method mentioned in the last paragraph.

We discuss the volumetric modeling method which embodies two types: regular feature and irregular feature. As to the regular feature, we analyze the CSG-tree, Octree and Regular Block; as to the irregular feature, we analyze the TEN, Pyramid, 3D-Voronoi and GTP. By a lot of digital experimentations, we find their advantages disadvantages and the applying way. In a word, the appropriate modeling method for the visualization expression of the invisible dispersive feature should be in accordance with the characteristics of the invisible dispersive feature.

 

Keywords: 3D Geographic Data Model, volume data, dispersive feature