Preliminary Studies on Contour Tree-based Topographic Data Mining

After many years of intensive investigation and mapping of the topography, a large number of topographic maps were produced by national mapping agencies. The explosive growth and wide availability of topographic data has created a data-rich environment for a variety of GIS users. How to make the best use of such topographic data has become a basic but daunting task. The research challenge now is to develop and use suitable approaches to discover new and interesting patterns, trends and relationships that might be hidden deep within the very large national topographic datasets. Among the digital topographic data, contour line is the most fundamental element. The shape and relationship of contour lines play a key role when human beings recognize topographic features from a contour map. A contour tree is a good graphical tool for representing the spatial relations of contour lines. In this paper, some preliminary researches are introduced, in which contour tree is used as a tool to find some implicitly information hidden in the contour lines that represent seveal typical kinds of landform. Firstly, the spatial relations of contours are classified as multi-order enclosure relation, parallel relation and multi-order disjoint relation, and tree method for representing spatial relations of contours are briefly introduced. Then, several items deduced from contour tree are analysed, i.e. the number of nodes, the number of leaf nodes, and the level of the tree. After comparing the values of these items of the trees of the contours representing mesa, loess ridge and Karst hill in 1:50 000 scale, some preliminary results are obtained which can be used to assist characterize the three landforms.