Construction Of The Mountain Object Based On Dem Analysis

At present, terrain model include Grid, TIN. Contour etc. The above models are based on the field viewpoint that does not have a terrain object, only a single pixel, contours, triangular facets. In fact, object exists in terrain. But how to define the object in the terrain and how to evaluate the definition method is still in a relatively weak phase. In this study, we try to construct object for mountain which is one of the most important terrain.The basis of mountain object construction is extraction the mountain boundary line and mountain skeleton. The drainage basins in Anti-Terrain could define mountain boundary line. Mountain skeleton contain ridge and valley lines. This paper based on DEM, we used D8algorithm to extract valley line.Then we used sub-basin boundary to extract ridge line.To get the hierarchical mountain object we proposed classification method for the valley lines and ridgelines. The basis of valley line network which was extracted by D8algorithm is flow accumulation.Beacause of water direction, this algorithm was suitable valley line. However, the ridge lines we extracted by sub-basin boundary neither own direction, nor can get flow accumulation. But, it is a hierarchical tree structure. Therefore, we converted ridge line network into binary tree to get depth of the binary tree which was the basis of classification. After grading, line network skeleton has a good hierarchical relationship, but it can’t be directly selected as the network backbone for each layer. Thus, we use K-Means algorithm to cluster skeleton line by grid and length. Then we select the best clustering a set of data as a skeleton network.In this study, we use SRTM90DEM terrain data to extract the boundary line of the mountain valley lines, ridgelines based on ArcGIS Desktop software.And then we made the grading algorithm come true on the ArcGIS Engine10and Visual Studio2010plantform using C#language.The result show that the grading algorithm we proposed could get the hierarchy structure. Using K-Means clustering algorithm to obtain the optimal skeleton line with each boundary line mountain lap, can basically be divided into each mountain object. Whole experimental results show that mountain object construction method in this paper is basically feasible.