Employing united Delaunay triangulation in contour lines generalization

Geomorphologic elements such as valley, ridge are structural information to represent natural geomorphology in spatial extension and distribution. The united Delaunay triangulation network methodology makes an improvement over traditional triangulation method, with its capability of detecting human recognizable bends. Although this united Delaunay triangulation network is more suitable for terrain structure extraction, it hasn't yet been applied in contour line generalization. This article aims at exploring its application in contour lines generalization. First, the curves of contours lines are extracted, and then at the curves local terrain structure lines are linked together. Later, a tree structure of these structure lines is built, representing their relations. In generalization, the square root model is chosen for specifying the number of valley selection. And based on the built triangulation network several important aspects to evaluate the importance of valley are taken as quantitative indexes for determining which valley needs kept and which removed. The general valley importance index calculated by this evaluation method affects the degree of generalization. In result, the generalized map generally shows no intersection and keeps the original terrain characteristic, and, thus exemplifying this united Delaunay triangulation model's great potential in contour line generalization.

[1]  John F. O'Callaghan,et al.  The extraction of drainage networks from digital elevation data , 1984, Comput. Vis. Graph. Image Process..

[2]  Christopher B. Jones,et al.  Map generalization in the Web age , 2005, Int. J. Geogr. Inf. Sci..

[3]  B. Schneider,et al.  Surface Networks: Extension of the Topology and Extraction from Bilinear Surface Patches , 2003 .

[4]  Wang Yu-hai A Study on the Autotracing Approach of Topgraphic Structure Based on Vector Contour Data , 2002 .

[5]  Nicholas Chrisman,et al.  Cartographic Data Structures , 1975 .

[6]  William W. Seemuller The extraction of ordered vector drainage networks from elevation data , 1989, Comput. Vis. Graph. Image Process..

[7]  Ron Johnston,et al.  , Geographical Information Systems Volume 1: Principles and Technical Issues , 1999 .

[8]  Christopher B. Jones,et al.  Characterisation and generalisation of cartographic lines using Delaunay triangulation , 2002, Int. J. Geogr. Inf. Sci..

[9]  A. Skidmore Terrain position as mapped from a gridded digital elevation model , 1990 .

[10]  Wu Fa Research on Methods for Medial Axis Extraction , 2004 .

[11]  Zhao Jie The Extraction of Topographic Patterns Based on Regular Grid DEMs , 2004 .

[12]  F. Töpfer,et al.  The Principles of Selection , 1966 .

[13]  Robert M. Haralick,et al.  Topographic classification of digital image intensity surfaces using generalized splines and the discrete cosine transformation , 1984, Comput. Vis. Graph. Image Process..

[14]  T. Kanade,et al.  Extracting topographic terrain features from elevation maps , 1994 .

[15]  Ai Ting A Binary Tree Representation of Curve Hierarchical Structure in Depth , 2001 .

[16]  James B. Campbell,et al.  DNESYS-an expert system for automatic extraction of drainage networks from digital elevation data , 1990 .

[17]  Tinghua Ai,et al.  The drainage network extraction from contour lines for contour line generalization , 2007 .

[18]  Zhang Gen-shou,et al.  Extraction of Landform Features and Organization of Valley Tree Structure Based on Delaunay Triangulation Model , 2003, National Remote Sensing Bulletin.

[19]  Wu Jin,et al.  Extracting Terrain Features from Contour Maps Based on United-Delaunay-Triangulation Model , 2007 .