2013•Unpublished venueRequires access

A Simplification Method for Terrain Modeling

Yunhua Gu, Xiaoyan Wu, Jin Wang

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Abstract

To solve the problem of three-dimensional terrain simplification in large-scale based on digital elevation model data, a terrain simplified method based on the theory of spatial autocorrelation was proposed. According to principle of regional similarities in geomorphology, a cluster analysis was performed on the terrain data to get the thresholds distinguish terrain features. On the basis, the gradient-based weighted method was adopted to fit elevation values of the center point and generated a new terrain mesh. The results of experiments show that the method to some extent reduces the size of the data, while maintaining good terrain features and curvature characteristic.

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What this paper is about

To solve the problem of three-dimensional terrain simplification in large-scale based on digital elevation model data, a terrain simplified method based on the theory of spatial autocorrelation was proposed. According to principle of regional similarities in geomorphology, a cluster analysis was performed on the terrain data to get the thresholds distinguish terrain features. On the basis, the gradient-based weighted method was adopted to fit elevation values of the center point and generated a new terrain mesh. The results of experiments show that the method to some extent reduces the size of the data, while maintaining good terrain features and curvature characteristic.

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Available abstract

To solve the problem of three-dimensional terrain simplification in large-scale based on digital elevation model data, a terrain simplified method based on the theory of spatial autocorrelation was proposed. According to principle of regional similarities in geomorphology, a cluster analysis was performed on the terrain data to get the thresholds distinguish terrain features. On the basis, the gradient-based weighted method was adopted to fit elevation values of the center point and generated a new terrain mesh. The results of experiments show that the method to some extent reduces the size of the data, while maintaining good terrain features and curvature characteristic.

Key concepts: Terrain, Computer science, Computer graphics (images), Geography, Cartography

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