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Open AccessArticle

Continuous-Scale 3D Terrain Visualization Based on a Detail-Increment Model

1
College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
2
Qingdao Yuehai Information Service Co, Ltd., Qingdao 266590, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(10), 465; https://doi.org/10.3390/ijgi8100465
Received: 16 July 2019 / Revised: 19 September 2019 / Accepted: 21 October 2019 / Published: 22 October 2019
(This article belongs to the Special Issue Landscape Modelling and Visualization)
Triangulated irregular networks (TINs) are widely used in terrain visualization due to their accuracy and efficiency. However, the conventional algorithm for multi-scale terrain rendering, based on TIN, has many problems, such as data redundancy and discontinuities in scale transition. To solve these issues, a method based on a detail-increment model for the construction of a continuous-scale hierarchical terrain model is proposed. First, using the algorithm of edge collapse, based on a quadric error metric (QEM), a complex terrain base model is processed to a most simplified model version. Edge collapse records at different scales are stored as compressed incremental information in order to make the rendering as simple as possible. Then, the detail-increment hierarchical terrain model is built using the incremental information and the most simplified model version. Finally, the square root of the mean minimum quadric error (MMQE), calculated by the points at each scale, is considered the smallest visible object (SVO) threshold that allows for the scale transition with the required scale or the visual range. A point cloud from Yanzhi island is converted into a hierarchical TIN model to verify the effectiveness of the proposed method. The results show that the method has low data redundancy, and no error existed in the topology. It can therefore meet the basic requirements of hierarchical visualization. View Full-Text
Keywords: triangulated irregular network; continuous-scale; detail-increment model; quadric error metric; edge collapse; smallest visible object triangulated irregular network; continuous-scale; detail-increment model; quadric error metric; edge collapse; smallest visible object
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Ai, B.; Wang, L.; Yang, F.; Bu, X.; Lin, Y.; Lv, G. Continuous-Scale 3D Terrain Visualization Based on a Detail-Increment Model. ISPRS Int. J. Geo-Inf. 2019, 8, 465.

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