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

Abstract

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.

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“…The generation of 3D models at different scales has already been addressed by the research community (Salonia et al, 2009). Also, structures for geographic information that support smooth zoom and may handle both 2D and 3D data have been proposed (van Oosterom and Meijers, 2011;2014) and structures that implement continuous-scale 3D visualization based on a detail-increment model that avoids the disadvantages of a static Level of Detail (LoD) model have been introduced (Ai et al, 2019). Furthermore, the concept of multiple dimensions, has already been implemented in various systems, e.g., by Ohori et al (2015), who introduced scale as the fourth dimension, and by Ioannidis et al (2015), who introduced time and scale as additional dimensions within a 5D land information system.…”