Abstract
The integration and visualization of geospatial data on a virtual globe play an significant role in understanding and analysis of the Earth surface processes. However, the current virtual globes always sacrifice the accuracy to ensure the efficiency for global data processing and visualization, which devalue their functionality for scientific applications. In this article, we propose a high-accuracy multi-resolution TIN pyramid construction and visualization method for virtual globe. Firstly, we introduce the cartographic principles to formulize the level of detail (LOD) generation so that the TIN model in each layer is controlled with a data quality standard. A maximum z-tolerance algorithm is then used to iteratively construct the multi-resolution TIN pyramid. Moreover, the extracted landscape features are incorporated into each-layer TIN, thus preserving the topological structure of terrain surface at different levels. In the proposed framework, a virtual node (VN)-based approach is developed to seamlessly partition and discretize each triangulation layer into tiles, which can be organized and stored with a global quad-tree index. Finally, the real time out-of-core spherical terrain rendering is realized on a virtual globe system VirtualWorld1.0. The experimental results showed that the proposed method can achieve an high-fidelity terrain representation, while produce a high quality underlying data that satisfies the demand for scientific analysis.
Highlights
Virtual globes play significant role in representing the threemulti-resolution, dimensional (3D) model of the (Gore 1998; Goodchild 2008)
The power of existing virtual globes was still restricted to functions as a “geo-browser”, which were weak at geospatial analysis and assessment (Craglia et al 2012; Yu and Gong 2012)
To extend the capabilities of virtual globes for scientific applications, the quality of data generated by the processing methods and its representation should be specially concerned (Goodchild et al 2012)
Summary
Virtual globes play significant role in representing the threemulti-resolution, dimensional (3D) model of the (Gore 1998; Goodchild 2008). The grid geometry is not adaptive to the irregularity of terrain leading to large data redundancy and large terrain expression distortion (Paredes et al 2015) When those Earth surface dynamics or related analysis results needed to be precisely displayed and evaluated, it could be failed with a distorted terrain representation. Another significant problem is that the grid terrain model is unable to represent the highly detailed surfaces measured by new sensors and methodologies, such as the LiDAR elevation points (Nebiker et al 2010). The TIN in each layer could be seamlessly partitioned and tiled with the global quad-tree structure, so that an efficient out-of-core spherical terrain rendering can be realized
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