| Abstract |
Three-dimensional (3D) geospatial technologies are essential in urban digital twins, smart cities, and metaverse. Rendering large-scale terrain data, often exceeding tens of terabytes, presents challenges. While planetary-scale platforms, like Google Earth and Cesium stream data, the streaming of data and the use of regular grid-type digital elevation models lead to cracks among tiles with different levels of detail. This paper proposes a novel dynamic tile-map generation method to eliminate these cracks. Unlike existing methods, our approach leverages tile subindex information to efficiently construct a tile adjacency map, significant reducing the search space for neighboring tiles and eliminating the need for prior knowledge of the terrain tile structure. Furthermore, our approach is robust to data loss, mitigating cracks caused by missing or incomplete tiles. Compared with existing root-down search methods, our method reduces processing time by 1–5 ms per frame and decreases the number of tile-to-tile links by a factor of 3–5, as demonstrated by experimental results. 1225-6463/$ © 2025 ETRI. |
