Volume IV-4
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4, 119-124, 2018
https://doi.org/10.5194/isprs-annals-IV-4-119-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4, 119-124, 2018
https://doi.org/10.5194/isprs-annals-IV-4-119-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Sep 2018

19 Sep 2018

EFFICIENT AND ACCURATE FUSION OF MASSIVE VECTOR DATA ON 3D TERRAIN

Z. Liu1, C. Li1, Z. Zhao1, D. Zhang2, F. Wang1, and Y. Wang1 Z. Liu et al.
  • 1Institute of Cartography and Geographic Information System, Chinese Academy of Surveying and Mapping, Beijing, China
  • 2Tai'an City Golden Land Surveying and Mapping Company, Shandong, China

Keywords: vector data, 3D terrain, seamless fusion, multi thread, level of detail

Abstract. This paper presents a viewpoint-related fusion method of massive vector data and 3D terrain, in order to superpose the massive 2D vector data onto the undulating multi-resolution 3D terrain precisely and efficiently. First, the method establishes an adaptive hierarchical grid spatial index for vector data. It will determine the geographic spatial relationship between vector data and the tiles of 3D terrain in the visible area; secondly, this method will use the improved sub-pixel graphics engine AggExt to generate textures for vector data that has been bound to terrain tiles in real time; Finally, considering that a large amount of vector data will generate a lot of 2D textures in the computer memory, the method should release the “expired” vector textures. In this paper, in order to take into account the real-time convergence and the smooth interactivity of 3D scenes, this method will adopt a multi-threading strategy. The experimental results show that this method can realize the real-time and seamless fusion of massive vector objects on the 3D terrain, and has a high rendering frame rate. It can also reduce the aliasing produced by traditional texture-based methods and improve the quality of vector data fusion.