The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XL-4/W2
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-4/W2, 101–105, 2013
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-4/W2, 101–105, 2013

  25 Oct 2013

25 Oct 2013

Rapid visualization of global image and dem based on SDOG-ESSG

H. G. Bo1, L. X. Wu1,2, J. Q. Yu3, Y. Z. Yang4, and L. Xie1 H. G. Bo et al.
  • 1College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, 100083, P.R. China
  • 2Key Laboratory of Environment Change and Natural Disaster, Beijing Normal University, Beijing, 100875, P.R. China
  • 3School of Environment Science and Spatial Informatics, China University of Mining and technology, Xuzhou, Jiangsu, 221116, P.R. China
  • 4College of Resources and Civil Engineering, North-eastern University, Shenyang, Liaoning, 110819, P.R. China

Keywords: SDOG-ESSG, rapid visualization, LOD, layers and blocks, data culling, GPU parallel compute

Abstract. Due to the limit of the two-dimension and small scale issues, it's impossible for the conventional planar and spherical global spatial grid to provide a unified real three-dimensional (3D) data model for Earth System Science research. The surface of the Earth is an important interface between lithosphere and atmosphere. Usually, the terrain should be added into the model in global changes and tectonic plates movement researches. However, both atmosphere and lithosphere are typical objects of three-dimension. Thus, it is necessary to represent and visualize the terrain in a real 3D mode. Spheroid Degenerated Octree Grid based Earth System Spatial Grid (SDOG-ESSG) not only solve the problem small-scale issues limited, but also solve the problem of two-dimension issues oriented. It can be used as real 3D model to represent and visualize the global image and DEM. Owing to the complex spatial structure of SDOG-ESSG, the visual efficiency of spatial data based on SDOG-ESSG is very low. Methods of layers and blocks data organization, as well as data culling, Level of Detail (LOD), and asynchronous scheduling, were adopted in this article to improve the efficiency of visualization. Finally, a prototype was developed for the quick visualization of global DEM and image based SDOG-ESSG.