作者:Wang, F (Wang Feng)[ 1 ] ; Wang, G (Wang Gang)[ 1 ] ; Pan, DJ (Pan Deji)[ 1 ] ; Liu, Y (Liu Yuan)[ 1 ] ; Yang, LZ (Yang Liuzhong)[ 2 ] ; Wang, HB (Wang Hongbo)[ 3 ]

COMPUTERS & GEOSCIENCES

卷: 75  页: 57-65

DOI: 10.1016/j.cageo.2014.10.012

出版年: FEB 2015

摘要

Viewshed analysis, often supported by geographic information systems, is widely used in the three-dimensional (3D) Digital Earth system. Many of the analyzes involve the siting of features and real-timedecision-making. Viewshed analysis is usually performed at a large scale, which poses substantial computational challenges, as geographic datasets continue to become increasingly large. Previous research on viewshed analysis has been generally limited to a single data structure (i.e., DEM), which cannot be used to analyze viewsheds in complicated scenes. In this paper, a real-time algorithm for viewshed analysis in Digital Earth is presented using the parallel computing of graphics processing units (GPUs). An occlusion for each geometric entity in the neighbor space of the viewshed point is generated according to line-of-sight. The region within the occlusion is marked by a stencil buffer within the programmable 3D visualization pipeline. The marked region is drawn with red color concurrently. In contrast to traditional algorithms based on line-of-sight, the new algorithm, in which the viewshed calculation is integrated with the rendering module, is more efficient and stable. This proposed method of viewshed generation is closer to the reality of the virtual geographic environment. No DEM interpolation, which is seen as a computational burden, is needed. The algorithm was implemented in a 3D Digital Earth system (GeoBeans3D) with the DirectX application programming interface (API) and has been widely used in a range of applications. (C) 2014 Elsevier Ltd. All rights reserved.

通讯作者地址: Wang, G (通讯作者)

Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.

地址:

[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China

[ 2 ] Urban Rural Planning Management Ctr, Minist Housing & Urban Rural Dev Peoples Republ C, Beijing 100835, Peoples R China

[ 3 ] China Natl Petr Grp, Managers Training Inst, Beijing 100096, Peoples R China