作者:Liang, JM (Liang, Jianming)[ 1,2 ] ; Gong, JH (Gong, Jianhua)[ 1,3 ] ; Li, WH (Li, Wenhang)[ 1,3 ] ; Ibrahim, AN (Ibrahim, Abdoul Nasser)[ 1,3 ]
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
卷: 28  期: 4  页: 780-798
DOI: 10.1080/13658816.2014.880168
出版年: APR 3 2014

摘要
The temporal and spatial distribution of solar energy in urban areas is highly variable because of the complex building structures present. Traditional GIS-based solar radiation models rely on two-dimensional (2D) digital elevation models to calculate insolation, without considering building facades and complicated three-dimensional (3D) shading effects. Inspired by the texture baking' technique used in computer graphics, we propose a full 3D method for computing and visualizing urban solar radiation based on image-space data representation. First, a surface mapping approach is employed to project each 3D triangular mesh onto a 2D raster surface whose cell size determines the calculation accuracy. Second, the positions and surface normal vectors of each 3D triangular mesh are rasterized onto the associated 2D raster using barycentric interpolation techniques. An efficient compute unified device architecture -accelerated shadow-casting algorithm is presented to accurately capture shading effects for large-scale 3D urban models. Solar radiation is calculated for each raster cell based on the input raster layers containing such information as slope, aspect, and shadow masks. Finally, a resulting insolation raster layer is produced for each triangular mesh and is represented as an RGB texture map using a color ramp. Because a virtual city can be composed of tens of thousands of triangular meshes and texture maps, a texture atlas technique is presented to merge thousands of small images into a single large image to batch draw calls and thereby efficiently render a large number of textured meshes on the graphics processing unit.

通讯作者地址: Gong, JH (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 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[ 3 ] Zhejiang CAS Applicat Ctr Geoinformat, Hangzhou 314100, Zhejiang, Peoples R China