We deal with quite a few geometric problems in spatial indexes. An area of curiosity is spherical data. Two primary cases are the locations of stars in the sky and geodesic data. Part one of this project deals with a few of the challenges in handling spherical data with a spatial database. We demonstrate that a practical method for integrating spherical data in a conventional spatial database is by using an appropriate mapping from the unit sphere to a rectangle. This enables us to simply use conventional two-dimensional spatial data structures on spherical data. We further describe algorithms to handle spherical data. In the second section of the dissertation, we introduce the areal projection, a novel projection that is computationally efficient and has low distortion. We reveal that the areal projection may be used for creating a competent method for low distortion quantization of unit normal vectors. This really is ideal for compact storage of spherical data and it has applications in computer….
Geometric Issues in Spatial Indexing Downloads
Source: University of Maryland