TY - CHAP
T1 - Multidimensional data structures for spatial applications
T2 - Algorithms and theory of computation handbookAlgorithms and theory of computation handbook
Y1 - 2010
A1 - Samet, Hanan
ED - Atallah,Mikhail J.
ED - Blanton,Marina
AB - An overview is presented of a number of representations of multidimensional data that arise in spatial applications. Multidimensional spatial data consists of points as well as objects that have extent such as line segments, rectangles, regions, and volumes. The points may have locational as well as nonlocational attributes. The focus is on spatial data which is a subset of multidimensional data consisting of points with locational attributes and objects with extent. The emphasis is on hierarchical representations based on the "divide-and-conquer" problem-solving paradigm. They are of interest because they enable focusing computational resources on the interesting subsets of data. Thus, there is no need to expend work where the payoff is small. These representations are of use in operations such as range searching and finding nearest neighbors.
JA - Algorithms and theory of computation handbookAlgorithms and theory of computation handbook
PB - Chapman & Hall/CRC
SN - 978-1-58488-822-2
UR - http://dl.acm.org/citation.cfm?id=1882757.1882763
ER -