Multidimensional binary search trees used for associative searching
Communications of the ACM
Quadtree and R-tree indexes in oracle spatial: a comparison using GIS data
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Pro Oracle Spatial for Oracle Database 11g (Expert's Voice in Oracle)
Pro Oracle Spatial for Oracle Database 11g (Expert's Voice in Oracle)
Modelling 3D spatial objects in a geo-DBMS using a 3D primitive
Computers & Geosciences
Binary B-trees for virtual memory
SIGFIDET '71 Proceedings of the 1971 ACM SIGFIDET (now SIGMOD) Workshop on Data Description, Access and Control
Spatial indexing on tetrahedral meshes
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Review: 3D geo-database research: Retrospective and future directions
Computers & Geosciences
An efficient point rendering using octree and texture lookup
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part III
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A large proportion of today's digital datasets have a spatial component. The effective storage and management of which poses particular challenges, especially with light detection and ranging (LiDAR), where datasets of even small geographic areas may contain several hundred million points. While in the last decade 2.5-dimensional data were prevalent, true 3-dimensional data are increasingly commonplace via LiDAR. They have gained particular popularity for urban applications including generation of city-scale maps, baseline data disaster management, and utility planning. Additionally, LiDAR is commonly used for flood plane identification, coastal-erosion tracking, and forest biomass mapping. Despite growing data availability, current spatial information systems do not provide suitable full support for the data's true 3D nature. Consequently, one system is needed to store the data and another for its processing, thereby necessitating format transformations. The work presented herein aims at a more cost-effective way for managing 3D LiDAR data that allows for storage and manipulation within a single system by enabling a new index within existing spatial database management technology. Implementation of an octree index for 3D LiDAR data atop Oracle Spatial 11g is presented, along with an evaluation showing up to an eight-fold improvement compared to the native Oracle R-tree index.