Spatial Partitioning and Indexing

This lesson will explain the basic concepts of spatial partitioning and indexing processes. Firstly, regular decomposition theory is discussed. The different methods are widely described and illustrated with comprehensive examples.
Afterwards, the object-oriented decomposition is explained, which on completion should allow the understanding of important aspects of spatial partitioning and indexing.

Learning Objectives

You recognise the meaning and characteristics of spatial object approximation and spatial data access methods.
You know and understand the advantages and disadvantages of space and data driven indexes.
You are able to compare different regular decompostion methods (regular grids, quadtrees, etc.) and you are familiar to their specific characteristics.
You can explain the object-oriented B-tree and R-tree decomposition methods.