Summary

In this lesson the most often used spatial partitioning and indexing methods were discussed. Using spatial indexing in geodatabases provides fast access to spatial data because only the required part of data is taken into account for spatial analyzing tasks (e.g. give me the result set of buildings which lie inside a specif geometry). The first part of the lesson gave a general remark on spatial object approximation and data access methods. The central point of the module deald with different aspects of regular decomposition (space driven indexing) and object-oriented decomposition (data driven indexing). Some of the most widely used indexing methods (quadtrees, B-tree, R-tree, etc.) were explained.