Preface
Acknowledgments
1. Introduction
1.1 Spatial data types, predicates, and queries
1.2 Extending a DBMS to an SDBMS
1.3 Historical evolution of research and systems development
1.4 Summary and outline
2. Spatial data
2.1 Spatial relationships
2.1.1 Topological relationships
2.1.2 Directional relationships
2.1.3 Distance relationships
2.2 Spatial queries
2.3 Issues in spatial query processing
2.3.1 Extent or not?
2.4 Summary
3. Indexing
3.1 Point access methods
3.1.1 The grid file
3.1.2 Space filling curves
3.1.3 The quadtree
3.2 Indexing objects with extent
3.3 The R-tree
3.3.1 Optimization of the R-tree structure
3.3.2 The R*-tree: an optimized version of the R-tree
3.3.3 Bulk-loading R-trees
3.4 Summary
4. Spatial query evaluation
4.1 Spatial selections
4.2 Nearest neighbor queries
4.2.1 A depth-first nearest neighbor search algorithm
4.2.2 A best-first nearest neighbor search algorithm
4.2.3 K-nearest neighbor search and incremental search
4.3 Spatial joins
4.3.1 Index-based methods
4.3.2 Algorithms that do not consider indexes
4.3.3 Single-index join methods
4.3.4 A unified spatial join approach
4.3.5 Comparison of spatial join algorithms
4.3.6 The refinement step of a spatial join
4.3.7 Distance joins and related queries
4.4 Query optimization
4.4.1 Selectivity estimation
4.4.2 Cost estimation for spatial query operations
4.5 Summary
5. Spatial networks
5.1 Modeling spatial networks
5.2 Disk-based indexing approaches
5.3 Shortest path computation
5.3.1 Dijkstras algorithm
5.3.2 A* search
5.3.3 Bi-directional search
5.3.4 Speeding-up search by preprocessing
5.3.5 Query points on graph edges
5.4 Evaluation of spatial queries over spatial networks
5.4.1 Distance-based spatial selection
5.4.2 Nearest-neighbor retrieval
5.4.3 Join queries
5.5 Path materialization techniques
5.5.1 Hierarchical path materialization
5.5.2 Compressing and indexing materialized paths
5.5.3 Embedding methods
5.6 Summary
6. Applications of spatial data management technology
6.1 Spatio-temporal data management
6.1.1 Models and queries for spatio-temporal data
6.1.2 Indexing
6.2 High dimensional data management
6.2.1 Similarity measures and queries
6.2.2 Multi-dimensional indexes and the curse of dimensionality
6.2.3 Gemini: generic multimedia object indexing
6.3 Multi-criteria ranking
6.3.1 Top-k and skyline evaluation using spatial access methods
6.3.2 Spatially ranking data
6.4 Data mining and OLAP
6.4.1 Classification
6.4.2 Clustering
6.4.3 Association rules mining
6.4.4 Spatial aggregation and on-line analytical processing
6.5 Privacy-preserving publication of microdata
6.6 Spatial information retrieval
6.6.1 The inverted file
6.6.2 Ranking by relevance
6.6.3 Indexing for ranking queries
6.6.4 Spatial keyword search
6.7 Summary
Bibliography
Author's biography.