The field of multidimensional data structures is large and growing very quickly. Here, for the first time, is a thorough treatment of multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets.

The book includes a thorough introduction; a comprehensive survey to spatial and multidimensional data structures and algorithms; and implementation details for the most useful data structures. Along with the hundreds of worked exercises and hundreds of illustrations, the result is an excellent and valuable reference tool for professionals in many areas, including computer graphics, databases, geographic information systems (GIS), game programming, image processing, pattern recognition, solid modeling, similarity retrieval, and VLSI design.

Award Winner in 2006 “Best Book” competition in Professional and Scholarly Publishing from the Association of American Publishers.

Morgan Kaufmann would like to congratulate Hanan Samet on receiving the UCGIS 2009 Research Award!

Read the announcement here:

Key Features

* First comprehensive work on multidimensional data structures available, a thorough and authoritative treatment. * An algorithmic rather than mathematical approach, with a liberal use of examples that allows the readers to easily see the possible implementation and use. * Each section includes a large number of exercises and solutions to self-test and confirm the reader's understanding and suggest future directions. * Written by a well-known authority in the area of spatial data structures who has made many significant contributions to the field. The author's website includes: Spatial Index Demos


This book is for the use of computer scientists who have a need to represent spatial data and as such will appeal to those in data management, computer graphics, game programming, bioinformatics, pattern recognition, GIS, and other non-CS fields like high energy physics, geography, mathematics, and engineering.

Table of Contents

Chapter 1: Multidimensional Point Data 1.1 Introduction 1.2 Range Trees 1.3 Priority Search Trees 1.4 Quadtrees 1.4.1 Point Quadtrees 1.4.2 Trie-based Quadtree 1.4.3 Comparison of Point and Trie-based Quadtrees 1.5 K-d Trees 1.5.1 Point K-d Trees 1.5.2 Trie-based K-d Trees 1.5.3 Conjugation Tree 1.6 One-dimensional Orderings 1.7 Bucket Methods 1.7.1 Tree Directory Methods (K-d-B-tree, Hybrid Tree, LSD Tree, hB-tree, K-d-B-trie, BV-tree) 1.7.2 Grid Directory Methods (Grid File, EXCELL, Linear Hashing, Spiral Hashing) 1.7.3 Storage Utilization 1.8 PK-tree 1.9 Conclusion Chapter 2: Object-based and Image-based Image Representations 2.1 Interior-based Representations 2.1.1 Unit-size Cells 2.1.2 Blocks (Medial Axis Transform, Region Quadtree and Octree, Bintree, X-Y Tree) 2.1.3 Nonorthogonal Blocks (BSP Tree, Layered DAG) 2.1.4 Arbitrary Objects (Loose Octree, Field Tree, PMR Quadtree) 2.1.5 Hierarchical Interior-based Representations (Pyramid, R-tree, Hilbert R-tree, R*-tree, R+-tree, Packed R-tree, R-tree, Cell Tree, Bulk Loading) 2.2 Boundary-based Representations 2.2.1 The Boundary Model (CSG,BREP, Winged-edge, Voronoi Diagram, Delaunay Triangulation, Tetrahedra) 2.2.2 Image-based Boundary Representations (PM Quadtree and Octree, Adaptively Sampled Distance Field) 2.2.3 Object-based Boundary Representation (LOD, Strip Tree, Simplification Methods) 2.2.4 Surface-based Boundary Representations (TIN) 2.3 Difference-based Compaction Methods 2.3.1 Runlength Encoding 2.3.2 Chain Code 2.3.3 Vertex Representation


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© 2006
Morgan Kaufmann
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About the editor

Hanan Samet

Hanan Samet is Professor in the Department of Computer Science at the University of Maryland, and a member of the Center for Automation Research and the Institute for Advanced Computer Studies. He is widely published in the fields of spatial databases and data structures, computer graphics, image databases and image processing, and geographic information systems (GIS), and is considered an authority on the use and design of hierarchical spatial data structures such as the quadtree and octree for geographic information systems, image processing, and computer graphics. He is the author of the two books The Design and Analysis of Spatial Data Structures and Applications of Spatial Data Structures: Computer Graphics, Image Processing and GIS. He holds a Ph.D. in computer science from Stanford University.

Affiliations and Expertise

University of Maryland at College Park, author of the pioneering books in this field, The Design and Analysis of Spatial Data structures, and Applications of Spatial Data Structures: Computer Graphics, Image Processing, and GIS, both published by Addison-Wesley, 1990.


Honorable Mention Award in the 2006 best book in Computer and Information Science competition from the Professional and Scholarly Publishers(PSP) Group of the American Publishers Association (AAP) “Hanan Samet is the dean of “spatial indexing”... This book is encyclopedic... this book will be invaluable for those of us who struggle with spatial data, scientific datasets, graphics, vision problems involving volumetric queries, or with higher dimensional datasets common in data mining.” — From the foreword by Jim Gray, Microsoft Research “Samet’s book on multidimensional and metric data structures is the most complete and thorough presentation on this topic. It has broad coverage of material from computational geometry, databases, graphics, GIS, and similarity retrieval literature. Written by the leading authority on hierarchical spatial representations, this book is a “must have” for all instructors, researchers, and developers working and teaching in these areas.” — Dinesh Manocha, University of North Carolina at Chapel Hill “To summarize, this book is excellent! It’s a very comprehensive survey of spatial and multidimensional data structures and algorithms, which is badly needed. The breadth and depth of coverage is astounding and I would consider several parts of it required reading for real time graphics and game developers.” — Bretton Wade, University of Washington and Microsoft Corp. “It’s a truly encyclopedic book on data structures for accelerating all sorts of 3D queries.” — Hector Yee, Hectorgon – A Graphics Programming Blog, October 18, 2006