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. * 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
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. * 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
Multidimensional data is data that exists and changes in more than one dimension, by time, or spatially, or both, sometimes dynamically. Think here of tracking hurricane data in order to project the storm's path, for just one example. As spatial and other multidimensional data structures become increasingly important for the applications in game programming, data mining, bioinformatics, and many other areas--including astronomy, geographic information systems, physics, etc., the need for a comprehensive book on the subject is paramount. This book is truly a life's work by the author who is clearly the best person for the job.
THE thorough and authoritative treatment on multidimensional data structures.
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.
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
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