"Spatial Databases" is the first unified, in-depth treatment of special techniques for dealing with spatial data, particularly in the field of geographic information systems (GIS). This book surveys various techniques, such as spatial data models, algorithms, and indexing methods, developed to address specific features of spatial data that are not adequately handled by mainstream DBMS technology. The book also reviews commercial solutions to geographic data handling: ArcInfo, ArcView, and Smallworld GISs; and two extensions to the relational model, PostgreSQL and Oracle Spatial. The authors examine these underlying GIS technologies, assess their strengths and weaknesses, and consider specific uses for which each product is best suited. It examines the strengths of various query languages and approaches to query processing. It explains the use of computational geometry in spatial databases GISs, providing necessary background and an in-depth look at key algorithms. It covers spatial access methods, including the R-tree and several space-driven structures, and is filled with dozens of helpful illustrations.
Spatial Databases
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"Spatial Databases covers all of the major themes of the field -- representation, query languages, computational geometry, spatial indexing -- using geographic information systems as the principal application domain and motivation. It is an excellent introduction for computer science professionals interested in exploring GIS, and an excellent resource for GIS professionals interested in learning more about the computer science foundations of the field." --Michael F. Goodchild, National Center for Geographic Information and Analysis, and University of California, Santa Barbara "Spatial Databases is a well-written, comprehensive treatment of a multi-disciplinary field, spanning computational geometry, database modeling, object-orientation, and query processing. The book presents both advanced research and commercial systems in a clear and accessible manner. This book is essential for understanding the current state of the art. Well done!" --Professor Dennis Shasha, New York University
About the Author
Philippe Rigaux is Assistant Professor of Computer Science at CNAM (Conservatoire National des Arts et Metiers), where his work focuses on spatial applications for database systems. Michel Scholl is a Professor of Computer Science at CNAM and a Senior Researcher at INRIA (French Institut National de Recherche en Informatique et en Automatique). His recent work has focused on spatial databases and digital libraries. Agnes Voisard is Assistant Professor of Computer Science at the Free University of Berlin and a System Architect at Kivera, Inc. Her research interests include data models for geographic and environmental information systems, interoperability in information systems, and navigation systems.
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Front Cover | Copyright | Table of Contents | Excerpt | Index
"If we move away from the traditional paper map and the explanation or journal that usually accompanies it, we have to consider a new type of digital information, characterized by its large volume (for instance, the amount of images recorded per day by a sa" Read the first page
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4.8 out of 5 stars
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18 of 18 people found the following review helpful
5.0 out of 5 stars
A textbook geared to advanced GIS analysts
18 Oct 2002
By Orlandoer
- Published on Amazon.com
Format:Hardcover|Amazon Verified Purchase
Very nicely written book. It is quite technical, with a very detailed and mathematically-oriented exposition. More suitable for a classroom teaching or for a GIS software developer/expert analyst than for the average user. Contains great chapters on representation of spatial objects and concepts, and computational geometry algorithms.
A must have for a GIS software developer or a GIS analyst trying to gain a deeper understanding of GIS database organization and optimal query algorithms. Too deep for beginners and occasional GIS users.
5 of 5 people found the following review helpful
5.0 out of 5 stars
A book for deep technical understanding Spatial Databases
16 Feb 2006
By Ali Roshannejad
- Published on Amazon.com
Format:Hardcover
Last summer, when I was asked to present an "Advanced GIS" course for some of grad students in Geomatics, I was fortunate enough to find this book on my first round of serach. It is a great book with deep technical explanation of the subject and its applications. It is more a type of textbook than a book can be used by general public. However, public users may still find some chapters informative. I recommend this book as a grad textbook for those who need technical undetrstanding of spatial databases in GIS.
4 of 4 people found the following review helpful
5.0 out of 5 stars
My second-favorite title for advanced GIS concepts
29 Dec 2008
By Eric B. Wolf
- Published on Amazon.com
Format:Hardcover
This textbook is an excellent resource for people specifically interested in the theoretical nuts and bolts of spatial databases. The book covers a lot of ground in just over 400 pages. It would be an excellent text for an advanced GIS programming course for either geography students or computer science students. For the geography student, the text provides an excellent coverage of database concepts while drawing on familiar topics. For the computer science student, the book extends basic knowledge of DBMS for spatial applications.
The book is divided into eight chapters. Each chapter is completed with an excellent bibliographical review of relevant publications. This review, alone, is worth the price of the book.
Chapter 1: Introduction to Spatial Database: Covers basic concepts of SQL, DBMS and spatial data.
Chapter 2: Representation of Spatial Objects: This chapter should be familiar to anyone with a GIS background but would fill in the gaps for computer science students. The section on formats and standards is a bit dated but provides a nice theoretical background - especially for the Census TIGER data.
Chapter 3: Logical Models and Query Languages: Opposite of Chapter 2, this chapter will challenge the Geography student while further grounding the Computer Science student in GIS data types.
Chapter 4: The Constraint Data Model: Here the authors choose to introduce some unique material in the form of the constraint data model. The model is designed specifically to encode spatial data in a basic relational model. The chapter even breaks down the model into relational algebra statements. For most teaching purposes, this chapter can be skipped.
Chapter 5: Computational Geometry: An odd gem in a text on spatial databases. This chapter provides a basic introduction to computation geometry techniques and their application to spatial data. One of the most significant aspects of a spatial databases is that it encodes geometric representations of geographic phenomena. Basic computational geometry is a necessary extension for a database to truly support spatial data. Pseudo-code is given but I would recommend the classic Computational Geometry in C (Cambridge Tracts in Theoretical Computer Science) for detailed implementations. This chapter will be challenging for Geography students but simple for Computer Science students.
Chapter 6: Spatial Access Methods: The biggest challenge for spatial databases is spatial indexing - adding a true sense of "where" to SELECT...WHERE! The chapter focuses mostly on classical index structures - B-tree, R-Tree, etc. This would be a good chapter for a "short week" as it is either a research focus or matter of "it just works". Students who desire to research spatial indexing will find the chapter lacking. Others will find it overwhelming.
Chapter 7: Query Processing: Like Chapter 6, this chapter delves into details that only a student truly interested in researching spatial indexes or developing new databases would be concerned with. The chapter presents how the spatial index is utilized for joins and relates.
Chapter 8: Commercial Systems: Any book that attempts to survey existing software is always out of date. This chapter might be of historical interest but is hardly worth covering. The section of PostgreSQL is interesting but better material exists on the web.
Overall, the book is well written and clearly presents the material. The coverage is focused on applications to spatial databases. My favorite advanced GIS textbook is GIS: A Computing Perspective, Second Edition.
The book is divided into eight chapters. Each chapter is completed with an excellent bibliographical review of relevant publications. This review, alone, is worth the price of the book.
Chapter 1: Introduction to Spatial Database: Covers basic concepts of SQL, DBMS and spatial data.
Chapter 2: Representation of Spatial Objects: This chapter should be familiar to anyone with a GIS background but would fill in the gaps for computer science students. The section on formats and standards is a bit dated but provides a nice theoretical background - especially for the Census TIGER data.
Chapter 3: Logical Models and Query Languages: Opposite of Chapter 2, this chapter will challenge the Geography student while further grounding the Computer Science student in GIS data types.
Chapter 4: The Constraint Data Model: Here the authors choose to introduce some unique material in the form of the constraint data model. The model is designed specifically to encode spatial data in a basic relational model. The chapter even breaks down the model into relational algebra statements. For most teaching purposes, this chapter can be skipped.
Chapter 5: Computational Geometry: An odd gem in a text on spatial databases. This chapter provides a basic introduction to computation geometry techniques and their application to spatial data. One of the most significant aspects of a spatial databases is that it encodes geometric representations of geographic phenomena. Basic computational geometry is a necessary extension for a database to truly support spatial data. Pseudo-code is given but I would recommend the classic Computational Geometry in C (Cambridge Tracts in Theoretical Computer Science) for detailed implementations. This chapter will be challenging for Geography students but simple for Computer Science students.
Chapter 6: Spatial Access Methods: The biggest challenge for spatial databases is spatial indexing - adding a true sense of "where" to SELECT...WHERE! The chapter focuses mostly on classical index structures - B-tree, R-Tree, etc. This would be a good chapter for a "short week" as it is either a research focus or matter of "it just works". Students who desire to research spatial indexing will find the chapter lacking. Others will find it overwhelming.
Chapter 7: Query Processing: Like Chapter 6, this chapter delves into details that only a student truly interested in researching spatial indexes or developing new databases would be concerned with. The chapter presents how the spatial index is utilized for joins and relates.
Chapter 8: Commercial Systems: Any book that attempts to survey existing software is always out of date. This chapter might be of historical interest but is hardly worth covering. The section of PostgreSQL is interesting but better material exists on the web.
Overall, the book is well written and clearly presents the material. The coverage is focused on applications to spatial databases. My favorite advanced GIS textbook is GIS: A Computing Perspective, Second Edition.
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