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Spatial Databases: With Application to GIS (The Morgan Kaufmann Series in Data Management Systems)

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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

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.

Features

  • Examines the strengths of various query languages and approaches to query processing.
  • Explains the use of computational geometry in spatial databases GISs, providing necessary background and an in-depth look at key algorithms.
  • Covers spatial access methods, including the R-tree and several space-driven structures, and is filled with dozens of helpful illustrations.
About the Author

Philippe Rigaux is Assistant Professor of Computer Science at CNAM (Conservatoire National des Arts et Métiers), 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.

Agnès 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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