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Spatial databases with application to GIS
Rigaux P., Scholl M., Voisard A., Morgan Kaufmann Publishers Inc., San Francisco, CA, 2002. 410 pp. Type: Book (9781558605886)
Date Reviewed: Jan 9 2004

The first generation of computer applications involved numerical computing. The second, as a response to the demands of commercial data processing, led to new data structures and algorithms for searching, sorting, and related topics. We are now in the third generation, driven mostly by computing with geometries, multimedia objects, and geographic data.

The relational database, with its simple conceptual structures, was extended to handle the spatial and multimedia data. However, it turned out that mapping relations like polyhedra, faces, edges, and vertices into tabular form had deleterious consequences. Geometric proximity, no matter how far apart in space, is not reflected by proximity in memory. Vertices get stored contiguously in the same relation, whereas a vertex and its incident edges are scattered all over the storage; an object has to be gathered in bits and pieces during several disk accesses. These and other factors persuaded the database management system (DBMS) community to investigate new ways to improve spatial data handling. The rapid strides in the areas of computer-aided design (CAD), very large-scale integration (VLSI), robotics, and image processing, all of which involve spatial data, are crying for efficiency and speed in representing and querying spatial data.

The way to broaden such investigations is by weaning many more researchers into the field. This can happen by inviting the DBMS and the geographic information system (GIS) communities to familiarize themselves with each other’s field of research. Books similar to this one will go a long way toward that goal. The book is aimed at database researchers and others involved in the development of tools for spatial applications, and geographers and GIS users, eager to understand the intricacies of GIS technology and effective management of geospatial data.

In the parlance of GIS, a geographic object has two components: the object description and its spatial component. The spatial component is also referred to as a spatial object, which defines the shape and location of the object in the embedding space. The spatial object, along with the description and an identifier, constitutes a geographic object, also referred to as an entity or feature. Chapter 2 deals with modeling and representing spatial objects, and the presentation is oriented toward readers with substantial database background.

The basic concepts of spatial object representation are illustrated using the spatial data exchange formats like topologically integrated geographic encoding and referencing (TIGER) and Open GIS Consortium (OGC). Chapter 3 deals with representation and querying of geographic objects, using the concept of abstract data types (ADTs). The chapter describes the representation of geographic objects, using an extended relational model as a support, and formulation of queries in an SQL-like language.

Instead of adding new data types to relational DBMSs that are limited to handle finite relations, the constraint data model extends the capability of relational databases to handle infinite relations. Chapter 4 shows how the constraint model can be extended to handle higher-dimensional data as seen in moving objects (spatio-temporal data) and elevation data (field-based data).

Chapter 5, “Computational Geometry,” discusses the algorithmic techniques for implementing the spatial databases. Algorithms, their analyses, performance evaluation, data structures, different algorithmic strategies, and polygon partitioning are some of the topics covered here. Included in this chapter are algorithms for some of the more prominent problems in spatial databases.

Common access methods available for off-the-shelf DBMSs cannot be used for processing spatial queries, since the latter leads to the execution of complex and enormous geometric computations. Issues concerning the spatial access methods and the data structures and algorithms for efficient query processing are the main concern of chapter 6.

In relational query languages, any given query can lead to many equivalent algebraic expressions. For a given algebraic expression, there are several query execution plans, as there are several possible accesses to the data and many algorithms available for each operator. Interesting algorithms for optimization and execution of complex spatial queries for spatial joins make up chapter 7.

The last chapter gives a thorough rundown on the current commercial GIS packages (ArcInfo, ArcView GIS, Smallworld, PostgreSQL, and Oracle’s extension for spatial data). For each system, its functionalities are benchmarked against those discussed in the previous chapters.

Bibliographic notes follow each chapter, and a bibliography follows the last chapter. The authors have done justice to the task they set at the beginning. The dual target of database designer and GIS user is kept in sight from the start to the end of the book. Database designers and GIS users are bound to find this work extremely useful as a source book for theory, algorithms, and methods for augmenting efficiency. The authors, editors, and publishers deserve compliments for an excellent task accomplished.

Reviewer:  A. K. Menon Review #: CR128889 (0406-0658)
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