Series: The Morgan Kaufmann Series in Data Management Systems
Hardcover: 410 pages
Publisher: Morgan Kaufmann; 1 edition (June 1, 2001)
Language: English
ISBN-10: 1558605886
ISBN-13: 978-1558605886
Product Dimensions: 7.7 x 1.2 x 9.6 inches
Shipping Weight: 2.3 pounds (View shipping rates and policies)
Average Customer Review: 4.8 out of 5 stars See all reviews (4 customer reviews)
Best Sellers Rank: #1,195,788 in Books (See Top 100 in Books) #109 in Books > Computers & Technology > Programming > Graphics & Multimedia > GIS #272 in Books > Science & Math > Earth Sciences > Geography > Information Systems #506 in Books > Computers & Technology > Networking & Cloud Computing > Network Administration > Storage & Retrieval
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.
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