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

Philippe Rigaux (Author), Michel Scholl (Author), Agnès Voisard (Author)
4.8 out of 5 stars  See all reviews (4 customer reviews)

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Book Description

1558605886 978-1558605886 June 1, 2001 1


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.

* 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.


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Editorial Reviews

Review

"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

From the Back Cover

"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.

Product Details

  • Hardcover: 410 pages
  • Publisher: Morgan Kaufmann; 1 edition (June 1, 2001)
  • Language: English
  • ISBN-10: 1558605886
  • ISBN-13: 978-1558605886
  • Product Dimensions: 9.3 x 7.4 x 1.1 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)
  • Amazon Best Sellers Rank: #179,805 in Books (See Top 100 in Books)

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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, October 18, 2002
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This review is from: Spatial Databases: With Application to GIS (The Morgan Kaufmann Series in Data Management Systems) (Hardcover)
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.

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5 of 5 people found the following review helpful:
5.0 out of 5 stars A book for deep technical understanding Spatial Databases, February 16, 2006
This review is from: Spatial Databases: With Application to GIS (The Morgan Kaufmann Series in Data Management Systems) (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.
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3 of 3 people found the following review helpful:
5.0 out of 5 stars My second-favorite title for advanced GIS concepts, December 29, 2008
By 
Eric "Map Geek" (Longmont, CO, United States) - See all my reviews
(REAL NAME)   
This review is from: Spatial Databases: With Application to GIS (The Morgan Kaufmann Series in Data Management Systems) (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.
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Inside This Book (learn more)
First Sentence:
"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
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
alphanumeric criteria, surfacic objects, geometric identifier, symbolic tuples, tessellation mode, bucket extents, directory rectangle, constraint data model, linear constraint model, arc identifier, monotone components, visibility segment, geometric union, spaghetti model, convex components, object duplication, linear quadtree, geographic objects, spatial join, external memory algorithms, nested loop algorithm, window query, monotone polygons, spatial access methods, spatial query processing
Key Phrases - Capitalized Phrases (CAPs): (learn more)
San Francisco, United States, Census Bureau, Adm Arcedit, Geographic Space Modeling, Length of Interstate, Two Optimal
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