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Spatial Databases: A Tour
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For Advanced Database Topics courses taught in Computer Science departments
and Advanced Geographic Information Systems courses taught in departments such
as Geography, Natural Resources, Civil Engineering, Urban Planning, Transportation,
Environmental Studies etc.
This text helps students master various stages of spatial database design
and implementation, introducing conceptual models (e.g., pictogram enhanced
ERD), explaining query languages (e.g., OGIS, SQL3), and finally describing
efficient implementations using query optimization and spatial indexes (e.g.,
R-trees). Aimed at students as well as professionals interested in spatial database
and GIS, this text balances theory and practice to provide many firsts: extensive
use of industry standard OGIS spatial data types, comprehensive coverage of
emerging topics of spatial networks, and spatial data mining.
Features
- Comprehensive yet concise overview of Spatial Databases for students
and practitioners.
- Provides students with a comprehensive and clear overview.
- Self-contained treatment without assuming pre-requisite knowledge of
either GIS or Databases.
- Extensive use of industry standards—e.g., OGIS spatial data
types and operations.
- Complete coverage of spatial networks—Including modeling,
querying and storage methods.
- Detailed discussion of emerging topic of Spatial Data Mining.
- Gives students the most current coverage of this quickly growing computing
area.
- Balance between cutting-edge research and commercial trends.
- Variety of exercises at the end of each chapter, and Companion Website.
- Allows students to apply the concepts learned in discussion.
- Easy to understand examples from common knowledge application-domains.
- Object-relational database framework applied in each chapter.
- Keeps students updated on this trend in commercial applications.
Table
of Contents
1. Introduction to Spatial Databases.
2. Spatial Concepts and Data Models.
3. Spatial Query Language.
4. Spatial Storage and Indexing.
5. Query Processing and Optimization.
6. Spatial Networks.
7. Introduction to Spatial Data Mining.
8. Trends in Spatial Databases.
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