Computer Science

ECS 266 Spacial Databases

ECS 266 SPATIAL DATABASES (4) III

Lecture: 3 hours

Discussion: 1 hour

Prerequisite: Course 165A

Grading: Letter; homework (40%), projects (40%), final (20%)

Catalog Description:
Concepts, models, and architectures for spatial databases, multidimensional access methods, query processing, spatio-temporal data management, remotely-sensed data, spatial data mining

Goals:
This course exclusively focuses on the concepts and methods associated with spatial databases, spatio-temporal databases, and Geographic Information Systems (GIS). Students will learn design and representation models for spatial data, the organizing of different types of spatial data in multidimensional access structures, and query processing strategies for spatial data. Students will also learn about advanced techniques and models, including spatio-temporal data, moving objects, and mining geospatial data

Expanded Course Description:

  1. Introduction to Spatial Databases
    1. Requirements, Principles, and Concepts for SDBMS
    2. Spatial Databases and Geographic Information Systems
    3. SDBMS and GIS Applications
  2. Models for Spatial Data
    1. Geographic Space Modeling
    2. Representation Models
    3. Geometry of Collection of Objects
    4. Vector Data
    5. Raster Data
    6. Modeling Spatial Data
  3. Spatial Access Methods (SAM)
    1. Issues in SAM Design
    2. Space Driven Structures versus Data Driven Structures/li>
    3. The Grid File
    4. Quadtree and Variants
    5. R-Tree and Variants
    6. k-d-B Tree
    7. Other common and useful SAM
    8. Cost Models
  4. Query Processing
    1. Algebras and Query Languages for Spatial Data
    2. Spatial Join Queries
    3. Nearest Neighbor Queries
    4. Queries over Raster Data (Map Algebra)
    5. Cost Models
  5. Spatio-Temporal Databases
    1. Introduction to Temporal Databases
    2. Specialized Index Structures
    3. Query Processing
  6. Spatial DBMS and GIS
    1. Oracle Spatial
    2. GRASS
    3. ArcInfo and ArcView
    4. PostGIS
  7. Advanced Topics
    1. Geographic Data Mining
    2. Streaming (remotely-sensed) Data
    3. Mobile Objects and Location Aware Services

Textbooks:
Philippe Rigaux, Michel Scholl, Agnes Voisard: Spatial Databases with Applications to GIS, Morgan Kaufman, 2002
Shashi Shekhar, Sanjay Chawla: Spatial Databases, Prentice Hall, 2002
Furthermore, a collection of papers addressing specific topics will be distributed in class

Projects:
There will be at least two projects. One project will be done in the form of teams. In these projects, students have to design, implement, and evaluate spatial access structures either from scratch or using a freely available GIS, such as GRASS or PostGIS. Project results will be presented in class

Computer Usage:
Students work individually and in groups on projects in a Linux/UNIX workstation environment, using standard Linux/UNIX tools as well as spatial database software packages (GRASS and PostGIS).

Instructor: M. Gertz

Prepared by: M. Gertz (August 2007)

Overlap Statement:
This course has a very minor overlap with ECS 226, in which some multidimensional access structures are covered.

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