1. Spatial Databases ENVE/CE 424/524

2. Definitions Database – an integrated set of data on a particular subject Spatial database - database containing geographic data of a particular subject for a particular area Database Management System (DBMS) – software to create, maintain and access databases Data load Editing Visualization Mapping Analysis Storage Indexing Security Query

3. GIS: old and new GIS used to be monolithic systems all-in-one, proprietary applications that stored, queried, and visualized data New systems follow more of a tool-box approach modularized applications that interoperate

4. Who can benefit from spatial data management? Army Commander: Has there been any significant enemy troop movement in the past week? Insurance Risk Manager: Which houses are most likely to be affected in the next great flood on the Mississippi? Medical Doctor: Based on this patient’s MRI, have we treated somebody with a similar condition? Molecular Biologist: Is the topology of the amino acid biosynthesis gene in the genome found in any other sequence feature map in the database? Astronomer: Find all blue galaxies within 2 arcmin of quasars.

5. Three classes of users for spatial databases Major database managers: specialized products for enterprise management GIS users: analysis of data Internet user: more generalized requirements

6. Advantages of Databases over Files Avoids redundancy and duplication Reduces data maintenance costs Applications are separated from the data –Applications persist over time –Support multiple concurrent applications Better data sharing Security and standards can be defined and enforced

7. Disadvantages of Databases over Files Expense Complexity Performance – especially complex data types Integration with other systems can be difficult

8. Types of DBMS Model Hierarchical Network Relational – RDBMS Object-oriented – OODBMS Object-relational - ORDBMS

9. Characteristics of DBMS Data model support for multiple data types –e.g MS Access: Text, Memo, Number, Date/Time, Currency, AutoNumber, Yes/No, OLE Object, Hyperlink, Lookup Wizard Load data from files, databases and other applications Index for rapid retrieval Query language – SQL Security – controlled access to data –Multi-level groups Controlled update using a transaction manager Backup and recovery

10. Relational DBMS Data stored as tuples (tup-el), conceptualized as tables Table – data about a class of objects –Two-dimensional list (array) –Rows = objects –Columns = object states (properties, attributes)

11. Table Row = object Column = property Table = Object Class Object Classes with Geometry called Feature Classes

12. Relational DBMS Most popular type of DBMS –Over 95% of data in DBMS is in RDBMS Commercial systems –IBM DB2 –Informix –Microsoft Access –Microsoft SQL Server –Oracle –Sybase

13. Spatial Database Example Land parcel with boundary id: 1050

14. Relational Database Example Four tables needed in the land parcel relational database

15. Relational database example #2

17. Relation Rules (Codd, 1970) Only one value in each cell (intersection of row and column) All values in a column are about the same subject Each row is unique No significance in column sequence No significance in row sequence

18. SQL Structured (Standard) Query Language – (pronounced SEQUEL) Developed by IBM in 1970s Now standard for accessing relational databases Three types of usage –Stand alone queries –High level programming –Embedded in other applications (ArcGIS)

19. Types of SQL Statements Data Definition Language (DDL) –Create, alter and delete data –CREATE TABLE, CREATE INDEX Data Manipulation Language (DML) –Retrieve and manipulate data –SELECT, UPDATE, DELETE, INSERT Data Control Languages (DCL) –Control security of data –GRANT, CREATE USER, DROP USER

20. Geometry PointCurveSurface LineString PolygonMultiSurface LineLinearRing MultiCurve MultiPolygonMultiLineString Composed Type Relationship SpatialReferenceSystem GeometryCollection MultiPoint Spatial Types – OGC Simple Features Data Model: A set of constructs for representing objects and processes in a digital environment

21. Spatial Relations Equals – are the geometries the same? Disjoint – do the geometries share common point? Intersects – do the geometries intersect? Touches – do the geometries intersect at their boundaries? Crosses – do the geometries overlap? Within– is one geometry within another? Contains – does one geometry completely contain another? Overlaps – do the geometries overlap? Relate – are their intersections between the interior, boundary or exterior of the geometries?

22. Contains Relation

23. Touches Relation

24. Spatial Methods Distance – determines shortest distance between any two points in two geometries Buffer – returns a geometry that represents all the points whose distance from the geometry is less than or equal to a user-defined distance ConvexHull – returns a geometry representing the small polygon that can enclose another geometry without any concave areas Intersection – returns a geometry that contains just the points common to both input geometries Union – returns a geometry that contains all the points in both input geometries Difference – returns a geometry containing the points that are different between the two geometries SymDifference – returns a geometry containing the points that are in either of the input geometries, but not both

25. Convex Hull and Difference Methods Convex Hull Difference

26. Indexing Used to locate rows quickly Like a book index, it is a special representation of the content that adds order and makes finding items faster RDBMS use simple 1-d indexing Spatial DBMS needs 2-d, hierarchical indexing –Grid –Quadtree –R-tree Multi-level queries often used for performance (MBR)

27. Grid Index (multi-level) - Overlay uniform grid - Assign objects a grid id Multi-level grids are used for variable sized objects within a database

28. Point and Region Quadtree Indexing Based on recursive division of space. Point Quadtree Region Quadtree

29. R-tree Use minimum bounding rectangle (MBR) or minimum bounding box (MBB) Add a new object to the MBR that would expand the least to accommodate the object

30. Study Area Minimum Bounding Rectangle

31. Order Dependence of a Query Query: Select all households within 3 km of a store that have an income greater than $100,000 1. Select all households with an income greater than $100,000; from this selected set, select all households within 3 km of a store 2. Select all households within 3 km of a store; from this selected set, select all households with an income greater than $100,000

32. Distributed Databases www.midcarb.org

33. References Longley et al., Geographic Information Systems and Science, 2001 Chapter 11 Guenther, Environmental Information Systems, 1998 Chapter 3

34. Final Few Weeks Lecture: April 15, Metadata and Interoperability Lab: April 17 (next Thursday), project/problem set work I’ll spend a few minutes with each of you to get an update on your progress. Article review due April 17 Lab: April 22, project lab session. Lecture April 24, GIS in decision-making Project Presentation: May 8