Gis Ii Midterm

Front 1

Levels of Data Model Abstraction

Back 1

Reality
Conceptual Model
Logical Mode
Physical

Front 2

Advantages of topological model(4)

Back 2

Requires all lines be connected, polygons closed, loose ends removed
Avoids such problems as overlapping polygons, dangling lines, polygon slivers
Allows efficient editing
Allows advanced spatial analysis: network, connectivity, contiguity

Front 3

Network Model

Back 3

Special type of vector topological model
Lines connect points
Topology define connections, direction

Front 4

Triangulated Irregular Network

Back 4

Topological vector model: allows 3D and surface representation
Represents surface as a combination of non-overlapping triangles

Front 5

Georelational Data Model

Back 5

The georelational data model stores spatial and attribute data separately in a split system: spatial data (“geo”) in graphic files and attribute data (“relational”) in a relational database
Uses feature label or ID to link the two
Utilizes RDBMS – relational database management systems for attribute storage
Coverages, shapefiles

Front 6

Object Based Data Model

Back 6

The object-based data model treats spatial data as objects. An object can represent a spatial feature such as a road, a timber stand, or a hydrologic unit.
The object-based data model stores both the spatial and attribute data of spatial features in a single system.
All objects are related via relationships (topological, geographical, general)
Each object has a set of properties (=state) and behaviors (=methods)
Object properties and behaviors may be constrained by rules
Groups of objects with identical properties and behaviors form class (feature class in geodatabase)

Front 7

Georelational v Object Based

Back 7

Spatial and attribute stored separately
Geographic information and attribute table (relational database)
Shapefile, coverage

Spatial and attribute in a single system
Allows an object to be associated with properties and methods
Geodatabase

Front 8

Advantages of Databases over files

Back 8

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

Front 9

Disadvantages of Databases over files

Back 9

Expense
Complexity
Performance – especially complex data types
Integration with other systems can be difficult

Front 10

Types of Databases

Back 10

Flat file – all data in one file
Hierarchical, Network
Relational – RDB – collection of interrelated tables that can be connected to each other by keys
Object-oriented - OODB
Object-relational - ORDB

Front 11

Characteristics of Databases

Back 11

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
DBA tools
Configuration, tuning

Front 12

Relational Databases

Back 12

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)
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

Front 13

Geographic DBMS reqs

Back 13

Query parser: interprets SQL, extends to geographic types and functions
Query optimizer
Query language is able to handle geographic types (points, polygons, etc.) and functions (e.g., select adjacent)
Indexing can support multidimentional geographic data types

Front 14

Indexing

Back 14

Used to locate rows quickly
RDBMS use simple 1-d indexing (R-tree, B-tree, etc.)
Spatial DBMS need 2-d, hierarchical indexing
Grid
Quadtree
R-tree
Others
Multi-level queries often used for performance (MBR)