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The Role of ErrorMap and attribute data errors are the data producer's responsibility,
GIS user must understand error.Accuracy and precision of map and attribute data in a GIS affect all other operations, especially when maps are compared across scales.
Accuracycloseness to TRUE values
results, computations, or estimates
compromise on “infinite complexity”
generalization of the real worlddifficult to identify a TRUE value
e.g., accuracy of a contourDoes not exist in real worldCompare to other sources
Accuracy (cont.)accuracy of the database = accuracy of the products computed from databasee.g., accuracy of a slope, aspect, or watershed computed from a DEM
Positional Accuracytypical UTM coordinate pair might be:Easting 579124.349 mNorthing 5194732.247 mIf the database was digitized from a 1:24,000 map sheet, the last four digits in each coordinate (units, tenths, hundredths, thousandths) would be questionable
Testing Positional AccuracyUse an independent source of higher accuracy:
find a larger scale map (cartographically speaking)
use GPS
Use internal evidence:digitized polygons that are unclosed, lines that overshoot or undershoot nodes, etc. are indications of inaccuracysizes of gaps, overshoots, etc. may be a measure of positional accuracy
not the same as accuracy!repeatability vs. “truth”not closeness of results, but number of decimal places or significant digits in a measurement A GIS works at high precision, usually much higher than the accuracy of the data themselves
Precision
Accuracy vs. Precision
High AccuracyLow Precision
Low AccuracyHigh Precision
Many darts in reproduceable clusters, but not in the bullseye.
Darts are near the bullseye (the "true value"), but there aren't very many clusters of them (not reproduceable).
Accuracy vs. Precision
High AccuracyLow Precision
Low AccuracyHigh Precision
Many darts in reproduceable clusters, but not in the bullseye.
Darts are near the bullseye (the "true value"), but there aren't very many clusters of them (not reproduceable).
Components of Data Quality
positional accuracyattribute accuracylogical consistencycompletenesslineage
Lecture 10Geographic Databases
Gateway to Spatial Analysis
Chapter 10 up to 10.4, Longley et al.
Definitions
Database – an integrated set of attributes on a particular subjectGeographic (=geospatial) database – set of attributes on a particular subject for a particular geographic areaDatabase Management System (DBMS) – software to create, maintain and access databases
A GIS can answer the question: What is where?
WHAT: Characteristics of features (= attributes).WHERE: In geographic space.
A GIS links attribute and spatial data
Attribute Data• Flat File or
DBMS• Relationships• Topology Table
Map Data• Point File• Line File• Area File• Topology Type
Flat File or DBMS
Record Value Value Value
Attribute Attribute Attribute
Record Value Value Value
Record Value Value Value
Types of DBMS Models
HierarchicalNetworkRelational - RDBMSObject-oriented - OODBMSObject-relational - ORDBMS
Historically, databases were structured hierarchically in flat files...
Relational Databases rule now
2/1/98 2/4/98
Geographic Information
System
Database Management
System
• Data loading• Editing• Visualization• Mapping• Analysis
• Storage• Indexing• Security• Query
Data
System TaskRole of DBMS
“Programmable API”
Relational DBMS (1)
Data stored as tuples (tup-el), conceptualized as tablesTable – data about a class of objects
Two-dimensional list (array)Rows = objectsColumns = object states (properties, attributes)
Table
Row = objectVector feature
Column = attribute
Relational DBMS (2)
Most popular type of DBMSOver 95% of data in DBMS is in RDBMS
Commercial systemsMicrosoft AccessMicrosoft SQL ServerOracleIBM DB2InformixSybase
Relational Join
Fundamental query operationOccurs because
Data created/maintained by different users, but integration needed for queries
Table joins use common keys (column values)Table (attribute) join concept has been extended to geographic case
Relational Databases
2/1/98 2/4/98
Parts of GIS database tables for U.S states (A) STATES table; (B) POPULATION table
Parts of GIS database tables for U.S states(C) joined table—COMBINED STATES and POPULATION
Tax assessment database
(D) joined table
(C) data partially normalized into three subtables
SQL
Structured (Standard) Query Language – (pronounced SEQUEL)Developed by IBM in 1970s
• Standard for accessing relational databasesThree types of usage
Stand alone queriesHigh level programmingEmbedded in other applications
Types of SQL Statements
Data Definition Language (DDL)Create, alter and delete dataCREATE TABLE, CREATE INDEX
Data Manipulation Language (DML)Retrieve and manipulate dataSELECT, UPDATE, DELETE, INSERT
Data Control Languages (DCL)Control security of dataGRANT, CREATE USER, DROP USER
Spatial Query/Search & Retrieval:Gateway to Spatial Analysis
Overlay is a spatial retrieval operation that is equivalent to an attribute join. Buffering is a spatial retrieval around points, lines, or areas based on distance.
Overlay
Image courtesy of K. Foote/M. Lynch, UT-Austin
Overlay like an attribute join
2/1/98 2/4/98
Types of overlay operations
UnionIntersectIdentityMaxMin
Etc.
Unioncomputes the geometric intersection of two polygon coverages. All polygons from both coverages will be split at their intersections and preserved in the output coverage.
Union
within 25 miles of a city OR within
25 miles of a major river.
Intersectcomputes the geometric intersection of two coverages. Only those features in the area common to both coverages will be preserved in the output coverage.
Intersect
within 25 miles of a city AND within
25 miles of a major river.
Identitycomputes the geometric intersection of two coverages. All features of the input coverage, as well as those features of the identity coverage that overlap the input coverage, are preserved in the output coverage.
Identity
within 25 miles of a city OR within 25 miles of a major river. within 25 miles of a city AND within 25 miles of a major river.
Portion of the major city buffer WITHIN the major river buffer
Union Intersect
Identity
Intersect
Raster Retrieval: Map AlgebraRaster overlayCombinations of spatial and attribute
queries can build some complex and powerful GIS operations.
Comparedwith
Input Grid A Input Grid B Output Grid C
Buffer
RecodeOR
And many more ….See spatial analysis handout on
course web site.