Chapters 9 and 10, Longley et al.

Data Bases: Population and Maintenance

Geog 176B Lecture 8

Data Collection

One of most expensive GIS activitiesMany diverse sources (source integration, data fusion, interoperability)Two broad types of collection

Data capture (direct collection)Data transfer

Two broad capture methodsPrimary (direct measurement)Secondary (indirect derivation)

Stages in Data Collection Projects

Planning

Preparation

Digitizing / TransferEditing / Improvement

Evaluation

Data Collection Techniques

Raster VectorPrimary Digital remote

sensing imagesGPS measurements

Digital aerial photographs

Survey measurements

Secondary Scanned maps Topographic surveys

DEMs from maps

Toponymy data sets from atlases

Primary Data Capture

Capture specifically for GIS useRaster – remote sensing

e.g. SPOT and IKONOS satellites and aerial photographyPassive and active sensors

Resolution is key considerationSpatialSpectralTemporal

www.spot.ucsb.edu

Imagery for GIS

Vector Primary Data Capture

SurveyingLocations of objects determines by angle and distance measurements from known locationsUses expensive field equipment and crewsMost accurate method for large scale, small areas

GPSCollection of satellites used to fix locations on Earth’s surfaceDifferential GPS used to improve accuracy

Total Station

Pen/Portable PC and GPS

Secondary Geographic Data Capture

Data collected for other purposes can be converted for use in GISRaster conversion

Scanning of maps, aerial photographs, documents, etcImportant scanning parameters are spatial and spectral (bit depth) resolution

Scanner

Raster to vector conversion

Vector Secondary Data Capture

Collection of vector objects from maps, photographs, plans, etc.Digitizing

Manual (table) Heads-up and vectorization

Photogrammetry – the science and technology of making measurements from photographs, etc.

Digitizer

Data Transfer

Buy vs. build is an important questionMany widely distributed sources of GIIncludes geocodingKey catalogs include

Geodata.govGeography Network

Access technologiesTranslationDirect read

Managing Data Capture ProjectsKey principles

Clear plan, adequate resources, appropriate funding, and sufficient time

Fundamental tradeoff among Quality, accuracy, speed and price

Two strategiesIncremental‘Blitzkrieg’

Alternative resource optionsIn houseSpecialist external agency

Map scale Ground distance corresponding to 0.5 mm map distance

1:1250 62.5 cm

1:2500 1.25 m

1:5000 2.5 m

1:10,000 5 m

1:24,000 12 m

1:50,000 25 m

1:100,000 50 m

1:250,000 125 m

1:1,000,000 500 m

1:10,000,000 5 km

A useful rule of thumb is that positions measured from maps are accurate to about 0.5 mm on the map. Multiplying this by the

scale of the map gives the corresponding distance on the ground.

Positional Accuracy (cont.)within a database a typical 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 mapuse precision GPS

Use internal evidence:digitized polygons that are unclosed, lines that overshoot or undershoot nodes, etc. are indications of errorsizes of gaps, overshoots, etc. may be a measure of positional accuracy

Testing Accuracy (cont.)Compute accuracy from knowledge of the errors introduced by different sourcese.g., 1 mm in source document0.5 mm in map registration for digitizing0.2 mm in digitizingif sources combine independently, we can get an estimate of overall accuracy...

(12 + 0.52 + 0.22) 0.5 = 1.14 mm

Definitions

Database – an integrated set of data (attributes) on a particular subjectGeographic (=spatial) database - database containing geographic data of a particular subject for a particular areaDatabase Management System (DBMS) – software to create, maintain and access databases

A GIS links attribute and spatial data

Attribute Data• Flat File• Relations

Map Data• Point File• Line File• Area File• Topology• Theme

Advantages of Databases over Files

Avoids redundancy and duplicationReduces data maintenance costsFaster for large datasetsApplications are separated from the data

Applications persist over timeSupport multiple concurrent applications

Better data sharingSecurity and standards can be defined and enforced

Disadvantages of Databases over Files

ExpenseComplexityPerformance – especially complex data typesIntegration with other systems can be difficult

Types of DBMS Model

HierarchicalNetworkRelational - RDBMSObject-oriented - OODBMSObject-relational - ORDBMS

Relational Databases rule now

Characteristics of DBMS (1)

Data model support for multiple data types

e.g MS Access: Text, Memo, Number, Date/Time, Currency, AutoNumber, Yes/No, OLE Object (MS Object linking and embedding), Hyperlink, Lookup Wizard

Load data from files, databases and other applicationsIndex for rapid retrieval

Characteristics of DBMS (2)

Query language – SQLSecurity – controlled access to data

Multi-level groups (e.g. census, NGA)

Controlled update using a transaction managerVersioningBackup and recovery

Characteristics of DBMS (3)

ApplicationsForms builderReportwriterInternet Application ServerCASE tools

Programmable API (Applications program interface)

Geographic Information

System

Database Management

System

• Data load• Editing• Visualization• Mapping• Analysis

• Storage• Indexing• Security• Query

Data

System TaskRole of DBMS

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 systemsIBM DB2InformixMicrosoft AccessMicrosoft SQL ServerOracleSybase

SQL

Structured (Standard) Query Language – (pronounced SEQUEL)Developed by IBM in 1970sNow de facto and de jure 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

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

JoinRecord ID

Address

#cars

1241 123 State St. 3

1242 1801 Main St. 1

1243 2106 Elm St. 2

1244 7262 Pine Drive 1

1241 Ford 2003

1241 Subaru 2000

1241 Honda 1999

1241 123 State St.

Ford

1241 123 State St.

Subaru

1241 123 State St.

Honda

1242 1801 Elm St.

Kia

Spatial indexing

Many maps tiledB-tree (Balanced) Grid indexingQuad tree: Points/regionsR-tree (Based on MBR)

New global/spatial grids: QTM

Go2 Grids38:53:22.08N 077:02:06.86WUS.DC.WAS.54.18.28.83.11US.CA.SBA.UCSB.UCEN

Spatial Search: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.