COMPUTERS AND COMPUTERS AND STATISTICS IN STATISTICS IN

ARCHAEOLOGYARCHAEOLOGY

Week 4. Geographic Week 4. Geographic Information Systems (GIS) - 2Information Systems (GIS) - 2

© Richard Haddlesey www.medievalarchitecture.net

Aims WEEK 4 Examine the differences between vector and raster graphics Discuss which data types are best represented by each Examine how ArcGIS treats vector graphics Outline vector data sources Create new vector themes by digitising in ArcGIS

WEEK 5 Discuss the use of photography and satellite date in GIS Outline raster data sources Load and geo-reference aerial photographs in ArcGIS Examine different display options when using raster images in ArcGIS

Key textKey text Conolly J, Lake M 2006.Conolly J, Lake M 2006. Geographical Information Systems in Geographical Information Systems in

Archaeology: Cambridge Manuals in Archaeology. Archaeology: Cambridge Manuals in Archaeology. Cambridge Cambridge University Press. CambridgeUniversity Press. Cambridge

Geographical Information Systems are a powerful Geographical Information Systems are a powerful technology that offer a host of analytical possibilities technology that offer a host of analytical possibilities for investigating the spatial organisation of cultural for investigating the spatial organisation of cultural and human-environment relationshipsand human-environment relationships (p31) (p31)

Data modelsData models

Data models and data structures: Data models and data structures: [are] the digital representation of [are] the digital representation of spatial phenomenaspatial phenomena

A GIS works by manipulating the A GIS works by manipulating the digital representations of real world digital representations of real world entities…[this is known as a] entities…[this is known as a]

data modeldata model

(Conolly and Lake, 2006: 24)(Conolly and Lake, 2006: 24)

Two main types of Data models in GIS

Vector– Objects represented as nodes (X,Y points)

and connecting lines, attributes of objects attached as database tables

Raster– Geographical space represented as a grid of

cells, numerical values represent attributes of each cell

Vector and Raster GISVector and Raster GIS

Forest Lake Grassland

Vector Raster

RoadSite

StrengthsStrengths

Vector Spatial precision Compact data storage Scalable presentation Object based Database linkage

Raster Analytical capabilities Surfaces Continuous quantities Pixellated data Photographs

Vector applicationsVector applications

Spatially referenced database applications (information about objects):• Location maps• Sites and Monuments• Artefacts

Mapping applications Triangulated Irregular Network (TIN)

elevation models

Vector applicationsVector applications

Downside:• Very CPU intensive• Boundedness• Elevation is hard to express without a

TIN

Raster applicationsRaster applications

Each cell can be given:Each cell can be given:• A quantitative value that signals the mean A quantitative value that signals the mean

elevationelevation• a single attributea single attribute

This is simple, in comparison to a vector, This is simple, in comparison to a vector, but that is it’s strength:but that is it’s strength:• It can be mathematically manipulated and It can be mathematically manipulated and

displayed much quicker than a vectordisplayed much quicker than a vector Fuzzy boundariesFuzzy boundaries Map algebraMap algebra

(Conolly and Lake, 2006: 28)(Conolly and Lake, 2006: 28)

Raster applicationsRaster applications

Downside:Downside:• Fixed resolution (not multiscalar)Fixed resolution (not multiscalar)• It’s difficulty in representing discrete It’s difficulty in representing discrete

entities (too blocky)entities (too blocky)• Limited ability to handle multiple Limited ability to handle multiple

attribute data through a DBMSattribute data through a DBMS

(Conolly and Lake, 2006: 30-1)(Conolly and Lake, 2006: 30-1)

The good news: Hybridisation

Vector/raster systems Most modern GIS software packages combine both

vector and raster capabilities

Image processing Aerial and satellite integration

ESRI desktop GIS suite ArcView

ArcCatalog and ArcMap

The good news: HybridisationThe good news: Hybridisation Vector/raster systems

Most modern GIS software packages combine both vector and raster capabilities

Image processing• Aerial and satellite integration• DBMS integration

ESRI desktop GIS suite (www.esri.com)• Arc Info • ArcEditor• ArcView

ArcCatalog and ArcMap• ArcReader• ArcGIS extensions

Hybridisation through layers in Hybridisation through layers in ArcViewArcView

MSc lecture notes 2005/6

Software CAD/CAM

• AutoCAD, Microstation Image processing

• MicroBrain, ERDAS Imagine Raster GIS

• Idrisi, Grass (Unix), Grassland, Spans, MapII (Mac)

Vector GIS• ArcInfo, ArcGIS, MGE

Desktop mapping• ArcView ≤3, MapInfo

Map objects

Point

Line/Polyline

Area/Region/Polygon

Text ABC

Database linkageMap objects = attributes

Most mapping applications are intimately linked with a database of objects:

• Territories

• Historical records

• Sites

• Museum objects

• Features

• Excavated/collected artefacts

Mapping to Database

Attributes

Graphical objects

Layers / themes

Why themes? Logical breakdown of data - related

objects in each theme Assemble maps for different purposes

by combining themes Examine interaction between themes,

create new themesPaper maps use symbolism to distinguish between layers, to compensate for the limitations of the technology

Data collection (1)

Conventional databases• Point data

• Attributes for line & area objects

Digital vector data sources• Geographically referenced

– Worldwide, DCW

– BGS

– National (e.g. Ordnance Survey)

– Other e.g. Developers plans etc

• Drafting / surveyors’ plans (DXF)

Data collection (2)

Map digitising Considerations:

• Accuracy, costs, heads-up/down

• Projection, geodetic system, topology

• Topographic / projected

• Plans / unprojected

• Historical maps & plans

Data collection (3) EDM, GPS & conventional survey

• Architectural survey Field survey & recording

• Sites• Survey units / material count• Individual artefact locations

Surface collection Excavation

– Units & features as objects– 3D / volumetric systems / voxels

• Vastly increased data requirements– Artefacts