axes systems ag by axes systems icc 2007, moscow, 5.-10. aug. 2007 icc 2007, moscow, russia...

Axes Systems AG

by Axes Systems

ICC 2007, Moscow, 5.-10. Aug. 2007

ICC 2007, Moscow, Russia

Automated Derivation of a 1:300 000 Topographic Map

from Swiss DLM VECTOR 200

Matthias Bobzien, Axes Systems AGIngo Petzold, University of Zurich

Dirk Burghardt, University of Zurich

by Axes Systems

ICC 2007, Moscow, 5.-10. Aug. 2007 Matthias Bobzien, Axes Systems

Overview

• Context / Introduction• Derivation of DCM300• Perspective: Derivation of DCM25• Conclusion

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Context / Introduction

swisstopo’s project OPTINA-LK

OPTINA-LK

Vector200

DCM 300

Vector200Karto

Generali-sationMRDB

Feasabilitystudy

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OPTINA-LK

Vector200

TLM

DCM 300

Vector200Karto

DCM 25

TLMKarto

Generali-sation

Generali-sationMRDB

MRDB

Feasabilitystudy

RealisationJan´08

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Source Data

DLM VECTOR200• digitized from topographic map 1:200'000• 31 feature classes, 6 topics:

– Transportation– Hydrography– Landcover– Buildings– POI– Boundaries

• Manually thinned for derivation of DCM300

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Source Data

DLM VECTOR200, sample 1 (mountains):

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Source Data

DLM VECTOR200, sample 2 (hills / lake):

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Target Data

DCM300• Digital Cartographic Model for

topographic map 1:300'000• ~40 feature classes (VECTOR200:

31)– Due to more detailed variations, e.g.

line symbolisation of roads

Two major parts of processing:• Reclassification• Cartographic Generalisation

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Reclassification

Reclassification / Model Transformation:

m:n relation

+ Attribute TransformationTransformation Rules, near Prolog Syntaxe.g. road:use:tunnel road:main AND construct == 3

FC

FC

FC

FC

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Reclassification

Rules definition through GUI:

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Cartographic Generalisation

Generalisation Operators used:• Selection

– Through feature size• Displacement

– Mainly between Road/Railway/River– Parameters: Stiffness (e.g. Major Road or

River)– Self-Displacement (e.g. narrow slopes)

• Simplification: Variant of Douglas-Peucker– Topology preservant– Connectivity preservant

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Workflow

Suitable workflow was compiled after a seriesof tests:

1. Model transformation2. De-selection3. Displacement of line features4. Line Simplification5. Area Simplification

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Examples

Sample 1 (mountains): VECTOR200

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Examples

Sample 1 (mountains): DCM300 after MT:

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Examples

Sample 1 (mountains): DCM300 after Gen.

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Examples

Sample 2 (hills / lake): VECTOR200

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Examples

Sample 2 (hills / lake): DCM300 after MT:

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Examples

Sample 2 (hills / lake): DCM300 after Gen.

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Examples

Central Switzerland: DCM300 after Gen.

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OPTINA-LK

Vector200

TLM

DCM 300

Vector200Karto

DCM 25

TLMKarto

Generali-sation

Generali-sationMRDB

MRDB

Feasabilitystudy

RealisationJan´08

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Derivation of DCM25

Source: • Topographic Landscape Model (TLM)• Newly created, currently built up• Only sample data• Basis for maps 1:25K, 1:50K, 1:100KTarget:• Digital Cartographic Model DCM25• Basis for map 1:25K

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Derivation of DCM25

Comparison to DCM300 : • Bigger amount of data• New feature classes (~220)More generalisation operators needed

• Area coverage, to be maintained• Full topology, to be maintained• Need for automated update

mechanism

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Derivation of DCM25

Main components of new system: • Workflow Management• New generalisation operators• Partitioning and Generalisation Zones• Horizontal Relations• Automated Incremental Updating

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Workflow Management

Workflow Editor:– Define workflows graphically

Workflow Engine:– Execute workflow

Characteristics of architecture:– Sequences– Sub-Workflows– Branches, concurrent processes– Loops– Connection to Generalisation Services

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Generalisation operators

New generalisation operators (compared to DCM300), most already implemented:

• Typification / of building alignments• Aggregation• Amalgamation• Merge• Building simplification• Geometry type change• Various special operators

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Partitioning / GenZones

Partitioning: handling of large amount of data

• Trans-Hydro-Graph• Density analysis, e.g. building density

City / residential zone / rural area

• Pre-defined regions• Manual partitioningGeneralisation Zones: Effect on Parameters• Urban / Rural • Alpine / Hilly

data driven

process driven(top-down)

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Horizontal Relations

Allow representation of relationships between features within one resolution

originalsituation

buildingalignments

trans-hydro-graph

topology nearness

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Conclusion

• swisstopo´s OPTINA LK• Derivation of DCM300:

– Feasability study– Accomplished

• Derivation of DCM25– Productive System– Realisation Jan´08

Thank you!

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Incremental Updating

Two Approaches: Re-Generalisation and Construction (see ICC 2005)

a a'

Original data

Updated data

ungener-alised

generalisedb b'

Re-Generalisation

GR GR

UR a a'

b b'

ConstructionGR

UR

UR

Original data

Updated data

Re-Generalisation Construction

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1..*

1..2

0..*

Feature

geometry:Geometryattributes:Collection

object-oriented model

Relation modeling

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1..*

1..2

0..*

Feature


Relation


Relation modeling

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1..*

1..2

0..*

Feature


BinaryRelation

feature1:Featurefeature2:Feature

NAryRelation

features:Collection

Relation

feature1 xor feature2 of an instance of aBinaryRelation can point to a null-object.


Relation modeling

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1..*

1..2

0..*

Feature


BinaryRelation

feature1:Featurefeature2:Feature

NAryRelation

features:Collection

Relation

IntraResolutionRelation

type:IntraResolutionRelationType

InterResolutionRelation

genOperators:CollectionconsideredFeatures:Collection

UpdateRelation

dateInserted:DatesourceOfInformation:String

minusGeometry:GeometryplusGeometry:GeometryattributeChanges:Collection

feature1 xor feature2 of an instance of aBinaryRelation can point to a null-object.


Relation modeling

axes systems ag by axes systems icc 2007, moscow, 5.-10. aug. 2007 icc 2007, moscow, russia...

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