modelling cartographic relations for categorical maps moritz neun and stefan steiniger

XXII International Cartographic Conference, A Coruña, July 9-16th, 2005 1

Modelling Cartographic Relations for Categorical Maps

Moritz Neun and Stefan Steiniger

University of Zürich, Department of Geography

Swiss National Science Foundation Project: DEGEN

{neun, sstein}@geo.unizh.ch


Outline

1. Motivation

2. Introducing Relations

3. Modelling Horizontal & Vertical Relations

4. Outlook


1. Motivation


Thematic (Categorical) Maps

Most research in generalization on topographic maps

majority of maps are of thematic nature (categorical, GIS, facilities, networks, POI ...)

focus on thematic mapswith polygons ina generic approach

Examples: geology, land-use, statistics, administration


Motivation

Generalization should preserve the typical and emphasise specifics.


2. Introducing Relations


What is considered as a relation?


3. Horizontal & Vertical Relations


Horizontal & Vertical Relations

Horizontal relations

of map objects exist within one specific scale or level of detail (LOD) and represent common structural properties.

horizontal relations


Relation Types topologic neighbour

frequency,

area statistics

compactness,

area size, distance

orientation =>

meso structure?

Inter-thematic

structurefor aggregation (are blue

soil classes of same familly?)

=> Semantic similarity

Geometry

Topology

Structure

Statistics and Density

Semantics


Horizontal Relations

Horizontal Relations

geometrical topological structural statistical semantical

position

size

orientation

shape

structure

order of neig-bourhood

9IM

ring

meso structure

background/foreground

macro structure

Inter-thematic

statistical baseparameters

area relations

categoricalrelations

similarity

priority

resistance/ attraction

nature of origin

orientationpatterns

causal and logicrelationsdiversity

metrics

configurationmetrics


Topological Properties

Topologic structure:- Island (in other polygon or background)

- Island cluster- Landscape (complete tesselation)

Ring model relationisland

island cluster

landscape

ring modelwith three levels

Topologic neighbourhood

Nine-Intersection Model (9IM) : e.g. overlap, touch, contain, ...

neigbourhood

l1l2

l3

A 1

2

2

3


Structural Properties

visible patterns gestalt theory meso structures

A proximity groupings

B similarity (size, shape, orientation)

C grouping by type

D parallelism





horizontal relations





horizontal relations vertical relations

1:25k

1:200k

Vertical relations

are links between single map objects or groups of map objects between different map scales and LODs.


vertical relations

map object relations LOD relations

semantic structural

neigbourhoodmatrix

diversity

configuration

similarity

legend

type priorities

causal & logic

identity relation1:1

group relationn:m

simplification

smoothing

enlargement

exaggeration

collapse

aggregation(alignment, cluster)

amalgamation(cluster)

typification(cluster, alignment)

symbolization

displacement

partitioning

(e.g. by alignments)

relations between propertiesof whole LODs

e.g. semantic similarity or type prioritiesfor aggregation


vertical relations


semantic structural

neigbourhoodmatrix

diversity

configuration

similarity

legend

type priorities

causal & logic


group relationn:m

simplification

smoothing

enlargement

exaggeration

collapse




symbolization

displacement

partitioning


relations between single map objects or groups matching and formalisation of thegeometrical, topological and semantical outcomewith abstract generalization operators

abstract procedural knowledge


Vertical Identity Relations 1:1

x


Vertical Identity Relations 1:1

x

A Coruña


Vertical Group Relations n:m


Enrichment of Relations


Vertical Relation Properties

enrich relations with additional information

relation properties

semantic properties geometric properties topological properties

size / position

shape

orientation

neigbourhood

intersection type

structure

statistics

resistance /attraction

configuration(island, landscape)

containment(in, ring model)

change originator

threshold level

type change


4. Outlook


Using Relations

• Improve automated generalisation (horizontal relations)• choice of appropriate algorithms

• more information about parameters for algorithms

• better evaluation of results

• Interpolation of intermediate scale levels

(Cecconi 2003) e.g. in combination with morphing

• Incremental updating of lower detailed LODs (Kilpeläinen

and Sarjakoski 1995)

• Training and use of learning algorithms (inductive, neuronal)

by analyzing relations and properties (Weibel et al. 1995


Thanks for your attention!

Any questions, suggestions or comments?

maps: • Flood hazard map: www.nlfb.de, • China –language region map: www.hphein.de/, • snow depth map: http://www.slf.ch/swiss-snow/hstopodc.html, • soil map „Littau“: IKA, ETHZ, Switzerland


Matching

1:25‘000 1:200‘000


Project DEGEN

Purpose: • data enrichment with relations• modeling of enriched data• exploitation of enriched data

Focus: • thematic vector maps

Goals/Questions: • types of “vertical” relations betweenmap objects on different LODs?

• modelling and representing in a MRDB?• matching of map objects in two LODs and

acquisition relations and their attributes?• management and deployment of relations?• usefulness of vertical relations for the

creation of intermediate LODs?• usefulness of the same relations for

incremental generalization?


Vertical Relationsvertical relations


semantic structural

neigbourhoodmatrix

diversity

configuration

similarity

legend

type priorities

causal & logic


group relationn:m

simplification

smoothing

enlargement

exaggeration

collapse




symbolization

displacement

partitioning


modelling cartographic relations for categorical maps moritz neun and stefan steiniger

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