A Knowledge Based Genetic Algorithm Approach to Automating Cartographic Generalisation

J. M. Ware; Ian D. Wilson; Andrew Ware

doi:10.1007/978-1-4471-0649-4_3

A Knowledge Based Genetic Algorithm Approach to Automating Cartographic Generalisation

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Pennod › adolygiad gan gymheiriaid

Crynodeb

Rendering map data at scales smaller than their source can give rise to map displays exhibiting graphic conflict, such that objects are either too small to be seen or too close to each other to be distinguishable. Furthermore, scale reduction will often require important features to be exaggerated in size, sometimes leading to overlapping features. Cartographic Map generalisation
is the process by which any graphic conflict that arises during scaling is resolved. In this paper, we show how a Genetic Algorithm approach was used to resolve spatial conflict between objects after scaling, achieving near optimal solutions within practical time constraints.

Iaith wreiddiol	Saesneg
Teitl	Applications and Innovations in Intelligent Systems X
Cyhoeddwr	Springer
Tudalennau	33-49
Nifer y tudalennau	17
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1007/978-1-4471-0649-4_3
Statws	Cyhoeddwyd - 2003

Mynediad at Ddogfen

10.1007/978-1-4471-0649-4_3

Dyfynnu hyn

@inbook{4c7a702f3b6e484c81c648e5a2e9e0b0,

title = "A Knowledge Based Genetic Algorithm Approach to Automating Cartographic Generalisation",

abstract = "Rendering map data at scales smaller than their source can give rise to map displays exhibiting graphic conflict, such that objects are either too small to be seen or too close to each other to be distinguishable. Furthermore, scale reduction will often require important features to be exaggerated in size, sometimes leading to overlapping features. Cartographic Map generalisationis the process by which any graphic conflict that arises during scaling is resolved. In this paper, we show how a Genetic Algorithm approach was used to resolve spatial conflict between objects after scaling, achieving near optimal solutions within practical time constraints. ",

author = "Ware, {J. M.} and Wilson, {Ian D.} and Andrew Ware",

year = "2003",

doi = "10.1007/978-1-4471-0649-4_3",

language = "English",

pages = "33--49",

booktitle = "Applications and Innovations in Intelligent Systems X",

publisher = "Springer",

address = "Germany",

}

TY - CHAP

T1 - A Knowledge Based Genetic Algorithm Approach to Automating Cartographic Generalisation

AU - Ware, J. M.

AU - Wilson, Ian D.

AU - Ware, Andrew

PY - 2003

Y1 - 2003

N2 - Rendering map data at scales smaller than their source can give rise to map displays exhibiting graphic conflict, such that objects are either too small to be seen or too close to each other to be distinguishable. Furthermore, scale reduction will often require important features to be exaggerated in size, sometimes leading to overlapping features. Cartographic Map generalisationis the process by which any graphic conflict that arises during scaling is resolved. In this paper, we show how a Genetic Algorithm approach was used to resolve spatial conflict between objects after scaling, achieving near optimal solutions within practical time constraints.

AB - Rendering map data at scales smaller than their source can give rise to map displays exhibiting graphic conflict, such that objects are either too small to be seen or too close to each other to be distinguishable. Furthermore, scale reduction will often require important features to be exaggerated in size, sometimes leading to overlapping features. Cartographic Map generalisationis the process by which any graphic conflict that arises during scaling is resolved. In this paper, we show how a Genetic Algorithm approach was used to resolve spatial conflict between objects after scaling, achieving near optimal solutions within practical time constraints.

U2 - 10.1007/978-1-4471-0649-4_3

DO - 10.1007/978-1-4471-0649-4_3

M3 - Chapter

SP - 33

EP - 49

BT - Applications and Innovations in Intelligent Systems X

PB - Springer

ER -

A Knowledge Based Genetic Algorithm Approach to Automating Cartographic Generalisation

Crynodeb

Mynediad at Ddogfen

Ôl bys

Dyfynnu hyn