Displaying map data at scales smaller than its source can result in objects that are either too small to be seen or too close to each other to be distinguishable. Furthermore, graphic conflicts become more likely when certain map symbols are no longer a true scale representation of the feature they represent. Map generalisation includes the processes by which such conflicts are resolved. The map generalisation technique presented here is exponential in the problem size and is, as such, combinatorially large (NP-hard). We show how the tabu search metaheuristic was used to resolve spatial conflict between objects after scaling, achieving near optimal solutions within practical time constraints
Map generalization is a procedure involving much intellective reasoning action, with very wide domai...
Maps and their usage have widely evolved recently, to become more and more interactive, multi-scale ...
This article presents the results of integrating large- and medium-scale data into a unified data st...
Displaying map data at scales smaller than its source can result in objects that are either too smal...
The paper deals with automation of cartographic generalization of point features by displacement and...
Abstract: In map generalization various operators are applied to the features of a map in order to m...
Automated map generalization is a difficult, complex and computational very intensive problem. The a...
AbstractThis paper investigates the capabilities of tabu search for solving the global path planning...
Processing massive datasets which are not fitting in the main memory of computer is challenging. Thi...
We describe the main features of tabu search, emphasizing a perspective for guiding a user to unders...
Many automated generalisation methods are based on local search optimisation techniques: Starting fr...
Processing massive datasets which are not fitting in the main memory of computer is challenging. Thi...
In map generalization various operators are applied to the features of a map in order to maintain an...
Cartographic generalisation is the process of simplifying a representation to suit the scale and pur...
International audienceAutomatic map generalization requires the use of computationally intensive pro...
Map generalization is a procedure involving much intellective reasoning action, with very wide domai...
Maps and their usage have widely evolved recently, to become more and more interactive, multi-scale ...
This article presents the results of integrating large- and medium-scale data into a unified data st...
Displaying map data at scales smaller than its source can result in objects that are either too smal...
The paper deals with automation of cartographic generalization of point features by displacement and...
Abstract: In map generalization various operators are applied to the features of a map in order to m...
Automated map generalization is a difficult, complex and computational very intensive problem. The a...
AbstractThis paper investigates the capabilities of tabu search for solving the global path planning...
Processing massive datasets which are not fitting in the main memory of computer is challenging. Thi...
We describe the main features of tabu search, emphasizing a perspective for guiding a user to unders...
Many automated generalisation methods are based on local search optimisation techniques: Starting fr...
Processing massive datasets which are not fitting in the main memory of computer is challenging. Thi...
In map generalization various operators are applied to the features of a map in order to maintain an...
Cartographic generalisation is the process of simplifying a representation to suit the scale and pur...
International audienceAutomatic map generalization requires the use of computationally intensive pro...
Map generalization is a procedure involving much intellective reasoning action, with very wide domai...
Maps and their usage have widely evolved recently, to become more and more interactive, multi-scale ...
This article presents the results of integrating large- and medium-scale data into a unified data st...