Abstract
Owing to map scale reduction and other cartographic generalization operations, spatial conflicts may occur between buildings and other features in automatic cartographic generalization. Displacement is an effective map generalization operation to resolve these spatial conflicts to guarantee map clarity and legibility. In this paper, a novel building displacement method based on multipopulation genetic algorithm (BDMPGA) is proposed to resolve spatial conflicts. This approach introduces multiple populations with different control parameters for simultaneous search optimization and adopts an immigration operation to connect different populations to realize coevolution. The optimal individuals of each population are selected and preserved in the elite population through manual selection operation to prevent the optimal individuals from being destroyed and lost in the evolutionary process. Meanwhile, the least preserving generation of the optimal individuals is used as the termination basis. To validate the proposed method, urban building data with a scale of 1:10,000 from Shenzhen, China are used. The experimental results indicate that the method proposed in this paper can effectively resolve spatial conflicts to obtain better results.
Highlights
In automatic cartographic generalization, spatial conflicts often occur between both the same and different features because of map scale reduction and other cartographic generalization operations
We propose a novel building displacement method based on multipopulation genetic algorithm (BDMPGA) to resolve spatial conflicts
A novel building displacement method based on multipopulation genetic algorithm (BDMPGA) is proposed to resolve spatial conflicts, which improves the deficiencies of the traditional GA and immune genetic algorithm (IGA)
Summary
Spatial conflicts (e.g., proximity conflicts or overlap conflicts) often occur between both the same and different features (e.g., between buildings and buildings or between buildings and roads) because of map scale reduction and other cartographic generalization operations. We propose a novel building displacement method based on multipopulation genetic algorithm (BDMPGA) to resolve spatial conflicts. The immigration operation is used to realize the information exchange among different populations to maintain the diversity of individuals in the population and obtain the optimal solution. This method adopts elite retention strategy that the optimal individuals in the population are selected and preserved in the elite population through manual selection operation, and the elite population is the basis for the termination of the algorithm.
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