Construction of an Emotion-Oriented Color Scheme Model for Maps

The model applies manifold learning to reduce the dimensionality of high-dimensional map color data derived from the Map Emotion Dataset, thereby extracting emotional color manifold features, then emotional color constraints for maps on color feature indicators was introduced to genetic algorithm framework to generate color schemes that align with the thematic and emotional requirements of maps. This model offers a structured framework for enhancing the emotional expressiveness of cartographic products while maintaining consistency with established color design principles.