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GeoAI for map generalization in multi-scale cartography: foundations, a research agenda, and interdisciplinary perspectives

This research investigates how GeoAI can contribute to the map generalization in multi-scale cartography.

Zhiyong Zhou, Cheng Fu, Yu Feng, Guillaume Touya, Monika Sester, Robert Weibel

GeoAI for map generalization in multi-scale cartography: foundations, a research agenda, and interdisciplinary perspectives

SpaGAN: A spatially-aware generative adversarial network for building generalization in image maps

This research proposes a spatially-aware generative adversarial network for building generalization in image maps, SpaGAN. It enhances the capacity to generalize buildings of varying sizes and shapes.

Zhiyong Zhou, Cheng Fu, Robert Weibel

SpaGAN: A spatially-aware generative adversarial network for building generalization in image maps

Reasoning cartographic knowledge in deep learning-based map generalization with explainable AI

This research investigates what cartographic knowledge have been learned by deep learning models in map generalization.

Cheng Fu, Zhiyong Zhou, Robert Weibel

Reasoning cartographic knowledge in deep learning-based map generalization with explainable AI

Move and remove: Multi-task learning for building simplification in vector maps with a graph convolutional neural network

This research proposes a multi-task learning method with graph convolutional neural networks. The proposed method formulates the building simplification problem as a joint task of node removal classification and node movement regression.

Zhiyong Zhou, Cheng Fu, Robert Weibel

Move and remove: Multi-task learning for building simplification in vector maps with a graph convolutional neural network