Machine learning in cartography

Lars Harrie (1) , Guillaume Touya (2) , Rachid Oucheikh (1) , Tinghua Ai (3) , Azelle Courtial (2) , Kai-Florian Richter (4)

1 Lund University
2 LaSTIG - Laboratoire sciences et technologies de l'information géographique
3 Wuhan University [China]
4 Umeå University, Sweden

Machine learning is increasingly used as a computing paradigm in cartographic research. In this extended editorial, we provide some background of the papers in the CaGIS special issue Machine Learning in Cartography with a special focus on pattern recognition in maps, cartographic generalization, style transfer, and map labeling. In addition, the paper includes a discussion about map encodings for machine learning applications and the possible need for explicit cartographic knowledge and procedural modeling in cartographic machine learning models. Keywords cartography and machine learning and deep learning and pattern recognition and map generalization and style transfer and map labeling

Domains: Computer Science [cs]

Lars Harrie, Guillaume Touya, Rachid Oucheikh, Tinghua Ai, Azelle Courtial, et al.. Machine learning in cartography. Cartography and Geographic Information Science, 2024, 51 (1), pp.1-19. ⟨10.1080/15230406.2023.2295948⟩. ⟨hal-04482556⟩