Machine learning in cartography

Lars Harrie, Guillaume Touya, Rachid Oucheikh, Tinghua Ai, Azelle Courtial, Kai Florian Richter

Research output: Contribution to journalDebate/Note/Editorialpeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)1-19
Number of pages19
JournalCartography and Geographic Information Science
Volume51
Issue number1
DOIs
Publication statusPublished - 2024

Subject classification (UKÄ)

  • Other Computer and Information Science

Free keywords

  • Cartography
  • deep learning
  • machine learning
  • map generalization
  • map labeling
  • pattern recognition
  • style transfer

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