A roadmap for generative mapping: unlocking the power of generative AI for map-making
Sidi Wu, Katharina Henggeler, Yizi Chen, Lorenz Hurni

TL;DR
This paper explores how generative AI can revolutionize map-making by making it more accessible, outlining key applications, recent advancements, challenges, and a roadmap for developing a generative mapping system.
Contribution
It provides a comprehensive roadmap for integrating generative AI into map-making, addressing current limitations and proposing future development directions.
Findings
Generative AI has significant potential to democratize map-making.
Current methods face technological and workflow challenges.
A strategic roadmap is proposed for developing generative mapping systems.
Abstract
Maps are broadly relevant across various fields, serving as valuable tools for presenting spatial phenomena and communicating spatial knowledge. However, map-making is still largely confined to those with expertise in GIS and cartography due to the specialized software and complex workflow involved, from data processing to visualization. While generative AI has recently demonstrated its remarkable capability in creating various types of content and its wide accessibility to the general public, its potential in generating maps is yet to be fully realized. This paper highlights the key applications of generative AI in map-making, summarizes recent advancements in generative AI, identifies the specific technologies required and the challenges of using current methods, and provides a roadmap for developing a generative mapping system (GMS) to make map-making more accessible.
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Taxonomy
TopicsGeographic Information Systems Studies
