Work

Geo-Foundation Models: Reality, Gaps and Opportunities

Year: 2023

Type: conference-paper

Abstract: With the recent rapid advances of revolutionary AI models such as ChatGPT, foundation models have become a main topic for the discussion of future AI. Despite the excitement, the success is still limited to specific types of tasks. Particularly, ChatGPT and similar foundation models have unique characteristics that are difficult to replicate for most geospatial tasks. This paper envisions several major challenges and opportunities in the creation of geospatial foundation (geo-foundation) models, as well as potential future adoption scenarios. We also expect that a major success story is necessary for geo-foundation models to take off in the long term.

Source: ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL)

DOI: 10.1145/3589132.3625616

Authors: Yiqun Xie, Zhaonan Wang, Gengchen Mai, Yanhua Li, Xiaowei Jia, Song Gao, Shaowen Wang

Institutions: University of Maryland, College Park, University of Illinois Urbana-Champaign, University of Georgia, Worcester Polytechnic Institute, University of Pittsburgh, University of Wisconsin–Madison

Language: English

Topic: Geographic Information Systems Studies

Subfield: Geography, Planning and Development

Field: Social Sciences

Domain: Social Sciences

Open Access status: hybrid

Funders: National Science Foundation, National Aeronautics and Space Administration, University of Pittsburgh, Nuclear Safety and Security Commission, U.S. Geological Survey

Awards: G1242460129, G3198493938, HDR Institute: Geospatial Understanding through an Integrative Discovery Environment, FAI: Advancing Deep Learning Towards Spatial Fairness, CRII: III: Discovering Complex Mixture Patterns in Spatial Data to Advance Resilience of Communities, G7002138997, Collaborative Research: EarthCube Capabilities: ICESpark: An Open-Source Big Data Platform for Science Discoveries in the New Arctic and Beyond

OpenAlex ID: W4390100389

FWCI: 68.3

Cites: 10

Cited by: 31

Related to: 10