The generative revolution: AI foundation models in geospatial health-applications, challenges and future research.

Journal: International journal of health geographics
PMID:

Abstract

In an era of rapid technological advancements, generative artificial intelligence and foundation models are reshaping industries and offering new advanced solutions in a wide range of scientific areas, particularly in public and environmental health. However, foundation models have previously mostly focused on understanding and generating text, while geospatial features, interrelations, flows and correlations have been neglected. Thus, this paper outlines the importance of research into Geospatial Foundation Models, which have the potential to revolutionise digital health surveillance and public health. We examine the latest advances, opportunities, challenges, and ethical considerations of geospatial foundation models for research and applications in digital health. We focus on the specific challenges of integrating geospatial context with foundation models and lay out the future potential for multimodal geospatial foundation models for a variety of research avenues in digital health surveillance and health assessment.

Authors

  • Bernd Resch
    Department of Geoinformatics-Z_GIS, University of Salzburg, 5020 Salzburg, Austria.
  • Polychronis Kolokoussis
    School of Rural, Surveying & Geoinformatics Engineering, National Technical University of Athens, 15780, Athens, Greece.
  • David Hanny
    IT:U Interdisciplinary Transformation University, 4040, Linz, Austria.
  • Maria Antonia Brovelli
    Department of Civil and Environmental Engineering, Politecnico Di Milano, 20133, Milan, Italy.
  • Maged N Kamel Boulos
    School of Information Management, Sun Yat-sen University, East Campus, Guangzhou, 510006, Guangdong, China. mnkboulos@mail.sysu.edu.cn.