GeoAI - Accelerating a virtuous cycle between AI and Geo

Lokendra P.S. Chauhan, Shashi Shekhar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Geospatial artificial intelligence (GeoAI) is the amalgamation of artificial intelligence (AI) with spatial computing to develop a better understanding of the physical world around us at the levels of an individual, communities, cities, nations, and the planet using geospatial data. The current applications of GeoAI vary from solving challenges in the fields of sustainable development, urban planning, supply chains, and navigation to defense, epidemiology, insurance, and the emerging on-demand economy. It is a highly interdisciplinary field that uses ideas from computing, geography, spatial data science, statistics, and engineering. The unique features of geospatial data like autocorrelation, geometric nature, and multiple modalities requires the AI algorithms to be developed in a fundamentally different way, which also expands the capabilities of AI in general. Considering the exponential increasing geospatial data and application, this confluence of AI and geospatial will become a virtuous cycle of growth for both AI and Geo.

Original languageEnglish (US)
Title of host publication2021 13th International Conference on Contemporary Computing, IC3 2021
PublisherAssociation for Computing Machinery
Pages355-370
Number of pages16
ISBN (Electronic)9781450389204
DOIs
StatePublished - Aug 5 2021
Event13th International Conference on Contemporary Computing, IC3 2021 - Virtual, Online, India
Duration: Aug 5 2021Aug 7 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference13th International Conference on Contemporary Computing, IC3 2021
Country/TerritoryIndia
CityVirtual, Online
Period8/5/218/7/21

Bibliographical note

Funding Information:
This work was supported by National Science Foundation (1737633, 1901099, 1916518 and 2040459), and USDA (2017-51181-27222). We would like to express our gratitude to Kim Koffolt from the spatial computing group at the University of Minnesota for her helpful comments and refinements that significantly improved the readability of this article. We would also like to thank World Geospatial Industry Council (WGIC) for a variety of contributions through their report on AI/ML applications and policies for geospatial industry.

Publisher Copyright:
© 2021 Association for Computing Machinery. All rights reserved.

Keywords

  • Artificial Intelligence
  • Embodied Intelligence
  • GeoAI
  • Geospatial
  • GIS
  • Remote Sensing
  • Spatial
  • Sustainable Development

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