Location and AI — academy.ogc.org: Difference between revisions

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== AI and Geospatial Data ==
== AI and Geospatial Data ==
AI → Machine learning → Deep learning → Generative AI → LLM.


== Geospatial Applications of AI: Enhancing Analysis Through Images, Sensor Data and 3D Tools ==
== Geospatial Applications of AI: Enhancing Analysis Through Images, Sensor Data and 3D Tools ==

Revision as of 11:05, 17 June 2025

Introduction

AI is helping to automate tasks, improve efficiency, and streamline operations. It is particularly useful for tasks involving large amounts of data and data analysis, and in high-dimensional spaces.

Eg

  • analyze traffic patterns and optimize public transport routes.
  • monitors crop health, predicts yields
  • changes in land use, deforestation, and habitat loss
  • to optimize the placement of renewable energy sources
  • autonomous boats to collect trash from the seas

AI and Geospatial Data

AI → Machine learning → Deep learning → Generative AI → LLM.

Geospatial Applications of AI: Enhancing Analysis Through Images, Sensor Data and 3D Tools

Trust, Risks and Regulation in Geospatial AI

GeoAI Skillbase and Tips for the future

Summary