Location and AI — academy.ogc.org: Difference between revisions
From wikiluntti
| Line 14: | Line 14: | ||
AI → Machine learning → Deep learning → Generative AI → LLM. | AI → Machine learning → Deep learning → Generative AI → LLM. | ||
* Supervised learning works with labeled datasets | |||
== 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 11:19, 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.
- Supervised learning works with labeled datasets
