Revolutionizing earth observation with geospatial foundation models on AWS

This article explores the use of Geospatial Foundation Models (GeoFMs) on AWS for revolutionizing earth observation, with a particular focus on monitoring deforestation in the Amazon rainforest. The solution leverages the Clay foundation model to enable advanced geospatial analytics.

• GeoFMs are transformer-based vision models specifically adapted to geospatial data
• The solution provides three core use cases:
  • Geospatial similarity search
  • Embedding-based change detection
  • Custom geospatial machine learning
• The data processing pipeline includes four key steps:
  • Pre-processing satellite tiles
  • Generating embeddings
  • Processing embeddings
  • Consolidating and indexing data
• Key capabilities include:
  • Finding similar geographic areas using embedding vectors
  • Detecting ecosystem changes over time
  • Fine-tuning models for specific geospatial tasks

The solution demonstrates how geospatial foundation models can provide powerful, flexible tools for environmental monitoring, urban planning, and other earth observation applications.