Research Paper#Remote Sensing, Foundation Models, Scaling, Vision Transformers🔬 ResearchAnalyzed: Jan 3, 2026 15:59
Scaling Remote Sensing Foundation Models: Data-Driven Insights
Published:Dec 29, 2025 23:53
•1 min read
•ArXiv
Analysis
This paper addresses the critical challenge of scaling foundation models for remote sensing, a domain with limited data compared to natural images. It investigates the scaling behavior of vision transformers using a massive dataset of commercial satellite imagery. The findings provide valuable insights into data-collection strategies and compute budgets for future development of large-scale remote sensing models, particularly highlighting the data-limited regime.
Key Takeaways
- •Explores scaling behaviors of vision transformers on petascale remote sensing data.
- •Identifies a data-limited regime, suggesting data collection is more critical than model size.
- •Provides practical insights for data collection, compute budgets, and optimization schedules for future RS foundation models.
Reference
“Performance is consistent with a data limited regime rather than a model parameter-limited one.”