2 papers
cs.CV2025
Leveraging AI multimodal geospatial foundation models for improved near-real-time flood mapping at a global scale
Mirela G. Tulbure, Julio Caineta, Mark Broich +6
Floods are among the most damaging weather-related hazards, and in 2024, the warmest year on record, extreme flood events affected communities across five continents. Earth observa…
cs.CV2024
Multi-Modal Vision Transformers for Crop Mapping from Satellite Image Time Series
Theresa Follath, David Mickisch, Jan Hemmerling +3
Using images acquired by different satellite sensors has shown to improve classification performance in the framework of crop mapping from satellite image time series (SITS). Exist…