1 citations · 1 across the 2 of their papers we have counts for
3 papers
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…
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…
Taking it further: leveraging pseudo labels for field delineation across label-scarce smallholder regions
Philippe Rufin, Sherrie Wang, Sá Nogueira Lisboa +3
Transfer learning allows for resource-efficient geographic transfer of pre-trained field delineation models. However, the scarcity of labeled data for complex and dynamic smallhold…