Combining multiple machine learning approaches with spatial awareness—rather than using one uniform model across an entire region—significantly improves predictions of natural hazard risks and reveals how different geographic areas are affected by different environmental factors.
This study develops a deep learning system to predict flood and landslide risks across large regions by combining multiple prediction approaches (Early Fusion, Late Fusion, and Mixture of Experts).