A spatially adaptive fusion and ensemble learning workflow using early fusion, late fusion, and mixture of experts improves joint flood-landslide susceptibility mapping while capturing spatial heterogeneity.
Multi-hazard mapping of droughts and forest fires using a multi-layer hazards approach with machine learning algorithms.Geomatics, Natural Hazards and Risk, 13(1):2649–2673
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FL-MHSM: Spatially-adaptive Fusion and Ensemble Learning for Flood-Landslide Multi-Hazard Susceptibility Mapping at Regional Scale
A spatially adaptive fusion and ensemble learning workflow using early fusion, late fusion, and mixture of experts improves joint flood-landslide susceptibility mapping while capturing spatial heterogeneity.