t5
proposing-a-top-down-data-driven-framework-to-improve-nasa's-landslide-situational-awareness-system

The authors : Aiding Kornejady, Meisam Samadi, Luigi Lombardo


Place of publication : 6th World Landslide Forum-2023 Florence Italy


Place of publication : 2023


Purpose:
This work pinpoints a discernible paradox in Landslide Hazard Assessment for Situational Awareness (LHASA): 1) simplicity in avoiding the intrinsic uncertainties stored in each part cascade through the entire computational process and diminish the value of a more inclusive and integrated analysis, and 2) including enough accessible and achievable components with a controlled level of uncertainty to provide a representative forecasting map of landslide occurrence. The latter issue would be surmounted with a
Top-Down strategy