On the estimation of landslide intensity, hazard and density via data-driven models [post]

Mariano Di Napoli, Hakan Tanyas, Daniela Castro-Camilo, Domenico Calcaterra, Andrea Cevasco, Diego Di Martire, Giacomo Pepe, Pierluigi Brandolini, Luigi Lombardo
2022 unpublished
Maps that attempt to predict landslide occurrences have essentially stayed the same since Brabb, E.E., Pampeyan, E.H. and Bonilla, M.G. (1972) Landslide susceptibility in San Mateo County, California (No. 360), US Geological Survey. The tools have certainly changed in fifty years. But, the geomorphological community addressed and still addresses this issue by estimating whether a given slope is potentially stable or unstable. This concept corresponds to the landslide susceptibility, a paradigm
more » ... hat entirely neglects how many landslides may trigger within a given slope, how large these landslides may be and what proportion of the given slope they may disrupt. Modeling how many landslides may occur per mapping unit has been recently proposed via the landslide intensity concept, which has later been shown to closely correlate to the planimetric extent of landslides per mapping unit. In this work, we take this observation a step further as we use the relation between landslide intensity and planimetric extent to generate maps that predict the aggregated size of landslides per mapping unit, and the proportion they may affect. Our findings suggest that it may be time for the geoscientific community as a whole, to revise the use of susceptibility assessment in favour of more informative analytical schemes. Our chain of landslide intensity, hazard and density may in fact lead to substantially improve decision-making processes related to landslide risk.
doi:10.31223/x52d1j fatcat:b72hfdwx2jhx7lvpbi2mvvsbfu