New global characterisation of landslide exposure

Landslides triggered by intense rainfall are hazards that impact people and infrastructure across the world, but comprehensively quantifying exposure to these hazards remains challenging. Unlike earthquakes or flooding, which cover large areas, landslides occur only in highly susceptible parts of a landscape affected by intense rainfall, which may not intersect human settlement or infrastructure. Existing datasets of landslides around the world generally include only those reported to have caused impacts, leading to significant biases toward areas with higher reporting capacity, limiting our understanding of exposure to landslides in developing countries. In this study, we use an alternative approach to estimate exposure to landslides in a homogenous fashion. We have combined a global landslide hazard proxy derived from satellite data with open-source datasets on population, roads and infrastructure to consistently estimate exposure to rapid landslide hazards around the globe. These exposure models compare favourably with existing datasets of rainfall-triggered landslide fatalities, while filling in major gaps in inventory-based estimates in parts of the world with lower reporting capacity. Our findings provide a global estimate of exposure to landslides from 2001 to 2019 that we suggest may be useful to disaster mitigation professionals.

Displacements of an Active Moderately Rapid Landslide—A Dataset Retrieved by Continuous GNSS Arrays

This paper describes a dataset of continuous GNSS positioning solutions referring to slope movements in the Ca’ Lita landslide (Northern Apennines, Italy). The dataset covers the period from 24 March 2016 to 17 July 2019 and includes time-series of the daily position of three GNSS rovers located in different parts of the landslide: head zone, upper track zone, and lower track zone. Two different types of continuous GNSS arrays have been used: one is based on high-end Leica geodetic receivers, and the other is based on low-cost effective Emlid receivers. Displacements captured in the dataset are up to more than a hundred meters and are characterized by prolonged phases of slow movement and moderately rapid acceleration phases. The data presented in this contribution were used to underline slope processes and validate displacements retrieved by the application of digital image correlation to a stack of a satellite images.