New global characterisation of landslide exposure

Abstract

Abstract. 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.

HazMapper: a global open-source natural hazard mapping application in Google Earth Engine

“…Multi-spectral indices such as the popular normalized burn ratio (NBR) and its derivatives (e.g., difference, relative difference) are widely employed to assess ecosystem impacts following a wildfire (Miller and Thode, 2007;Cocke et al, 2005). Discussion and debate about the most appropriate multi-spectral index to utilize for understanding fire impacts in wildland fire science are ongoing (Keeley, 2009;Miller and Thode, 2007;Escuin et al, 2008;Amos et al, 2019). The rdNDVI technique (Eq.…”

Characteristics and Distribution of Landslides in the Populated Hillslopes of Bujumbura, Burundi

“…The highlands of tropical Africa stand out as continental landslide hotspots where, in addition, high population densities are typically found, frequently on the rise and combined with high societal vulnerability [1][2][3][4][5][6][7]. Despite the frequent occurrence of landslides and the high vulnerability of the population, these mountainous regions are less studied in comparison to similar landscapes in other parts of the world, as is the case with many other places in the African tropics [8][9][10].…”

Data-Driven Landslide Nowcasting at the Global Scale

“…The resulting daily maps of landslide probability were limited to the zone between 60°North and South. In order to evaluate the model's performance against the discrete outputs of LHASA version 1 (Emberson et al, 2020), a threshold of 0.12 was applied to the probabilistic outputs of LHASA version 2; this ensured that the discretized nowcasts would have the same false positive rate (FPR). This threshold is solely intended for comparison and is not necessarily optimal for any specific use.…”

“…The National Aeronautics and Space Administration (NASA) has developed a nearly global landslide nowcasting system that locates the most hazardous conditions in near real-time. Landslide Hazard Assessment for Situational Awareness (LHASA) version 1 is a decision tree model that produces a map of potentially hazardous landslide areas between 60°North and South latitude with three categorizations: low hazard, moderate hazard, and high hazard (Kirschbaum and Stanley, 2018;Emberson et al, 2020). It combines satellite precipitation estimates with a global landslide susceptibility map that incorporates information on roads, faults, geology, forest loss, and topography (Stanley and Kirschbaum, 2017).…”