Articles | Volume 20, issue 12
https://doi.org/10.5194/nhess-20-3413-2020
https://doi.org/10.5194/nhess-20-3413-2020
Research article
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14 Dec 2020
Research article | Highlight paper |  | 14 Dec 2020

New global characterisation of landslide exposure

Robert Emberson, Dalia Kirschbaum, and Thomas Stanley

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Cited articles

Barrington-Leigh, C. and Millard-Ball, A.: The world' s user-generated road map is more than 80 % complete, PLoS One, 12, e0180698, https://doi.org/10.1371/journal.pone.0180698, 2017. 
Carrao, H., Naumann, G., and Barbosa, P.: Mapping global patterns of drought risk: An empirical framework based on sub-national estimates of hazard, exposure and vulnerability, Global Environ. Chang., 39, 108–124, https://doi.org/10.1016/j.gloenvcha.2016.04.012, 2016. 
Coe, B. J. A., Godt, J. W., and Tachker, P.: Map showing recent (1997–98 El Niño) and historical landslides, Crow Creek and vicinity, Alameda and Contra Costa Counties, California, US Department of the Interior, US Geological Survey, Denver, CO, https://doi.org/10.3133/sim2859, 2004. 
De Bono, A. and Chatenoux, B.: A Global Exposure Model for GAR 2015, Background Paper prepared for the 2015 Global Assessment Report on Disaster Risk Reduction, UNEP/Grid, Geneva, 1–20, 2014. 
Dilley, M., Chen, R. S., Deichmann, U., Lerner-Lam, A. L., Arnold, M., Agwe, J., Buys, P., Kjekstad, O., Lyon, B., and Gregory, Y.: Natural Disaster Hotspots A Global Risk Analysis, Disaster Risk Management Series, https://doi.org/10.1596/0-8213-5930-4, 2005. 
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Short summary
Landslides cause thousands of fatalities and cost billions of dollars of damage worldwide every year, but different inventories of landslide events can have widely diverging completeness. This can lead to spatial biases in our understanding of the impacts. Here we use a globally homogeneous model of landslide hazard and exposure to provide consistent estimates of where landslides are most likely to cause damage to people, roads and other critical infrastructure at 1 km resolution.
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