New global characterisation of landslide exposure
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Published:2020-12-14
Issue:12
Volume:20
Page:3413-3424
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ISSN:1684-9981
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Container-title:Natural Hazards and Earth System Sciences
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language:en
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Short-container-title:Nat. Hazards Earth Syst. Sci.
Author:
Emberson Robert, Kirschbaum Dalia, Stanley ThomasORCID
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.
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences
Reference22 articles.
1. 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. 2. 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. 3. 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. 4. 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. 5. 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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