Progress and Lessons Learned from Responses to Landslide Disasters-Reference-Cited by-同舟云学术

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Progress and Lessons Learned from Responses to Landslide Disasters

Published:2020-12-22 Issue: Volume: Page:85-111
ISSN:2662-1894
Container-title:Understanding and Reducing Landslide Disaster Risk
language:
Short-container-title:

Author:

Collins Brian D.,Reid Mark E.,Coe Jeffrey A.,Kean Jason W.,Baum Rex L.,Jibson Randall W.,Godt Jonathan W.,Slaughter Stephen L.,Stock Greg M.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-60196-6_4

Reference91 articles.

1. Angeli M-G, Pasuto A, Silvano S (2000) A critical review of landslide monitoring experiences. Eng Geol 55(30):133–147. https://doi.org/10.1016/S0013-7952(99)00122-2

2. Badger TC, D’Ignazio M (2018) First-time landslides in Vashon advance glaciolacustrine deposits, Puget Lowland, U.S.A. Eng Geol 243:294–307. https://doi.org/10.1016/j.enggeo.2018.07.011

3. Baum RL, Coe JA, Geiger JW et al (2016) Outburst flood creates opportunity to look inside the West Salt Creek rock avalanche deposit, Mesa County, Colorado. Geol Soc Am Abstr Programs 48(7). https://doi.org/10.1130/abs/2016AM-283901

4. Bessette-Kirton EK, Coe JA (2016) Inventory of rock avalanches in western Glacier Bay National Park and Preserve, Alaska, 1984–2016: a baseline data set for evaluating the impact of climate change on avalanche magnitude, mobility, and frequency. U.S. Geological Survey Data Release. https://doi.org/10.5066/F7C827F8

5. Bessette-Kirton EK, Coe JA, Zhou W (2018) Using stereo satellite imagery to account for ablation, entrainment, and compaction in volume calculations for rock avalanches on glaciers: application to the 2016 Lamplugh rock avalanche in Glacier Bay National Park, Alaska. J Geophys Res Earth Surf 123(4):622–641. https://doi.org/10.1002/2017JF004512

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1. Detecting sources of water leakage in fractured limestone: Case study in Mokattam District, Egypt;Water Science;2024-07-14

2. Integrating the Particle Swarm Optimization (PSO) with machine learning methods for improving the accuracy of the landslide susceptibility model;Earth Science Informatics;2022-10-18

3. When hazard avoidance is not an option: lessons learned from monitoring the postdisaster Oso landslide, USA;Landslides;2021-06-18

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