Building a landslide hazard indicator with machine learning and land surface models-Reference-Cited by-同舟云学术

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Building a landslide hazard indicator with machine learning and land surface models

Published:2020-07 Issue: Volume:129 Page:104692
ISSN:1364-8152
Container-title:Environmental Modelling & Software
language:en
Short-container-title:Environmental Modelling & Software

Author:

Stanley T.A.,Kirschbaum D.B.,Sobieszczyk S.,Jasinski M.F.,Borak J.S.,Slaughter S.L.

Funder

NASA National Climate Assessment Project

Climate Indicators and Data Products for Future National Climate Assessments

US Global Change Research Program

Publisher

Elsevier BV

Subject

Ecological Modelling,Environmental Engineering,Software

Reference75 articles.

1. Early warning of rainfall-induced shallow landslides and debris flows in the USA;Baum;Landslides,2009

2. Landslides in West Coast metropolitan areas: the role of extreme weather events;Biasutti;Weather Clim. Extrem.,2016

3. Spatial prediction models for landslide hazards: review, comparison and evaluation;Brenning;Nat. Hazards Earth Syst. Sci.,2005

4. The role of windstorm exposure and yellow cedar decline on landslide susceptibility in southeast Alaskan temperate rainforests;Buma;Geomorphology,2015

5. Catchment similarity for regional flood frequency analysis using seasonality measures;Burn;J. Hydrol.,1997

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2. Landslide susceptibility mapping using physics-guided machine learning: a case study of a debris flow event in Colorado Front Range;Acta Geotechnica;2024-08-13

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4. An ensemble neural network approach for space–time landslide predictive modelling;International Journal of Applied Earth Observation and Geoinformation;2024-08

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