A data-driven method for the estimation of shallow landslide runout

Rainfall-induced shallow landslides cause damages and casualties. Estimating the development of the runout is essential, however, the methods which are traditionally employed to predict the runout distance are either reliable but complex and applicable at a local scale or applicable at a larger scal...

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Vydané v:Catena (Giessen) Ročník 234; s. 107573
Hlavní autori: Giarola, Alessia, Meisina, Claudia, Tarolli, Paolo, Zucca, Francesco, Galve, Jorge Pedro, Bordoni, Massimiliano
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: 01.01.2024
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ISSN:0341-8162
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Abstract Rainfall-induced shallow landslides cause damages and casualties. Estimating the development of the runout is essential, however, the methods which are traditionally employed to predict the runout distance are either reliable but complex and applicable at a local scale or applicable at a larger scale but highly simplified. The present work aims to develop a method based on data-driven algorithms for predicting the runout of shallow landslides at a large scale, taking into account geological, geomorphological, and land use heterogeneities. The model, which was tested in the Oltrepò Pavese (Italy), a hilly area of over 1000 km², requires as inputs a set of predictors collected from geological maps, land use maps and freely available satellite images. Different algorithms were tested, identifying the Random Forest algorithm as the best performing, with a Coefficient of Determination of 0.94 and Mean Absolute Error of 4–5.8 m. The size of the source area strongly influences runout estimation, as do land use, lithology, and slope angle. The model provides a probable runout length, which can be estimated, based on past observations in the test area, to propagate along the line of the greatest slope. The main novelties of this work include: a) the development of a methodology to study the previously overlooked runout dynamics, b) the exploitation of remotely-derived, freely available input data, c) the application at a large scale in a heterogenous area, d) the adaptability of the model different study areas and e) the dependency of the model on land use, which allows for land use change scenarios to be made. If coupled with a susceptibility assessment tool to identify where a landslide might develop, it could be used to give a fast yet accurate assessment of the probable runout length and to identify which targets could potentially be affected by the landslide.
AbstractList Rainfall-induced shallow landslides cause damages and casualties. Estimating the development of the runout is essential, however, the methods which are traditionally employed to predict the runout distance are either reliable but complex and applicable at a local scale or applicable at a larger scale but highly simplified. The present work aims to develop a method based on data-driven algorithms for predicting the runout of shallow landslides at a large scale, taking into account geological, geomorphological, and land use heterogeneities. The model, which was tested in the Oltrepò Pavese (Italy), a hilly area of over 1000 km², requires as inputs a set of predictors collected from geological maps, land use maps and freely available satellite images. Different algorithms were tested, identifying the Random Forest algorithm as the best performing, with a Coefficient of Determination of 0.94 and Mean Absolute Error of 4–5.8 m. The size of the source area strongly influences runout estimation, as do land use, lithology, and slope angle. The model provides a probable runout length, which can be estimated, based on past observations in the test area, to propagate along the line of the greatest slope. The main novelties of this work include: a) the development of a methodology to study the previously overlooked runout dynamics, b) the exploitation of remotely-derived, freely available input data, c) the application at a large scale in a heterogenous area, d) the adaptability of the model different study areas and e) the dependency of the model on land use, which allows for land use change scenarios to be made. If coupled with a susceptibility assessment tool to identify where a landslide might develop, it could be used to give a fast yet accurate assessment of the probable runout length and to identify which targets could potentially be affected by the landslide.
ArticleNumber 107573
Author Giarola, Alessia
Galve, Jorge Pedro
Meisina, Claudia
Bordoni, Massimiliano
Tarolli, Paolo
Zucca, Francesco
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Cites_doi 10.1111/j.2041-210x.2012.00261.x
10.1029/2019GL082351
10.1016/j.epsl.2020.116203
10.1080/19475705.2022.2097451
10.1016/j.geomorph.2009.06.032
10.1007/BF01301796
10.1007/s10346-012-0348-2
10.3390/w12092555
10.1016/j.enggeo.2008.01.011
10.1007/s10346-014-0478-9
10.5194/nhess-18-1735-2018
10.1139/cgj-2016-0104
10.1029/97RG00426
10.1680/jgeot.15.P.222
10.1016/j.catena.2017.05.026
10.1007/s10064-013-0544-x
10.5194/nhess-13-2815-2013
10.1016/j.geomorph.2012.05.007
10.1007/s10346-020-01392-9
10.1016/j.jhydrol.2019.123932
10.2307/2986296
10.1073/pnas.2021855118
10.1007/s11069-019-03795-x
10.1109/5.784219
10.1080/17445647.2019.1604438
10.1080/21580103.2018.1446367
10.1007/s10346-014-0533-6
10.1007/s11629-021-7254-9
10.5194/nhess-13-559-2013
10.1016/j.geomorph.2014.02.031
10.1007/978-3-030-60227-7_16
10.1007/s10346-020-01485-5
10.5194/hess-23-4603-2019
10.1214/009053607000000505
10.1002/ieam.4132
10.1016/j.catena.2020.104805
10.1029/2006JF000495
10.1016/j.quaint.2010.11.020
10.1016/j.geomorph.2005.08.013
10.1007/s10706-017-0241-9
10.3390/w13040488
10.1002/esp.1064
10.1016/j.geomorph.2014.11.030
10.1016/j.enggeo.2004.10.004
10.3354/cr030079
10.1016/j.geomorph.2021.107921
10.1007/s10346-020-01592-3
10.1007/s12517-012-0807-z
10.1016/j.enggeo.2016.09.002
10.3390/w11122653
10.1016/j.enggeo.2016.10.011
10.1007/s11749-016-0481-7
10.1016/j.geomorph.2011.03.001
10.1139/t96-005
10.1016/j.geomorph.2008.07.009
10.1007/s12303-017-0034-4
10.1680/geot.7.00121
10.1016/j.catena.2019.04.010
10.1007/s10064-018-1328-0
10.1144/1470-9236/03-044
10.1007/s10346-015-0557-6
10.1016/j.catena.2017.09.025
10.1007/s10346-017-0809-8
10.3390/geosciences10050198
10.1007/s10346-014-0484-y
10.1007/s10064-017-1176-3
10.1007/s10064-004-0244-7
10.1016/j.catena.2020.104630
10.1002/wics.182
10.1109/TSMCC.2004.829279
10.5194/nhess-15-1025-2015
10.1016/j.enggeo.2006.09.010
10.1007/s10661-012-2855-y
10.1016/j.enggeo.2004.06.001
10.5194/isprs-archives-XLII-1-W1-83-2017
10.1016/j.epsl.2012.10.029
10.1007/s11069-013-0671-5
10.1016/0006-3207(89)90005-0
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References 10.1016/j.catena.2023.107573_b0240
Hattanji (10.1016/j.catena.2023.107573_b0225) 2009; 103
Koch (10.1016/j.catena.2023.107573_b0275) 2019; 23
10.1016/j.catena.2023.107573_b0165
10.1016/j.catena.2023.107573_b0040
Cascini (10.1016/j.catena.2023.107573_b0080) 2014; 214
Meisina (10.1016/j.catena.2023.107573_b0335) 2006; 88
Qiu (10.1016/j.catena.2023.107573_b0395) 2017; 157
Di Napoli (10.1016/j.catena.2023.107573_b0150) 2020; 17
Roda-Boluda (10.1016/j.catena.2023.107573_b0415) 2018; 43
Pham (10.1016/j.catena.2023.107573_b0380) 2020; 195
Bellugi (10.1016/j.catena.2023.107573_b0015) 2012
Zizioli (10.1016/j.catena.2023.107573_b0480) 2015
Nakagawa (10.1016/j.catena.2023.107573_b0345) 2013; 4
Chen (10.1016/j.catena.2023.107573_b0110) 2013; 185
Medwedeff (10.1016/j.catena.2023.107573_b0325) 2020; 539
Kass (10.1016/j.catena.2023.107573_b0270) 1980; 29
Lima (10.1016/j.catena.2023.107573_b0295) 2022; 19
Nicholls (10.1016/j.catena.2023.107573_b0350) 1989; 50
Zhang (10.1016/j.catena.2023.107573_b0470) 2004; 34
Huang (10.1016/j.catena.2023.107573_b0235) 2013; 68
Scheidegger (10.1016/j.catena.2023.107573_b0425) 1973; 5
Tofani (10.1016/j.catena.2023.107573_b0445) 2017; 14
McDougall (10.1016/j.catena.2023.107573_b0320) 2017; 54
10.1016/j.catena.2023.107573_b0035
Gunn (10.1016/j.catena.2023.107573_b0215) 1998; 14
Domej (10.1016/j.catena.2023.107573_b0160) 2020; 10
Cevasco (10.1016/j.catena.2023.107573_b0095) 2014; 73
Ozturk (10.1016/j.catena.2023.107573_b0355) 2021; 18
10.1016/j.catena.2023.107573_bib482
An (10.1016/j.catena.2023.107573_b0010) 2016; 66
Corominas (10.1016/j.catena.2023.107573_b0125) 2014; 73
Galve (10.1016/j.catena.2023.107573_b0200) 2015; 12
Bosino (10.1016/j.catena.2023.107573_b0065) 2019; 15
Catani (10.1016/j.catena.2023.107573_b0085) 2013; 13
Bordoni (10.1016/j.catena.2023.107573_b0055) 2020; 193
Manenti (10.1016/j.catena.2023.107573_b0310) 2020; 12
Watakabe (10.1016/j.catena.2023.107573_b0450) 2019; 180
Budetta (10.1016/j.catena.2023.107573_b0075) 2004; 63
10.1016/j.catena.2023.107573_b0100
10.1016/j.catena.2023.107573_b0265
Regmi (10.1016/j.catena.2023.107573_b0410) 2014; 7
Nahayo (10.1016/j.catena.2023.107573_b0340) 2019; 15
10.1016/j.catena.2023.107573_b0465
10.1016/j.catena.2023.107573_b0020
De Vita (10.1016/j.catena.2023.107573_b0145) 2013; 10
Willmott (10.1016/j.catena.2023.107573_b0455) 2005; 30
Di Napoli (10.1016/j.catena.2023.107573_b0155) 2021; 13
10.1016/j.catena.2023.107573_b0180
Pawłuszek (10.1016/j.catena.2023.107573_b0365) 2017; 42
Cavalli (10.1016/j.catena.2023.107573_b0090) 2013; 188
Goetz (10.1016/j.catena.2023.107573_b0205) 2011; 129
Iverson (10.1016/j.catena.2023.107573_b0250) 1997; 35
Bordoni (10.1016/j.catena.2023.107573_b0060) 2021; 18
Weiss (10.1016/j.catena.2023.107573_bib483) 2001; Vol.
Meisina (10.1016/j.catena.2023.107573_b0330) 2004; 37
Galve (10.1016/j.catena.2023.107573_b0195) 2006; 213
Gomez (10.1016/j.catena.2023.107573_b0210) 2005; 78
Friedman (10.1016/j.catena.2023.107573_b0185) 1991; 19
Prochaska (10.1016/j.catena.2023.107573_b0385) 2008; 98
Xu (10.1016/j.catena.2023.107573_b0460) 2019; 78
Bordoni (10.1016/j.catena.2023.107573_b0050) 2018; 18
Magidson (10.1016/j.catena.2023.107573_b0300) 1993; 1
10.1016/j.catena.2023.107573_b0255
Persichillo (10.1016/j.catena.2023.107573_b0370) 2017; 8
Tien Bui (10.1016/j.catena.2023.107573_b0440) 2016; 13
10.1016/j.catena.2023.107573_b0130
Jakob (10.1016/j.catena.2023.107573_b0260) 2005; 305–324
10.1016/j.catena.2023.107573_b0175
D'Agostino (10.1016/j.catena.2023.107573_b0135) 2010; 115
Gabet (10.1016/j.catena.2023.107573_b0190) 2006; 74
Breiman (10.1016/j.catena.2023.107573_b0070) 1984
Persichillo (10.1016/j.catena.2023.107573_b0375) 2018; 160
Malamud (10.1016/j.catena.2023.107573_b0305) 2004; 29
Bellugi (10.1016/j.catena.2023.107573_bib485) 2015; 120
Tang (10.1016/j.catena.2023.107573_b0435) 2012; 250
Bordoni (10.1016/j.catena.2023.107573_b0045) 2015; 15
Qi (10.1016/j.catena.2023.107573_b0390) 2012
de Oliveira (10.1016/j.catena.2023.107573_b0140) 2019; 99
Székely (10.1016/j.catena.2023.107573_b0430) 2007; 35
Zizioli (10.1016/j.catena.2023.107573_b0475) 2013; 13
Pastor (10.1016/j.catena.2023.107573_b0360) 2014; 11
10.1016/j.catena.2023.107573_b0405
Chae (10.1016/j.catena.2023.107573_b0105) 2017; 21
Kritikos (10.1016/j.catena.2023.107573_b0280) 2015; 12
10.1016/j.catena.2023.107573_b0005
Qiu (10.1016/j.catena.2023.107573_b0400) 2018; 77
Zhou (10.1016/j.catena.2023.107573_bib481) 2019; 577
Biau (10.1016/j.catena.2023.107573_b0025) 2016; 25
Bordoni (10.1016/j.catena.2023.107573_b0030) 2019; 11
Corominas (10.1016/j.catena.2023.107573_b0120) 1996; 33
Hesterberg (10.1016/j.catena.2023.107573_b0230) 2011; 3
10.1016/j.catena.2023.107573_b0245
Martinović (10.1016/j.catena.2023.107573_b0315) 2016; 215
References_xml – volume: 73
  start-page: 209
  year: 2014
  ident: 10.1016/j.catena.2023.107573_b0125
  article-title: Recommendations for the quantitative analysis of landslide risk
  publication-title: Bull. Eng. Geol. Environ.
– volume: 4
  start-page: 133
  issue: 2
  year: 2013
  ident: 10.1016/j.catena.2023.107573_b0345
  article-title: A general and simple method for obtaining R2 from generalized linear mixed-effects models
  publication-title: Methods Ecol. Evol.
  doi: 10.1111/j.2041-210x.2012.00261.x
– ident: 10.1016/j.catena.2023.107573_b0265
  doi: 10.1029/2019GL082351
– volume: 539
  year: 2020
  ident: 10.1016/j.catena.2023.107573_b0325
  article-title: Characteristic landslide distributions: An investigation of landscape controls on landslide size
  publication-title: Earth Planet. Sci. Lett.
  doi: 10.1016/j.epsl.2020.116203
– ident: 10.1016/j.catena.2023.107573_b0405
  doi: 10.1080/19475705.2022.2097451
– year: 2012
  ident: 10.1016/j.catena.2023.107573_b0015
– volume: 115
  start-page: 294
  issue: 3–4
  year: 2010
  ident: 10.1016/j.catena.2023.107573_b0135
  article-title: Field and laboratory investigations of runout distances of debris flows in the Dolomites (Eastern Italian Alps)
  publication-title: Geomorphology
  doi: 10.1016/j.geomorph.2009.06.032
– volume: 305–324
  year: 2005
  ident: 10.1016/j.catena.2023.107573_b0260
  article-title: Runout prediction methods
  publication-title: Debris-Flow Hazards Related Phenomena
– volume: 5
  start-page: 231
  issue: 4
  year: 1973
  ident: 10.1016/j.catena.2023.107573_b0425
  article-title: On the prediction of the reach and velocity of catastrophic landslides
  publication-title: Rock Mech.
  doi: 10.1007/BF01301796
– volume: 10
  start-page: 713
  year: 2013
  ident: 10.1016/j.catena.2023.107573_b0145
  article-title: Deterministic estimation of hydrological thresholds for shallow landslide initiation and slope stability models: case study from the Somma-Vesuvius area of southern Italy
  publication-title: Landslides
  doi: 10.1007/s10346-012-0348-2
– volume: 12
  start-page: 2555
  issue: 9
  year: 2020
  ident: 10.1016/j.catena.2023.107573_b0310
  article-title: Post-failure dynamics of rainfall-induced landslide in oltrepò pavese
  publication-title: Water
  doi: 10.3390/w12092555
– volume: 98
  start-page: 29
  year: 2008
  ident: 10.1016/j.catena.2023.107573_b0385
  article-title: Debris-flow runout predictions based on the average channel slope (ACS)
  publication-title: Eng. Geol.
  doi: 10.1016/j.enggeo.2008.01.011
– volume: 12
  start-page: 101
  year: 2015
  ident: 10.1016/j.catena.2023.107573_b0200
  article-title: Assessment of Shallow landslide risk mitigation measures based on land use planning through probabilistic modelling
  publication-title: Landslides
  doi: 10.1007/s10346-014-0478-9
– volume: 18
  start-page: 1735
  issue: 6
  year: 2018
  ident: 10.1016/j.catena.2023.107573_b0050
  article-title: Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity
  publication-title: Nat. Hazards Earth Syst. Sci.
  doi: 10.5194/nhess-18-1735-2018
– start-page: 405
  year: 2015
  ident: 10.1016/j.catena.2023.107573_b0480
  article-title: Evaluation of Pleiades Images for Rainfall-Triggered Shallow Landslides Mapping
– volume: 54
  start-page: 605
  issue: 5
  year: 2017
  ident: 10.1016/j.catena.2023.107573_b0320
  article-title: Canadian Geotechnical Colloquium: Landslide runout analysis—current practice and challenges
  publication-title: Can. Geotech. J.
  doi: 10.1139/cgj-2016-0104
– volume: 35
  start-page: 245
  year: 1997
  ident: 10.1016/j.catena.2023.107573_b0250
  article-title: The physics of debris flows
  publication-title: Rev. Geophys.
  doi: 10.1029/97RG00426
– volume: 66
  start-page: 670
  issue: 8
  year: 2016
  ident: 10.1016/j.catena.2023.107573_b0010
  article-title: Three-dimensional smoothed-particle hydrodynamics simulation of deformation characteristics in slope failure
  publication-title: Géotechnique
  doi: 10.1680/jgeot.15.P.222
– volume: 157
  start-page: 180
  year: 2017
  ident: 10.1016/j.catena.2023.107573_b0395
  article-title: Influence of topography and volume on mobility of loess slides within different slip surfaces
  publication-title: Catena
  doi: 10.1016/j.catena.2017.05.026
– volume: 73
  start-page: 859
  year: 2014
  ident: 10.1016/j.catena.2023.107573_b0095
  article-title: The influences of geological and land use settings on shallow landslides triggered by an intense rainfall event in a coastal terraced environment
  publication-title: Bull. Eng. Geol. Environ.
  doi: 10.1007/s10064-013-0544-x
– volume: 120
  start-page: 2552
  issue: 12
  year: 2015
  ident: 10.1016/j.catena.2023.107573_bib485
  article-title: Predicting shallow landslide size and location across a natural landscape: Application of a spectral clustering search algorithm
  publication-title: JGR: Earth Surface
– volume: 13
  start-page: 2815
  issue: 11
  year: 2013
  ident: 10.1016/j.catena.2023.107573_b0085
  article-title: Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues
  publication-title: Nat. Hazards Earth Syst. Sci.
  doi: 10.5194/nhess-13-2815-2013
– volume: Vol.
  year: 2001
  ident: 10.1016/j.catena.2023.107573_bib483
  article-title: Topographic position and landforms analysis
  publication-title: Poster presentation, ESRI user conference
– year: 1984
  ident: 10.1016/j.catena.2023.107573_b0070
– volume: 188
  start-page: 31
  year: 2013
  ident: 10.1016/j.catena.2023.107573_b0090
  article-title: Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments
  publication-title: Geomorphology
  doi: 10.1016/j.geomorph.2012.05.007
– volume: 17
  start-page: 1897
  issue: 8
  year: 2020
  ident: 10.1016/j.catena.2023.107573_b0150
  article-title: Machine learning ensemble modelling as a tool to improve landslide susceptibility mapping reliability
  publication-title: Landslides
  doi: 10.1007/s10346-020-01392-9
– volume: 1
  start-page: 29
  year: 1993
  ident: 10.1016/j.catena.2023.107573_b0300
  article-title: The use of the new ordinal algorithm in CHAID to target profitable segments
  publication-title: J. Database Market.
– volume: 577
  start-page: 123932
  year: 2019
  ident: 10.1016/j.catena.2023.107573_bib481
  article-title: Empirical relationships for the estimation of debris flow runout distances on depositional fans in the Wenchuan earthquake zone
  publication-title: Journal of Hydrology
  doi: 10.1016/j.jhydrol.2019.123932
– volume: 29
  start-page: 199
  year: 1980
  ident: 10.1016/j.catena.2023.107573_b0270
  article-title: An exploratory technique for investigating large quantities of categorical data
  publication-title: Appl. Stat.
  doi: 10.2307/2986296
– ident: 10.1016/j.catena.2023.107573_b0020
  doi: 10.1073/pnas.2021855118
– volume: 99
  start-page: 1049
  year: 2019
  ident: 10.1016/j.catena.2023.107573_b0140
  article-title: Random forest and artificial neural networks in landslide susceptibility modeling: a case study of the Fão River Basin, Southern Brazil
  publication-title: Nat. Hazards
  doi: 10.1007/s11069-019-03795-x
– ident: 10.1016/j.catena.2023.107573_b0465
  doi: 10.1109/5.784219
– volume: 15
  start-page: 382
  issue: 2
  year: 2019
  ident: 10.1016/j.catena.2023.107573_b0065
  article-title: Litho-structure of the Oltrepo Pavese, Northern Apennines (Italy)
  publication-title: J. Maps
  doi: 10.1080/17445647.2019.1604438
– ident: 10.1016/j.catena.2023.107573_b0100
  doi: 10.1080/21580103.2018.1446367
– volume: 19
  start-page: 1
  issue: 1
  year: 1991
  ident: 10.1016/j.catena.2023.107573_b0185
  article-title: Multivariate adaptive regression splines
  publication-title: The Annals of Statistics
– volume: 12
  start-page: 1051
  year: 2015
  ident: 10.1016/j.catena.2023.107573_b0280
  article-title: Assessment of rainfall-generated shallow landslide/debris-flow susceptibility and runout using a GIS-based approach: application to western Southern Alps of New Zealand
  publication-title: Landslides
  doi: 10.1007/s10346-014-0533-6
– volume: 19
  start-page: 1670
  issue: 6
  year: 2022
  ident: 10.1016/j.catena.2023.107573_b0295
  article-title: Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility
  publication-title: J. Mt. Sci.
  doi: 10.1007/s11629-021-7254-9
– volume: 13
  start-page: 559
  issue: 3
  year: 2013
  ident: 10.1016/j.catena.2023.107573_b0475
  article-title: Comparison between different approaches to modeling shallow landslide susceptibility: a case history in Oltrepo Pavese, Northern Italy
  publication-title: Nat. Hazards Earth Syst. Sci.
  doi: 10.5194/nhess-13-559-2013
– volume: 214
  start-page: 502
  year: 2014
  ident: 10.1016/j.catena.2023.107573_b0080
  article-title: SPH run-out modelling of channelised landslides of the flow type
  publication-title: Geomorphology
  doi: 10.1016/j.geomorph.2014.02.031
– ident: 10.1016/j.catena.2023.107573_b0040
  doi: 10.1007/978-3-030-60227-7_16
– volume: 18
  start-page: 681
  issue: 2
  year: 2021
  ident: 10.1016/j.catena.2023.107573_b0355
  article-title: How robust are landslide susceptibility estimates?
  publication-title: Landslides
  doi: 10.1007/s10346-020-01485-5
– volume: 23
  start-page: 4603
  issue: 11
  year: 2019
  ident: 10.1016/j.catena.2023.107573_b0275
  article-title: Modelling of the shallow water table at high spatial resolution using random forests
  publication-title: Hydrol. Earth Syst. Sci.
  doi: 10.5194/hess-23-4603-2019
– volume: 35
  start-page: 2769
  issue: 6
  year: 2007
  ident: 10.1016/j.catena.2023.107573_b0430
  article-title: Measuring and testing dependence by correlation of distances
  publication-title: Ann. Statist.
  doi: 10.1214/009053607000000505
– volume: 15
  start-page: 364
  issue: 3
  year: 2019
  ident: 10.1016/j.catena.2023.107573_b0340
  article-title: Estimating landslides vulnerability in Rwanda using analytic hierarchy process and geographic information system
  publication-title: Integr. Environ. Assess. Manag.
  doi: 10.1002/ieam.4132
– volume: 43
  start-page: 956
  issue: 5
  year: 2018
  ident: 10.1016/j.catena.2023.107573_b0415
  article-title: Lithological controls on hillslope sediment supply: insights from landslide activity and grain size distributions
  publication-title: ESPL.
– volume: 195
  year: 2020
  ident: 10.1016/j.catena.2023.107573_b0380
  article-title: Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping
  publication-title: Catena
  doi: 10.1016/j.catena.2020.104805
– ident: 10.1016/j.catena.2023.107573_b0245
  doi: 10.1029/2006JF000495
– volume: 250
  start-page: 63
  year: 2012
  ident: 10.1016/j.catena.2023.107573_b0435
  article-title: An empirical-statistical model for predicting debris-flow runout zones in the Wenchuan earthquake area
  publication-title: Quat. Int.
  doi: 10.1016/j.quaint.2010.11.020
– volume: 74
  start-page: 207
  issue: 1–4
  year: 2006
  ident: 10.1016/j.catena.2023.107573_b0190
  article-title: The mobilization of debris flows from shallow landslides
  publication-title: Geomorphology
  doi: 10.1016/j.geomorph.2005.08.013
– ident: 10.1016/j.catena.2023.107573_b0175
  doi: 10.1007/s10706-017-0241-9
– volume: 13
  start-page: 488
  issue: 4
  year: 2021
  ident: 10.1016/j.catena.2023.107573_b0155
  article-title: Rainfall-induced shallow landslide detachment, transit and runout susceptibility mapping by integrating machine learning techniques and GIS-based approaches
  publication-title: Water
  doi: 10.3390/w13040488
– volume: 29
  start-page: 687
  issue: 6
  year: 2004
  ident: 10.1016/j.catena.2023.107573_b0305
  article-title: Landslide inventories and their statistical properties
  publication-title: Earth Surf. Proc. Land.
  doi: 10.1002/esp.1064
– volume: 8
  start-page: 748
  issue: 2
  year: 2017
  ident: 10.1016/j.catena.2023.107573_b0370
  article-title: Shallow landslides susceptibility assessment in different environments Geomatics Nat Hazards
  publication-title: Risk
– ident: 10.1016/j.catena.2023.107573_b0005
– ident: 10.1016/j.catena.2023.107573_b0240
  doi: 10.1016/j.geomorph.2014.11.030
– ident: 10.1016/j.catena.2023.107573_b0130
– volume: 78
  start-page: 11
  issue: 1–2
  year: 2005
  ident: 10.1016/j.catena.2023.107573_b0210
  article-title: Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River basin, Venezuela
  publication-title: Eng. Geol.
  doi: 10.1016/j.enggeo.2004.10.004
– volume: 30
  start-page: 79
  issue: 1
  year: 2005
  ident: 10.1016/j.catena.2023.107573_b0455
  article-title: Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance
  publication-title: Climate Res.
  doi: 10.3354/cr030079
– ident: 10.1016/j.catena.2023.107573_b0255
  doi: 10.1016/j.geomorph.2021.107921
– volume: 18
  start-page: 1209
  issue: 4
  year: 2021
  ident: 10.1016/j.catena.2023.107573_b0060
  article-title: Development of a data-driven model for spatial and temporal shallow landslide probability of occurrence at catchment scale
  publication-title: Landslides
  doi: 10.1007/s10346-020-01592-3
– volume: 7
  start-page: 725
  issue: 2
  year: 2014
  ident: 10.1016/j.catena.2023.107573_b0410
  article-title: Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya
  publication-title: Arab. J. Geosci.
  doi: 10.1007/s12517-012-0807-z
– volume: 213
  start-page: 142
  year: 2006
  ident: 10.1016/j.catena.2023.107573_b0195
  article-title: Cost-Based analysis of mitigation measures for shallow-landslide risk reduction strategies
  publication-title: Eng. Geol.
  doi: 10.1016/j.enggeo.2016.09.002
– volume: 11
  start-page: 2653
  year: 2019
  ident: 10.1016/j.catena.2023.107573_b0030
  article-title: Empirical and physically based thresholds for the occurrence of shallow landslides in a prone area of Northern Italian Apennines
  publication-title: Water
  doi: 10.3390/w11122653
– volume: 215
  start-page: 1
  year: 2016
  ident: 10.1016/j.catena.2023.107573_b0315
  article-title: Development of a landslide susceptibility assessment for a rail network
  publication-title: Eng. Geol.
  doi: 10.1016/j.enggeo.2016.10.011
– volume: 25
  start-page: 197
  issue: 2
  year: 2016
  ident: 10.1016/j.catena.2023.107573_b0025
  article-title: A random forest guided tour
  publication-title: TEST
  doi: 10.1007/s11749-016-0481-7
– volume: 129
  start-page: 376
  issue: 3–4
  year: 2011
  ident: 10.1016/j.catena.2023.107573_b0205
  article-title: Integrating physical and empirical landslide susceptibility models using generalized additive models
  publication-title: Geomorphology
  doi: 10.1016/j.geomorph.2011.03.001
– volume: 33
  start-page: 260
  issue: 2
  year: 1996
  ident: 10.1016/j.catena.2023.107573_b0120
  article-title: The angle of reach as a mobility index for small and large landslides
  publication-title: Can. Geotech. J.
  doi: 10.1139/t96-005
– volume: 103
  start-page: 447
  issue: 3
  year: 2009
  ident: 10.1016/j.catena.2023.107573_b0225
  article-title: Morphometric analysis of relic landslides using detailed landslide distribution maps: implications for forecasting travel distance of future landslides
  publication-title: Geomorphology
  doi: 10.1016/j.geomorph.2008.07.009
– volume: 21
  start-page: 1033
  year: 2017
  ident: 10.1016/j.catena.2023.107573_b0105
  article-title: Landslide prediction, monitoring and early warning: a concise review of state-of-the-art
  publication-title: Geosci. J.
  doi: 10.1007/s12303-017-0034-4
– ident: 10.1016/j.catena.2023.107573_bib482
  doi: 10.1680/geot.7.00121
– volume: 180
  start-page: 55
  year: 2019
  ident: 10.1016/j.catena.2023.107573_b0450
  article-title: Lithological controls on hydrological processes that trigger shallow landslides: Observations from granite and hornfels hillslopes in Hiroshima, Japan
  publication-title: Catena
  doi: 10.1016/j.catena.2019.04.010
– volume: 77
  start-page: 1299
  issue: 4
  year: 2018
  ident: 10.1016/j.catena.2023.107573_b0400
  article-title: Developing empirical relationships to predict loess slide travel distances: a case study on the Loess Plateau in China
  publication-title: Bull. Eng. Geol. Environ.
  doi: 10.1007/s10064-018-1328-0
– volume: 37
  start-page: 77
  year: 2004
  ident: 10.1016/j.catena.2023.107573_b0330
  article-title: Swelling-shrinking properties of weathered clayey soils associated with shallow landslides
  publication-title: Q. J. Eng. Geol. Hydrogeol.
  doi: 10.1144/1470-9236/03-044
– volume: 13
  start-page: 361
  year: 2016
  ident: 10.1016/j.catena.2023.107573_b0440
  article-title: Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree
  publication-title: Landslides
  doi: 10.1007/s10346-015-0557-6
– volume: 160
  start-page: 261
  year: 2018
  ident: 10.1016/j.catena.2023.107573_b0375
  article-title: The role of human activities on sediment connectivity of shallow landslides
  publication-title: Catena
  doi: 10.1016/j.catena.2017.09.025
– volume: 14
  start-page: 755
  year: 2017
  ident: 10.1016/j.catena.2023.107573_b0445
  article-title: Soil characterization for shallow landslides modeling: a case study in the Northern Apennines (Central Italy)
  publication-title: Landslides
  doi: 10.1007/s10346-017-0809-8
– volume: 10
  start-page: 198
  issue: 5
  year: 2020
  ident: 10.1016/j.catena.2023.107573_b0160
  article-title: Shape and Dimension Estimations of Landslide Rupture Zones via Correlations of Characteristic Parameters
  publication-title: Geosciences
  doi: 10.3390/geosciences10050198
– volume: 11
  start-page: 793
  year: 2014
  ident: 10.1016/j.catena.2023.107573_b0360
  article-title: Application of a SPH depth-integrated model to landslide run-out analysis
  publication-title: Landslides
  doi: 10.1007/s10346-014-0484-y
– volume: 78
  start-page: 1281
  issue: 2
  year: 2019
  ident: 10.1016/j.catena.2023.107573_b0460
  article-title: Comparison of data-driven models of loess landslide runout distance estimation
  publication-title: Bull. Eng. Geol. Environ.
  doi: 10.1007/s10064-017-1176-3
– volume: 63
  start-page: 293
  issue: 4
  year: 2004
  ident: 10.1016/j.catena.2023.107573_b0075
  article-title: The mobility of some debris flows in pyroclastic deposits of the northwestern Campanian region (southern Italy)
  publication-title: Bull. Eng. Geol. Environ.
  doi: 10.1007/s10064-004-0244-7
– volume: 193
  year: 2020
  ident: 10.1016/j.catena.2023.107573_b0055
  article-title: The influence of the inventory on the determination of the rainfall-induced shallow landslides susceptibility using generalized additive models
  publication-title: Catena
  doi: 10.1016/j.catena.2020.104630
– volume: 3
  start-page: 497
  issue: 6
  year: 2011
  ident: 10.1016/j.catena.2023.107573_b0230
  article-title: Bootstrap
  publication-title: Wiley Interdiscip. Rev. Comput. Stat.
  doi: 10.1002/wics.182
– volume: 34
  start-page: 513
  issue: 4
  year: 2004
  ident: 10.1016/j.catena.2023.107573_b0470
  article-title: Discovering golden nuggets: data mining in financial application
  publication-title: IEEE Trans. Syst., Man, Cybernet., Part C (Appl. Rev.)
  doi: 10.1109/TSMCC.2004.829279
– volume: 14
  start-page: 5
  issue: 1
  year: 1998
  ident: 10.1016/j.catena.2023.107573_b0215
  article-title: Support vector machines for classification and regression
  publication-title: ISIS Technical Report
– volume: 15
  start-page: 1025
  issue: 5
  year: 2015
  ident: 10.1016/j.catena.2023.107573_b0045
  article-title: Site-specific to local-scale shallow landslides triggering zones assessment using TRIGRS
  publication-title: Nat. Hazards Earth Syst. Sci.
  doi: 10.5194/nhess-15-1025-2015
– volume: 88
  start-page: 240
  year: 2006
  ident: 10.1016/j.catena.2023.107573_b0335
  article-title: Ground deformation monitoring by using the permanent scatterers technique: The example of the Oltrepò Pavese (Lombardia, Italy)
  publication-title: Eng. Geol.
  doi: 10.1016/j.enggeo.2006.09.010
– ident: 10.1016/j.catena.2023.107573_b0035
  doi: 10.1016/j.catena.2020.104630
– volume: 185
  start-page: 4125
  year: 2013
  ident: 10.1016/j.catena.2023.107573_b0110
  article-title: Land use change and landslide characteristics analysis for community-based disaster mitigation
  publication-title: Environ. Monit. Assess.
  doi: 10.1007/s10661-012-2855-y
– ident: 10.1016/j.catena.2023.107573_b0165
  doi: 10.1016/j.enggeo.2004.06.001
– volume: 42
  start-page: 83
  year: 2017
  ident: 10.1016/j.catena.2023.107573_b0365
  article-title: Towards the optimal pixel size of DEM for automatic mapping of landslide areas
  publication-title: Int. Arch. Photogramm. Remote. Sens. Spat. Inf. Sci.
  doi: 10.5194/isprs-archives-XLII-1-W1-83-2017
– ident: 10.1016/j.catena.2023.107573_b0180
  doi: 10.1016/j.epsl.2012.10.029
– volume: 68
  start-page: 1021
  year: 2013
  ident: 10.1016/j.catena.2023.107573_b0235
  article-title: Analysis of an anti-dip landslide triggered by the 2008 Wenchuan earthquake in China
  publication-title: Nat. Hazards
  doi: 10.1007/s11069-013-0671-5
– volume: 50
  start-page: 51
  issue: 1–4
  year: 1989
  ident: 10.1016/j.catena.2023.107573_b0350
  article-title: How to make biological surveys go further with generalised linear models
  publication-title: Biol. Conserv.
  doi: 10.1016/0006-3207(89)90005-0
– year: 2012
  ident: 10.1016/j.catena.2023.107573_b0390
  article-title: Random forest for bioinformatics In Ensemble machine learning (pp 307–323)
  publication-title: Springer, Boston, MA.
SSID ssj0004751
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Snippet Rainfall-induced shallow landslides cause damages and casualties. Estimating the development of the runout is essential, however, the methods which are...
SourceID proquest
crossref
SourceType Aggregation Database
Enrichment Source
Index Database
StartPage 107573
SubjectTerms algorithms
catenas
geomorphology
Italy
land use change
landslides
lithology
satellites
Title A data-driven method for the estimation of shallow landslide runout
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Volume 234
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