List of Contributors

Beecham, Simon; Begbie, Don; Beza, Beau B.; Bustami, Rosmina A.; Byrne, Josh; Catchlove, Rob; Cilliers, Elizelle Juaneé; Cook, Stephen A.; Dallas, S.; Dandy, Graeme C.; Dillon, Peter J.; Matteo, Michael Di; Dobbie, Meredith Frances; Dodson, Jago; Rohr, Hildegard Edith; Ehrenfried, Lisa; Furlong, Casey; Sharma, Ashok; Gehrmann, Simon; Goonetilleke, Ashantha; Green, Melissa; Hadwen, Wade L.; Hamlyn-Harris, David; Hanson, Frederick W.; Hawley, Robert J.; Hoban, Alan E.; Iftekhar, Sayed; Jamei, Elmira; Ladson, Anthony Richard; LaGro, James; Lampard, Jane-Louise; Leigh, Catherine; Leonard, Rosemary; Lucke, Terry; Ying, Ma; Maier, Holger R.; McAlister, Tony; Morison, Peter; Mullaly, Jack; Myers, Baden; Neilan, Wendy; Newham, Michael; O'Bannon, Deborah; Pendergast, Micah; Pezzaniti, David; Phillips, Samuel; Pitt, Robert; Polson, Carolyn; Radcliffe, John; Rashetnia, Samira; Razzaghmanesh, Mostafa; Rowlands, Leon; Rudolph-Cleff, Annette; Schramm, Engelbert; Sharma, Ashok; Sheldon, Fran; Talebi, Leila; Tapper, Nigel; Tjandraatmadja, Grace; Meene, Susan van de; Roon, Marjorie van; Vietz, Geoff; Walker, Christopher J.; Walton, Andrea; Ward, J. V.; Whiteoak, Kym; Winker, Martina; Qian, Yu; Zeunert, Joshua; Zimmermann, Martin

doi:10.1016/b978-0-12-812843-5.01002-9

Cited by 1 publication

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“…Land use is associated with urbanization processes. Urbanization results in irrevocable changes to the landscape, the spread of the built environment, and an increase in anthropogenic activities (Sharma et al 2019).…”

Section: Figmentioning

confidence: 99%

Landslide susceptibility mapping of Gdynia using geographic information system-based statistical models

Małka

2021

Nat Hazards

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This work aims to prepare a reliable landslide susceptibility model and to analyse the factors contributing to landslides in a dynamic environment by considering the city of Gdynia, Poland as a case study. Geological, geomorphological, hydrological, hydrogeological, and anthropogenic predisposing factors are considered using geographic information systems. Ground types at different depths (1 m and 4 m b.g.l.) are used in the statistical susceptibility assessment for the first time. Landslide susceptibility maps are developed using two techniques in presenting landslides, 13 conditioning factors, and three statistical methods: landslide index, weight of evidence, and logistic regression. The considered factors have an influence on mass movement formation, but their roles are different. Many of these passive factors are interrelated and some of them are also related to active factors, i.e. triggers. Consideration of many thematic layers in the statistical approach allows for the selection of the most appropriate geo-environmental variables. The most significant conditioning factors that affect the likelihood of landsliding include land use and land cover as well as topography. The susceptibility maps generated by the index model and many interrelated passive factors appear to be over-predicted. The logistic regression model and only independent controlling factors (slope angle, slope aspect, and lithology) are sufficient to compile a reliable susceptibility map of Gdynia. Prediction rate curve plots show that the susceptibility map produced using logistic regression exhibits the highest prediction accuracy. The results emphasize the need to check independence in the selection of instability factors and the use of an independent subset of landslides for validation.

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Section: Figmentioning

confidence: 99%

Landslide susceptibility mapping of Gdynia using geographic information system-based statistical models

Małka

2021

Nat Hazards

View full text Add to dashboard Cite

show abstract

List of Contributors

Cited by 1 publication

References 0 publications

Landslide susceptibility mapping of Gdynia using geographic information system-based statistical models

Landslide susceptibility mapping of Gdynia using geographic information system-based statistical models

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