Application of novel ensemble models to improve landslide susceptibility mapping reliability

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985891%3A_____%2F23%3A00573977" target="_blank" >RIV/67985891:_____/23:00573977 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11310/23:10468601

Result on the web

<a href="https://doi.org/10.1007/s10064-023-03328-8" target="_blank" >https://doi.org/10.1007/s10064-023-03328-8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10064-023-03328-8" target="_blank" >10.1007/s10064-023-03328-8</a>

Result language

angličtina

Original language name

Application of novel ensemble models to improve landslide susceptibility mapping reliability

Original language description

Most landslides in the Eastern Golestan province in Iran occur in the Doji watershed. Their number, however, lies at the lower limit for reliable statistical analyses. By selecting a statistical sample in an area with rather homogeneous conditions (thereby reducing the number of meaningful covariates), significant insights can nevertheless be obtained. We relied on an inventory of 145 landslides which discerns between types of movement and implemented six machine learning algorithms (Decorate, DE-REPTree, Random Subspace, RS-REPTree, Dagging, and DA-REPTree) to produce landslide susceptibility maps. This allowed us to evaluate the relative importance and the effect of covariates in the models and identify factors that are consistently associated with the presence of landslides. Our results demonstrate that, even for a small landslide inventory, reliable susceptibility maps can be produced for homogeneous landscapes. We discuss that our approach could be used to assess the reliability of statistical approaches at small scales, where a distinctive trigger is lacking.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10505 - Geology

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Bulletin of Engineering Geology and the Environment

ISSN

1435-9529

e-ISSN

1435-9537

Volume of the periodical

82

Issue of the periodical within the volume

8

Country of publishing house

DE - GERMANY

Number of pages

21

Pages from-to

309

UT code for WoS article

001027857000001

EID of the result in the Scopus database

2-s2.0-85165221970