Comparison of major statistical methods and their combination using matrix validation for landslide susceptibility mapping

A. Q. Akbar, Guangqi Chen

研究成果: Contribution to journalArticle査読

1 被引用数 (Scopus)

抄録

Landslide risk exists with the mountain regions and every year creates a great life and financial losses. To prevent the disaster, numbers of statistical methods have been proposed, but it is still unclear which one is more accurate and yet very few studies proposes a reliable method. Therefore, this study aims to compare the commonly used bivariate statistical method and multivariate statistical methods and their combination to achieve higher accuracy for landslide susceptibility map. Moreover, the classification used for landslide susceptibility mapping is associated with errors, which affects the accuracy of the analysis. In this study, new tool was designed to reduce the classification. To implement this study, a landslide susceptibility maps were created Kabul city. The result proposes that the new designed tool is a good way not only to reduce the classification error by defining the critical thresholds for the classifications. Moreover, all of the statistical methodologies is giving and acceptable result but the combination bivariate and multivariate statistical methods increase the accuracy of the analysis and they are complimentary to each other.

本文言語英語
ページ(範囲)401-412
ページ数12
ジャーナルlowland technology international
20
3
出版ステータス出版済み - 1 1 2018

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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