• Login
  • Help Guide
View Item 
  •   JOOUST IR Home
  • Journal Articles
  • School of Engineering and Technology
  • View Item
  •   JOOUST IR Home
  • Journal Articles
  • School of Engineering and Technology
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Comparative assessment of landslide susceptibility by logistic regression and first order second moment method: Case study of Bujumbura Peri-Urban Area, Burundi.

Thumbnail
View/Open
Shirambere_Comparative assessment of landslide susceptibility by logistic.pdf (886.2Kb)
Publication Date
2018-08
Author
Shirambere, Gervais
Nyadawa, Maurice O
Masekanya, Jean pierre
Nyomboi, Timothy
Type
Article
Metadata
Show full item record
Abstract/Overview

Several landslides incidents in the Bujumbura region are reported regularly by independent sources. However, few studies on the causes in the region have been conducted and no record of susceptibility map at a regional exists. In this study, two different approaches are applied to map landslide susceptibility in the region. The physical approach is based on mohr-coulomb failure criterion and is applied using a probabilistic approach, the first order second moment method. The statistical approach is based on logistic regression. The study has two objectives: (i) to map landslide susceptibility in the region and (ii) to compare the results of the different approaches. Applying the two approaches in a GIS framework, two susceptibility map are produced. The accuracy of the two models is independently assessed using ROC and AUC curves. A comparative analysis of the results is conducted and the results shows a fair spatial correlation. The susceptibility maps are compared using rank differences and ArcSDM and a spatial comparison map of susceptibility levels is produced.

Subject/Keywords
Shallow landslide; FOSM; Logistic regression; Bujumbura
Publisher
Journal of Engineering Research and Application
ISSN
2248-9622
Permalink
http://ir.jooust.ac.ke:8080/xmlui/handle/123456789/9417
Collections
  • School of Engineering and Technology [48]

Browse

All of JOOUST IRCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

LoginRegister

Statistics

View Usage Statistics

Contact Us

Copyright © 2023-4 Jaramogi Oginga Odinga University of Science and Technology (JOOUST)
P.O. Box 210 - 40601
Bondo – Kenya

Useful Links

  • Report a problem with the content
  • Accessibility Policy
  • Deaccession/Takedown Policy

TwitterFacebookYouTubeInstagram

  • University Policies
  • Access to Information
  • JOOUST Quality Statement