0
  • DE
  • EN
  • FR
  • International Database and Gallery of Structures

Advertisement

Landslide Susceptibility Mapping Using GIS and Bivariate Statistical Models in Chemoga Watershed, Ethiopia

Author(s): ORCID
Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2024
Page(s): 1-15
DOI: 10.1155/2024/6616269
Abstract:

This study aimed to map the landslide susceptibility in the Chemoga watershed, Ethiopia, using Geographic Information System (GIS) and bivariate statistical models. Based on Google earth imagery and field survey, about 169 landslide locations were identified and classified randomly into training datasets (70%) and test datasets (30%). Eleven landslides conditioning factors, including slope, elevation, aspect, curvature, topographic wetness index, normalized difference vegetation index, road, river, land use, rainfall, and lithology were integrated with training landslides to determine the weights of each factor and factor classes using both frequency ratio (FR) and information value (IV) models. The final landslide susceptibility map was classified into five classes: very low, low, moderate, high, and very high. The results of area under the curve (AUC) accuracy models showed that the success rates of the FR and IV models were 87.00% and 90.10%, while the prediction rates were 88.00% and 92.30%, respectively. This type of study will be very useful to the local government for future planning and decision on landslide mitigation plans.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1155/2024/6616269.
  • About this
    data sheet
  • Reference-ID
    10771594
  • Published on:
    29/04/2024
  • Last updated on:
    29/04/2024
 
Structurae cooperates with
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine