Content area

Abstract

ABSTRACT

Landslides have a profound impact on landscape geology, resulting in extensive devastation and loss of human lives. Mapping landslide susceptibility is crucial for effective land use planning in mountainous country like Ethiopia. This study was conducted in the upper Didessa sub-basin, southwestern parts of Ethiopia using Geographic Information System (GIS) and multi criteria evaluation (MCE) technique. This study employed a blend of primary data, encompassing field surveys and interviews with experts, as well as secondary data derived from diverse source, such as remote sensing data, digital soil maps, and geological maps. A total of eleven critical factors were employed to assess the triggers of landslides. These factors include slope, aspect, drainage density, topographic wetness index (TWI), stream power index (SPI), topographic ruggedness index (TRI), hypsometric integral, lithology, land use land cover (LULC), soil texture, and distance from roads. The analytical hierarchy process (AHP) method was used to determine the significance of each indicator through pairwise comparison matrix. The study area was categorized into different zones based on the susceptibility to landslides, namely very high, high, moderate, low, and very low. Results revealed that cultivated land had the highest likelihood of experiencing landslides, with a total of nine incidents out of 25, followed by built-up areas with seven landslides. Conversely, dense forests, sparse forests, and grazing land experienced a lower likelihood of landslides. Out of the 11 factors contributing to landslides, 24% of the surveyed region was deemed to have a moderate susceptibility, with 12% and 6% falling into the categories of high and very high susceptibility to landslides, respectively. The findings of this research provide important information for policymakers to develop efficient measures for preventing and reducing the risks of landslides.

Details

1009240
Business indexing term
Location
Title
Landslide susceptibility zonation mapping using geospatial technologies and multi criteria evaluation techniques in the upper Didessa sub-basin, Southwest Ethiopia
Author
Redwan Sultan Mohammednur 1 ; Deribew, Kiros Tsegay 2 ; Moisa, Mitiku Badasa 3 ; Gemeda, Dessalegn Obsi 4 

 Department of Geography and Environmental Studies, College of Social Sciences and Humanities, Jimma University , Jimma , Ethiopia, National Region of Oromia Land Bureau , Addis Ababa , Ethiopia 
 Department of Geography and Environmental Studies, College of Social Sciences and Humanities, Jimma University , Jimma , Ethiopia, Department of Geography and Environmental Studies, Raya University , Maichew , Ethiopia 
 Department of Earth Science, GIS program, College of Natural and Computational, Wollega University Nekemte , Nekemte , Ethiopia 
 Department of Natural Resources Management, College of Agriculture and Veterinary Medicine, Jimma University , Jimma , Ethiopia 
Publication title
Volume
9
Issue
4
Pages
1299-1313
Number of pages
16
Publication year
2025
Publication date
Dec 2025
Publisher
Taylor & Francis Ltd.
Place of publication
Abingdon
Country of publication
United Kingdom
Publication subject
e-ISSN
24749508
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Milestone dates
2023-05-15 (Received); 2024-08-18 (Accepted)
ProQuest document ID
3278753946
Document URL
https://www.proquest.com/scholarly-journals/landslide-susceptibility-zonation-mapping-using/docview/3278753946/se-2?accountid=208611
Copyright
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON).. This work is licensed under the Creative Commons  Attribution – Non-Commercial License http://creativecommons.org/licenses/by-nc/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-12-04
Database
ProQuest One Academic