Leveraging geospatial technologies and statistical models for enhanced landslide susceptibility mapping in Ethiopia’s north-western highlands: a comparative analysis of frequency ratio and weight of evidence models

Landslides pose a significant geohazard in Ethiopia’s northwestern highlands due to steep terrain, heavy rainfall, and unsustainable land use. This study integrates Frequency Ratio (FR) and Weight of Evidence (WoE) models with natural (e.g. slope, lithology, rainfall) and anthropogenic factors (e.g....

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Bibliographic Details
Main Author: Ajitesh Singh Chandel
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:All Earth
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Online Access:https://www.tandfonline.com/doi/10.1080/27669645.2025.2470541
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Summary:Landslides pose a significant geohazard in Ethiopia’s northwestern highlands due to steep terrain, heavy rainfall, and unsustainable land use. This study integrates Frequency Ratio (FR) and Weight of Evidence (WoE) models with natural (e.g. slope, lithology, rainfall) and anthropogenic factors (e.g. deforestation, road proximity) to develop high-resolution susceptibility maps in ArcGIS Pro. Model validation using the Area Under the Curve (AUC) showed superior performance for the FR model (AUC: 88.87%), highlighting its predictive accuracy. High and very high susceptibility zones, covering 41.37% of the study area, are concentrated in the south-central, southeastern, and eastern regions, where steep slopes (>30°), weak lithology, and rainfall exceeding 900 mm, combined with human activities, intensify landslide risks. Over 80% of 339 mapped landslides occurred in these zones, emphasizing the need for targeted interventions. Slope, lithology, and rainfall emerged as dominant triggers, providing actionable insights for mitigation and sustainable land management. This scalable framework supports global applications in geohazard-prone regions like the Andes and Himalayas. Aligned with the Sendai Framework and UN Sustainable Development Goals (SDGs) 11 and 13, the study advocates integrating climate change scenarios into future risk assessments, equipping policymakers to enhance disaster resilience and advance geohazard mitigation strategies.
ISSN:2766-9645