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Journals / International Journal of Earth Sciences Knowledge and Applications / 2026 / Volume: 8 Issue: 1

Landslide Susceptibility, Risk Assessment, and Mitigation Strategies in Africa: A Systematic Review and Meta-Analysis

Michael Stanley Peprah(IHTMOC Consulting Company Limited)
Edwin Kojo Larbi(Geo-Informatics Division, Building and Road Research Institute)
Pages
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Publication Date
2026-08-03
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Results show that rainfall, slope gradient, and lithology are the main determinants of landslide susceptibility, while deforestation, mining, and informal urban expansion amplify risk.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Landslides are a major environmental hazard across Africa, threatening lives, infrastructure, and sustainable development.
📊
Key Findings & Data:This study conducts a systematic review and meta-analysis of 33 peer-reviewed publications (2010–2025) to evaluate the state of landslide research in Africa.
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Conclusion & Impact:Results show that rainfall, slope gradient, and lithology are the main determinants of landslide susceptibility, while deforestation, mining, and informal urban expansion amplify risk.
🔬Design:Review & Systematic Survey
📍Scope:2010–2025 Verileri
⚙️Variables:Landslide Susceptibility Mapping · Landslide Risk Assessment · Hazard Mitigation Strategies

Abstract

Landslides are a major environmental hazard across Africa, threatening lives, infrastructure, and sustainable development. Their increasing frequency is driven by climate extremes, fragile geology, and rapid, unregulated urbanisation. This study conducts a systematic review and meta-analysis of 33 peer-reviewed publications (2010–2025) to evaluate the state of landslide research in Africa. The objectives were to assess susceptibility and risk assessment models, identify dominant environmental and human risk factors, and compare mitigation strategies across regions. Using the PRISMA framework, data was extracted from multiple databases and analysed through both quantitative and qualitative integration. Results show that rainfall, slope gradient, and lithology are the main determinants of landslide susceptibility, while deforestation, mining, and informal urban expansion amplify risk. Traditional GIS–AHP models achieved mean accuracies of 82%, whereas advanced machine learning and hybrid approaches (RF, FAHP, XAI) attained 88–92%, reflecting improved predictive reliability. East and North Africa exhibit the highest hazard densities due to steep terrain and high rainfall, while Central Africa remains data deficient. Despite methodological progress, fewer than 20% of studies influence national disaster risk reduction (DRR) policies, exposing a persistent science–policy gap. The study highlights the need for evidence-based, data-driven, and inclusive risk management. Strengthening geospatial data infrastructure, integrating scientific research into land-use planning, and enhancing community participation are critical for resilience. These efforts align with the Sendai Framework (2015–2030) and Sustainable Development Goals (SDGs 11, 13, and 15) to advance proactive and climate-resilient landslide risk governance in Africa.

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Cite This Article

Peprah, M. S., Larbi, E. K. (2026). Landslide Susceptibility, Risk Assessment, and Mitigation Strategies in Africa: A Systematic Review and Meta-Analysis. International Journal of Earth Sciences Knowledge and Applications, Volume: 8 Issue: 1. https://ajindex.com/articles/1494599

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