Author
Listed:
- Myint Myint Shwe
(Nanjing University of Information Science and Technology, China)
- Emmanuel Yeboah
(Nanjing University of Information Science and Technology, China)
- Abraham Okrah
(Nanjing University of Information Science and Technology, China)
- Isaac Sarfo
(Henan University, China)
- Kyaw Lwin Oo
(Department of Meteorology and Hydrology, Myanmar)
- Aye Htet Htet Moe
(Hohai University, China)
- M’Ponkrou Takin
(Nanjing University of Information Science and Technology, China)
- Nana Agyemang Prempeh
(University of Energy and Natural Resources, Ghana)
- Caleb Mensah
(University of Energy and Natural Resources, Ghana)
- Clement Kwang
(University of Ghana, Ghana)
- Dipesh Bhatta
(Hohai University, China)
- Michael Atuahene Djan
(University of Nebraska, USA)
Abstract
This study presents a comprehensive assessment of landslide susceptibility in Chin State, Western Myanmar, focusing on the influence of environmental factors such as rainfall patterns, topographic features, and geological characteristics. Through spatial analysis and statistical inference, strong correlations were identified between these factors and landslide occurrences. The significant correlations revealed robust correlations between rainfall intensity and landslide occurrences, with Pearson correlation coefficient of 0.806, Kendall’s tau_b coefficient of 0.908, and Spearman’s rho coefficient of 0.979. Moreover, topographic features such as flow direction and elevation significantly impacted landslide dynamics, with converging flow patterns and steep slopes contributing to heightened susceptibility. These findings underscore the importance of integrating these insights into risk mitigation strategies and infrastructure planning efforts in Chin State. Urgent proactive measures are needed to safeguard vulnerable communities and critical infrastructure, particularly in light of the increasing trend in landslides and flooding incidents observed over the past decade.
Suggested Citation
Handle:
RePEc:epw:ejgeo0:v:5:y:2024:i:3:id:16459
DOI: 10.24018/ejgeo.2024.5.3.459
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