What is it about?
Bangladesh faces frequent natural disasters like cyclones and floods due to its flat geography and monsoon climate, especially in vulnerable coastal areas like Gabua Union. Researchers used a machine learning model called LASSO to identify factors that make people more vulnerable to these disasters.
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Why is it important?
Understanding these key factors can help governments, policymakers, and aid organizations design better strategies to protect vulnerable communities. For example: Improving access to clean water can reduce vulnerability. Encouraging home gardening can provide food security. Financial support (like access to bank accounts) can help people recover from disasters more quickly.
Perspectives
This research provides a data-driven approach to understanding why some communities in coastal Bangladesh are more vulnerable than others. By using advanced machine learning techniques, it offers valuable insights for improving disaster risk management and achieving global development goals.
Dr. Anjum Tasnuva
Khulna University of Engineering and Technology
Read the Original
This page is a summary of: Employing the generalized Lasso model to evaluate key determinants of livelihood vulnerability in the Southwestern coastal Bangladesh, January 2025, American Institute of Physics,
DOI: 10.1063/5.0249196.
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