Predicting urban landslides in the hilly regions of Bangladesh leveraging a hybrid machine learning model and CMIP6 climate projections

Predicting urban landslides in the hilly regions of Bangladesh leveraging a hybrid machine learning model and CMIP6 climate projections

Landslides pose significant risks to infrastructure and human lives in cities, exacerbated by climate change. Therefore, a reliable predictive landslide model is crucial for mitigation, especially in resource-limited nations. This study employs hybrid machine learning (ML) techniques and climate pro...

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Bibliographic Details
Main Authors: Md․ Ashraful Islam, Musabbir Ahmed Arrafi, Mehedi Hasan Peas, Tanvir Hossain, Md Mehedi Hasan, Sanzida Murshed, Monira Jahan Tania
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:Geosystems and Geoenvironment
Subjects:
Landslide
Climate change
Bangladesh
Disaster risk reduction
Landslide mapping
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2772883825000044
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