Projecting the effect of climate change on multiple Geomorphological hazard using machine learning data driven approaches

Projecting the effect of climate change on multiple Geomorphological hazard using machine learning data driven approaches

Abstract Land subsidence (LS) and collapsed pipes (CP) pose environmental and socio-economic threats in arid and semi-arid regions. This study assesses the effect of climate change to address these problems in Khorasan-Razavi province, Iran. Thus, we mapped soil landforms susceptible to LS and CP ba...

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Bibliographic Details
Main Authors: Narges Kariminejad, Atiyeh Amindin, Adel Sepehr, Hamid Reza Pourghasemi
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Natural hazards
Land subsidence
Collapsed pipe
Climate change
Ensemble model
Online Access:https://doi.org/10.1038/s41598-025-03176-4
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https://doi.org/10.1038/s41598-025-03176-4

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