Researchers in eThekwini use machine learning to map landslide risks
Scientists in eThekwini have published a study using machine learning and satellite data to identify areas most prone to landslides four years after the 2022 floods.
Study identifies human impact on slopes
A new research paper in Scientific Reports links urban development activities directly to increased landslide susceptibility. The analysis shows that road construction and property development significantly alter the stability of local terrain. Vegetation loss and cultivated land were found to be more dangerous than less disturbed natural environments.
Specific factors drive slope instability
The researchers mapped areas likely to experience landslides by examining elevation, geological conditions, and vegetation cover. Construction activities may change drainage patterns while removing vegetation reduces overall slope stability. These findings highlight the critical role of land use in determining where slides occur.
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