Landslides and related hazards

Landslides kill thousands of people each year and cause billions of dollars in infrastructure damage, yet predicting exactly where and when they will occur remains difficult because the conditions that trigger them — heavy rainfall, earthquakes, or gradual soil weakening — interact in ways that vary sharply across landscapes. Researchers use GIS-based modeling, remote sensing, and statistical learning to build susceptibility maps that estimate which slopes are most likely to fail, helping planners prioritize monitoring and land-use restrictions before disaster strikes. A central open question is how well models trained on historical inventories generalize to future events, especially as climate change shifts rainfall patterns and alters the frequency of the extreme precipitation episodes that most commonly set landslides in motion. Translating probabilistic risk assessments into enforceable policy and early-warning systems that communities can act on remains an active area of work bridging environmental science, engineering, and governance.

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150,680

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1,788,314

Keywords

LandslideHazardSusceptibility MappingRainfall TriggeringGIS-based ModelingRisk Assessment