Question 1

Why is landslide susceptibility mapping important in the Himalayas?

Accepted Answer

It supports informed decision-making and proactive planning by identifying areas prone to landslides, which threaten infrastructure and human life in a challenging terrain.

Question 2

How does the study incorporate multi-hazard influences into landslide susceptibility?

Accepted Answer

It integrates flood-related and forest-fire-related susceptibility as novel conditioning factors alongside other environmental and geomorphic variables when building the susceptibility map.

Question 3

Which machine learning model performed best, and what accuracy was reported?

Accepted Answer

XGBoost achieved the highest accuracy at 94%, followed by Random Forest (92%), while ANN reached 77% based on ROC–AUC evaluation.