The topic of rainfall thresholds for landslide occurrence was thoroughly investigated,
producing abundance of case studies at different scales of analysis and several technical …

The main objective of the current study was to introduce a Deep Learning Neural Network
(DLNN) model in landslide susceptibility assessments and compare its predictive …

This paper assesses the potentiality of certainty factor models (CF) for the best suitable
causative factors extraction for landslide susceptibility mapping in the Sado Island, Niigata …

The study of rainfall thresholds is vital in understanding the factors that trigger landslides,
being one of the criteria applied to landslide early warning systems that aim to mitigate their …

Landslides are a recurrent environmental hazard in hilly regions and affect the
socioeconomic development in Pakistan. The current study area is the tourism and hydro …

Abstract In 2018 Typhoon Mangkhut (locally known as Typhoon Ompong) triggered
thousands of landslides in the Itogon region of the Philippines. A landslide inventory of the …

Flood triggered by heavy rains and typhoons leads to extensive damage to land and
structures putting rural communities in crucial condition. Most of the studies on risk …

There is a clear need to improve and update landslide susceptibility models across the
Philippines. This is challenging, as landslides in this region are frequently triggered by …

This research focuses on assessing landslide susceptibility in the Jammu and Kashmir
(J&K) region of the northwestern Himalayas, which is known for its high incidence of …

Identifying landslide-susceptible zones is warranted to prevent and mitigate associated
hazards in mountainous regions, where a landslide is a destructive type of erosion. A …