Bivariate statistical analysis of data-driven approaches is widely used for landslide
susceptibility assessment, and the frequency ratio (FR) method is one of the most popular …

Landslide susceptibility mapping plays an important role in integrated watershed
management planning, especially in the field of land-use planning in landslide-prone areas …

Abstract AM w= 6.5 earthquake struck the Jiuzhaigou region of Sichuan Province, China, at
21: 19 LT on Tuesday, 8 August 2017, and triggered a large number of landslides. For …

Landslides have frequently occurred in deeply incised valleys in the upper reaches of the
Minjiang River. Long-term interactions between rock uplift and river undercutting developed …

Landslide warning models are important for mitigating landslide risks. The rainfall threshold
model is the most widely used early warning model for predicting rainfall-triggered …

This study aims at proposing and designing an improved clustering algorithm for assessing
landslide susceptibility using an integration of a Chameleon algorithm and an adaptive …

In the valley of the Surkhob River, manifestations of modern geological processes,
characterized by various forms of manifestation, are widely developed. Studying these …

In landslide susceptibility mapping, a comparative assessment of the susceptibility models is
necessary to find the best fit for the specific area. Data-driven statistical model Information …

Landslides distribute extensively in Rongxian county, the southeast of Guangxi province,
China and pose great threats to this county. At present, hazard management strategy is …

The first question that generally comes to mind about the curvature parameter is whether this
parameter is suitable for the study area. This question uses every parameter to be asked, but …