In this study, a novel approach of the landslide numerical risk factor (LNRF) bivariate model
was used in ensemble with linear multivariate regression (LMR) and boosted regression …

This study aims to delineate landslide susceptibility maps using an integrated approach of
remote sensing, geographical information system (GIS), and Analytical Hierarchy Process …

Choosing appropriate landslide-controlling factors (LCFs) in landslide susceptibility
mapping (LSM) is a challenging task and depends on the nature of terrain and expert …

The main purpose of this study was to perform landslide hazard zonation and evaluation
around Debre Markos town, Northwest Ethiopia. This was achieved using a GIS-based …

The prediction performance of conventional landslide susceptibility (LS) models is generally
limited by the size of samples in the landslide inventory, as unsatisfying performance may be …

Landslide identification is a fundamental step enabling the assessment of landslide
susceptibility and determining the associated risks. Landslide identification by conventional …

Landslide susceptibility map provides a useful tool to the decision-makers to prevent and
mitigate landslide hazards. For this study 16 spatial parameters and past landslide inventory …

This study presented the prediction capability of three methods including the frequency ratio
(FR), fuzzy gamma (FG) and landslide index method (LIM) to produce landslide-prone areas …

In the last decade, development in remote sensing techniques has opened new avenues for
studying the evolution of landscapes dominated by mass wasting processes. Conventional …

Mughal road located in the high mountainous region of Kashmir Himalaya, India is prone to
landslide hazards because of anthropogenic pressure and ongoing climate change …