This study performs a GIS-based landslide susceptibility assessment using convolutional neural network, CNN, in area of the Gorzineh-khil region, northeastern Iran. For this assessment, 15-layered CNN was programmed Python high-level language for mapping. In regard, as far landside triggering factors are concerned, it concluded that geomorphologic/topographic parameters (i.e., slope curvature, ...

Landslide Susceptibility Assessment (LSA) is a fundamental component of landslide risk management and substantial area geospatial research. Previous researchers have considered the spatial non-stationarity relationship between occurrences Conditioning Factors (LCFs) as fixed effects. The effects consider scale different LCFs an average value, which represented by single bandwidth in Geographica...

Subalpine ecosystems are highly fragile as compared to biological andenvironmental factors. Landslide is one of the ruinous upshots of this ecosystem. One of theimpressionable areas in the cause of natural factor is Masoleh watershed in western AlborzMt, (Iran). In order to landslide hazard zonation, landslide index and frequency ratio methodbased on twelve causative factors such as slope, slop...

Various methods are currently used in order to predict shallow landslides within the catchment scale. Among them, physically based models present advantages associated with the physical description of processes by means of mathematical equations. The main objective of this research is the prediction of shallow landslides using TRIGRS model, in a pilot catchment located at Serra do Mar mountain ...