Predicting the susceptibility of a specific part landslide (SSPL) involves predicting likelihood that (e.g., entire landslide, source area, or scarp) will form in given area. When SSPL, samples are far less than non-landslide samples. This class imbalance makes it difficult to predict SSPL. paper proposes an advanced artificial intelligence (AI) model based on dice-cross entropy (DCE) loss func...

In the last years a research project aimed at the assessment of the landslide hazard and susceptibility in the high Cordevole river basin (Eastern Dolomites, Italy) have been carried out. The hazard map was made adopting the Swiss Confederation semi-deterministic approach that takes into account parameters such as velocity, geometry and frequency of landslides. Usually these parameters are coll...

Landslide susceptibility models are fundamental components of landslide risk management strategies. These typically assume that occurrence is time-independent, even though processes including earthquake preconditioning and path dependency transiently impact occurrence. Understanding the temporal characteristics remains limited by a lack systematic investigation into how distributions vary throu...

RESEARCH ARTICLE Application of GIS-Based Back Propagation Artificial Neural Networks and Logistic Regression for shallow Landslide Susceptibility Mapping in South China-Take Meijiang River Basin as an Example Qing-hua Gong, Jun-xiang Zhang and Jun Wang Guangzhou Institute of Geography, Guangzhou 510070, China Guangdong Open Laboratory of Geo-spatial Information Technology and Application, Guan...

The quality of samples is crucial in constructing a data-driven landslide susceptibility model. This article aims to construct model that takes into account the selection non-landslide samples. First, 21 conditioning factors are selected, including four types topography and landform, geological conditions, environmental human activities. Grid units with 30 m resolution established by combining ...

The 3 August 2014 Ludian earthquake with a moment magnitude scale (Mw) of 6.1 induced widespread landslides in the Ludian County and its vicinity. This paper presents a preliminary analysis of the distribution patterns and characteristics of these co-seismic landslides. In total, 1826 landslides with a total area of 19.12 km2 triggered by the 3 August 2014 Ludian earthquake were visually interp...

GIS-based ordered weighted averaging and Dempster–Shafer methods for landslide susceptibility mapping in the Urmia Lake Basin, Iran Bakhtiar Feizizadeh a b , Thomas Blaschke a & Hossein Nazmfar c a Department of Physical Geography, Centre for Remote Sensing and GIS, University of Tabriz, Tabriz, Iran b Department of Geoinformatics (Z_GIS), University of Salzburg, Salzburg, Austria c Department ...

This paper presents a model for quantitative risk analysis with the application of geographic information systems (GISs) using Bayesian theory. It was used for the thematic integration of maps in a natural state (vegetation, geological-geotechnical, natural drainage and gradient). A landslide susceptibility map was produced based on this integration associated with vulnerability data (time and ...

Though danger prediction and countermeasures for landslides are important, it is fundamentally difficult to take preventive measures in all areas susceptible dangerous landslides. Therefore, necessary perform landslide susceptibility mapping, extract slopes with high hazard/risk, prioritize locations conducting investigations countermeasures. In this study, mapping along the whole slope of Japa...