Landslides are the most destructive geological hazard in the hilly regions. For systematic
landslide mitigation and management, landslide evaluation and hazard zonation is required …

Riverside landslides present a significant geohazard globally, posing threats to
infrastructure and human lives. In line with the United Nations' Sustainable Development …

Statistical and now machine learning prediction methods have been gaining popularity in
the field of landslide susceptibility modeling. Particularly, these data driven approaches …

Flood is one of the most prevalent natural disasters that frequently occur in the northern part
of Iran reported in hot spots of flood occurrences. The main aim of the current study was to …

Flood is one of the most devastating natural disasters with socio-economic and
environmental consequences. Thus, comprehensive flood management is essential to …

Landslide hazard mapping is essential for disaster reduction and mitigation. The hazard
map produced by the spatiotemporal probability analysis is usually static with false-negative …

The main objective of the present study was to produce a novel ensemble data mining
technique that involves an adaptive neuro-fuzzy inference system (ANFIS) optimized by …

Statistical landslide susceptibility mapping is a topic in complete and constant evolution,
especially since the introduction of machine learning (ML) methods. A new methodological …

Remote sensing and GIS play a vital role in exploration and assessment of groundwater and
has wide application in detection, monitoring, assessment, conservation and various other …

This research presents the results of the GIS-based statistical models for generation of
landslide susceptibility mapping using geographic information system (GIS) and remote …