The application of ensemble learning models has been continuously improved in recent
landslide susceptibility research, but most studies have no unified ensemble framework …

In recent years, there has been a growing interest in flood susceptibility modeling. In this
study, we conducted a bibliometric analysis followed by a meta-data analysis to capture the …

Flood resilience assessment is an important step for any community as it gives the actual
scenario of its ability to resist and recover from flood disasters. However, operationalising …

Globally, communities and governments face growing challenges from an increase in
natural disasters and worsening weather extremes. Precision in disaster preparation is …

Landslides are one of the most common geological hazards worldwide, especially in
Sichuan Province (Southwest China). The current study's main purposes are to explore the …

Flooding is one of the catastrophic natural hazards worldwide that can easily cause
devastating effects on human life and property. Remote sensing devices are becoming …

This study aims to map flood susceptibility in the Qaa'Jahran watersheds located in Dhamar,
Yemen, using geoprocessing and computational techniques. Historical flood data and SAR …

Regional landslide susceptibility mapping (LSM) is essential for risk mitigation. While deep
learning algorithms are increasingly used in LSM, their extensive parameters and scarce …

Assessing and mapping landslide susceptibility is a powerful approach to decrease the cost
of landslide disasters. The aim of this paper is to design combination models by combining …

The stability of tower foundation slopes is an important factor to maintain the operation of a
power system. However, it is time-consuming and expensive to evaluate tower foundation …