Landslides are widespread occurrences that can become catastrophic when they occur near
settlements and infrastructure. Detection, monitoring and prediction are fundamental to …

This paper includes a critical review of the existing literature on the use of satellite SAR
imagery for subsidence analysis. Land subsidence, related to multiple natural and human …

Recent landslide detection studies have focused on pixel-based deep learning (DL)
approaches. In contrast, intuitive annotation of landslides from satellite imagery is based on …

As artificial intelligence (AI) techniques are becoming more popular in landslide modeling, it
is important to understand how decisions are made. Fairness, and transparency becomes …

Earthquakes and heavy rainfalls are the two leading causes of landslides around the world.
Since they often occur across large areas, landslide detection requires rapid and reliable …

Multiple landslide events are common around the globe. They can cause severe damage to
both human lives and infrastructures. Although a huge quantity of research has been …

Landslides originating from remote steep slopes render people living downhill vulnerable,
unaware of the impending danger. Identifications of slow-moving mountain slopes are …

The paper explores the potential of the satellite advanced differential synthetic aperture
radar interferometry (A-DInSAR) technique for the identification of impending slope failure …

Landslide detection is a hot topic in the remote sensing community, particularly with the
current rapid growth in volume (and variety) of Earth observation data and the substantial …

The standard definition of landslide hazard requires the estimation of where, when (or how
frequently) and how large a given landslide event may be. The geoscientific community …