Upon the introduction of machine learning (ML) and its variants, in the form that we know
today, to the landslide community, many studies have been carried out to explore the …

As natural disasters are induced by geodynamic activities or abnormal changes in the
environment, geological hazards tend to wreak havoc on the environment and human …

The present study aims to develop two hybrid models to optimize the factors and enhance
the predictive ability of the landslide susceptibility models. For this, a landslide inventory …

Large earthquakes initiate chains of surface processes that last much longer than the brief
moments of strong shaking. Most moderate‐and large‐magnitude earthquakes trigger …

Image segmentation is a critical and important step in (GEographic) Object-Based Image
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …

In this paper, we do a critical review of statistical methods for landslide susceptibility
modelling and associated terrain zonations. Landslide susceptibility is the likelihood of a …

Machine learning offers the potential for effective and efficient classification of remotely
sensed imagery. The strengths of machine learning include the capacity to handle data of …

Remote sensing image scene classification plays an important role in a wide range of
applications and hence has been receiving remarkable attention. During the past years …

Landslides are a common type of natural disaster that brings great threats to the human lives
and economic development around the world, especially in the Chinese Loess Plateau …

Object-based image classification for land-cover mapping purposes using remote-sensing
imagery has attracted significant attention in recent years. Numerous studies conducted over …