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 …

Air quality, water pollution, and radiation pollution are major factors that pose genuine
challenges in the environment. Suitable monitoring is necessary so that the world can …

This study introduces four heterogeneous ensemble-learning techniques, that is, stacking,
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …

For emergency rescue and damage assessment after an earthquake, quick detection of
seismic landslides in the affected areas is crucial. The purpose of this study is to quickly …

This article presents a novel method of landslide detection by exploiting the Mask R-CNN
capability of identifying an object layout by using a pixel-based segmentation, along with …

Abstract The WHO (World Health Organization) study reports that, between 1998-2017, 4.8
million people have been affected by landslides with more than 18000 deaths. The …

In recent years, the growth of Machine Learning (ML) algorithms has raised the number of
studies including their applicability in a variety of different scenarios. Among all, one of the …

Classification of environmental sounds plays a key role in security, investigation, robotics
since the study of the sounds present in a specific environment can allow to get significant …

Landslide susceptibility mapping (LSM) is an effective way to predict spatial probability of
landslide occurrence. Existing convolutional neural network (CNN)-based methods apply …

Recent advances in remote sensing hyperspectral imaging and artificial intelligence (AI)
bring exciting opportunities to various fields of science and industry that can directly benefit …