Dempster–Shafer theory-based information fusion for natural disaster emergency management: a systematic literature review
The frequency and unpredictability of natural disasters pose serious challenges to
emergency management in modern society. Effective emergency management requires not …
emergency management in modern society. Effective emergency management requires not …
Landslide4sense: Reference benchmark data and deep learning models for landslide detection
This study introduces\textit {Landslide4Sense}, a reference benchmark for landslide
detection from remote sensing. The repository features 3,799 image patches fusing optical …
detection from remote sensing. The repository features 3,799 image patches fusing optical …
Landslide detection in the Himalayas using machine learning algorithms and U-Net
Event-based landslide inventories are essential sources to broaden our understanding of
the causal relationship between triggering events and the occurring landslides. Moreover …
the causal relationship between triggering events and the occurring landslides. Moreover …
Deep Learning for Earthquake Disaster Assessment: Objects, Data, Models, Stages, Challenges, and Opportunities
J Jia, W Ye - Remote Sensing, 2023 - mdpi.com
Earthquake Disaster Assessment (EDA) plays a critical role in earthquake disaster
prevention, evacuation, and rescue efforts. Deep learning (DL), which boasts advantages in …
prevention, evacuation, and rescue efforts. Deep learning (DL), which boasts advantages in …
Cross-domain landslide mapping from large-scale remote sensing images using prototype-guided domain-aware progressive representation learning
Landslide mapping via pixel-wise classification of remote sensing imagery is essential for
hazard prevention and risk assessment. Deep-learning-based change detection greatly aids …
hazard prevention and risk assessment. Deep-learning-based change detection greatly aids …
A Google Earth Engine approach for wildfire susceptibility prediction fusion with remote sensing data of different spatial resolutions
The effects of the spatial resolution of remote sensing (RS) data on wildfire susceptibility
prediction are not fully understood. In this study, we evaluate the effects of coarse (Landsat 8 …
prediction are not fully understood. In this study, we evaluate the effects of coarse (Landsat 8 …
Landslide detection based on ResU-Net with transformer and CBAM embedded: Two examples with geologically different environments
An efficient method of landslide detection can provide basic scientific data for emergency
command and landslide susceptibility mapping. Compared to a traditional landslide …
command and landslide susceptibility mapping. Compared to a traditional landslide …
Landslide detection using densely connected convolutional networks and environmental conditions
A complete and accurate landslide map is necessary for landslide susceptibility and risk
assessment. Currently, deep learning faces the dilemma of insufficient application, scarce …
assessment. Currently, deep learning faces the dilemma of insufficient application, scarce …
Rapid mapping of landslides on SAR data by attention U-Net
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 …
both human lives and infrastructures. Although a huge quantity of research has been …
Employing remote sensing, data communication networks, ai, and optimization methodologies in seismology
MS Abdalzaher, HA Elsayed… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Seismology is among the intrinsic sciences that strictly affect human lives. Many research
efforts are presented in the literature aiming at achieving risk mitigation and disaster …
efforts are presented in the literature aiming at achieving risk mitigation and disaster …