In recent years, black-box machine learning approaches have become a dominant modeling
paradigm for knowledge extraction in remote sensing. Despite the potential benefits of …

This paper systematically reviews remote sensing technology and learning algorithms in
exploring landslides. The work is categorized into four key components:(1) literature search …

This study aims to evaluate the effectiveness of various individual machine learning and
their ensemble techniques such as Stacking, Voting and Meta-learning in landslide …

This study introduces a novel approach to landslide detection by incorporating the Spatial
and Band Refinement Convolution (SBConv) module into the U-Net architecture, to extract …

The complex structures and intricate hyperparameters of existing deep learning models
make achieving higher accuracy in landslide susceptibility assessment timeconsuming and …