This study introduces\textit {Landslide4Sense}, a reference benchmark for landslide
detection from remote sensing. The repository features 3,799 image patches fusing optical …

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

The main goal of the present study is to generate the GIS-based landslide susceptibility map
(LSM) of Meghalaya, India. For this purpose, two bivariate statistical (FR and SE) and multi …

Enormous amount of earth information, gathered from satellite sensors, simulations, and
other resources, are collectively referred to as Big Earth Observation Data (BEOD). The data …

Landslide inventory mapping (LIM) is an important application in remote sensing for
assisting in the relief of landslide geohazards. However, while conducting LIM tasks …

Immediately after an earthquake, rapid disaster management is the main challenge for
relevant organizations. While satellite images have been used in the past two decades for …

Landslides and flash floods are geomorphic hazards (GH) that often co-occur and interact
and frequently lead to societal and environmental impact. The compilation of detailed multi …

Detailed landslide inventories are required for multiple purposes including disaster damage
assessments, susceptibility mapping for spatial planning, and disaster risk reduction. Active …

Accurate landslide susceptibility mapping (LSM) relies on a detailed landslide inventory and
relevant influencing factors. In this study, Sentinel 2 remote sensing imagery is employed to …

Landslides are a dangerous hazard that might have devastating results. Thus, detecting
landslides from satellite images can be significant for various governing authorities. In the …