Results 11 to 20 of about 159,716 (337)
Deep learning-based landslide susceptibility mapping
Scientific Reports, 2021 Landslides are considered as one of the most devastating natural hazards in Iran, causing extensive damage and loss of life. Landslide susceptibility maps for landslide prone areas can be used to plan for and mitigate the consequences of catastrophic ...
Mohammad Azarafza +4 more
semanticscholar +1 more source
Landslide displacement forecasting using deep learning and monitoring data across selected sites
Landslides, 2023 Accurate early warning systems for landslides are a reliable risk-reduction strategy that may significantly reduce fatalities and economic losses. Several machine learning methods have been examined for this purpose, underlying deep learning (DL) models’
Lorenzo Nava +10 more
semanticscholar +1 more source
Landslide4Sense: Reference Benchmark Data and Deep Learning Models for Landslide Detection [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 This study introduces Landslide4Sense, a reference benchmark for landslide detection from remote sensing. The repository features 3799 image patches fusing optical layers from Sentinel-2 sensors with the digital elevation model and slope layer derived ...
O. Ghorbanzadeh +4 more
semanticscholar +1 more source
Atmospheric Science Letters, 2021 The seeder–feeder interactions (SFIs), where raindrops from upper clouds grow by accreting cloud droplets in the lower clouds, have been extensively studied.
Ryohei Misumi +2 more
doaj +1 more source
A temperature- and stress-controlled failure criterion for ice-filled permafrost rock joints [PDF]
The Cryosphere, 2018 Instability and failure of high mountain rock slopes have significantly increased since the 1990s coincident with climatic warming and are expected to rise further.
P. Mamot +4 more
doaj +1 more source
Integration of meteorology and geomorphology for enhanced understanding of post-fire debris-flow hazards [PDF]
E3S Web of Conferences, 2023 Through precipitation, the fields of meteorology and geomorphology are fundamentally linked, thus interdisciplinary efforts are needed to advance understanding and warning of rainfall-driven geohazards.
Oakley Nina +2 more
doaj +1 more source
Spatial and temporal landslide distributions using global and open landslide databases
Natural Hazards, 2023 Landslide databases are a potential tool for the analysis of landslide susceptibility, hazard, and risk. Additionally, the spatio-temporal distribution of landslides and their correlation with their triggering factors are inputs that facilitate the ...
Derly Gómez +2 more
semanticscholar +1 more source
Geoscience Letters, 2023 Sakiyama and Amitori bays of Iriomote Island in Japan are adjacent, but their coral distributions differ significantly. This study investigates the differences in the coral distribution and diversity between both bays from the diversity index and ...
Shinya Shimokawa +2 more
doaj +1 more source
A LightGBM-based landslide susceptibility model considering the uncertainty of non-landslide samples
Geomatics, Natural Hazards & Risk, 2023 The quality of samples is crucial in constructing a data-driven landslide susceptibility model. This article aims to construct a data-driven landslide susceptibility model that takes into account the selection of non-landslide samples.
Deliang Sun +3 more
semanticscholar +1 more source
Landslide detection using deep learning and object-based image analysis
Landslides, 2022 Recent landslide detection studies have focused on pixel-based deep learning (DL) approaches. In contrast, intuitive annotation of landslides from satellite imagery is based on distinct features rather than individual pixels.
O. Ghorbanzadeh +5 more
semanticscholar +1 more source