Modelling landslide susceptibility prediction: a review and construction of semi-supervised imbalanced theory
Fully supervised machine learning models are widely applied for landslide susceptibility
prediction (LSP), mainly using landslide and non-landslide samples as output variables and …
prediction (LSP), mainly using landslide and non-landslide samples as output variables and …
Identification of sliding surface and classification of landslide warning based on the integration of surface and deep displacement under normal distribution theory
D Wang, Y Wang, G Li, L Wang, Z Zhou, Y Du… - … and Geophysics for Geo …, 2024 - Springer
Advanced identification of the potential sliding surface of a slope and accurate early warning
are crucial prerequisites for effective management of landslides and timely and prevention of …
are crucial prerequisites for effective management of landslides and timely and prevention of …
[HTML][HTML] Using the spatiotemporal hot spot analysis and multi-annual landslide inventories to analyze the evolution and characteristic of rainfall-induced landslide at …
C Wu - Water, 2023 - mdpi.com
This study used rainfall and annual landslide data for the 2003–2017 period in Taiwan to
determine the long-term evolution of landslides and conducted a spatiotemporal analysis of …
determine the long-term evolution of landslides and conducted a spatiotemporal analysis of …
Methodology and Results of Staged UAS Photogrammetric Rockslide Monitoring in the Alpine Terrain in High Tatras, Slovakia, after the Hydrological Event in 2022
There are numerous talus cones that have formed by long-term geological processes and
sudden hydrological events in the Small Cold Valley (High Tatras National Park in Slovakia) …
sudden hydrological events in the Small Cold Valley (High Tatras National Park in Slovakia) …
Prediction of airport runway settlement using an integrated SBAS-InSAR and BP-EnKF approach
SH Xiong, ZP Wang, G Li, MJ Skibniewski, ZS Chen - Information Sciences, 2024 - Elsevier
The prediction of surface settlement occupies a crucial role in achieving effective
catastrophe prevention and mitigation, as well as facilitating the maintenance of airport …
catastrophe prevention and mitigation, as well as facilitating the maintenance of airport …
SBAS DInSAR and in situ monitoring of the Šumljak landslide (SW Slovenia) dynamics driven by rainfall and piezometric-level fluctuation
G Debevec Jordanova, Z Popović, PE Yastika… - Landslides, 2024 - Springer
This paper presents the first attempt at establishing the dynamics of the Šumljak debris slide
by using a multidisciplinary approach, including long-term inclinometer and piezometer …
by using a multidisciplinary approach, including long-term inclinometer and piezometer …
[HTML][HTML] Unveiling soil coherence patterns along Etihad Rail using Sentinel-1 and Sentinel-2 data and machine learning in arid region
S Alyounis, DE Al Momani, FA Gafoor… - Remote Sensing …, 2024 - Elsevier
This research applies machine learning to predict soil coherence for Etihad Rail, marking
the first comprehensive study in the United Arab Emirates (UAE)'s arid regions. By …
the first comprehensive study in the United Arab Emirates (UAE)'s arid regions. By …
[PDF][PDF] Emprego da Técnica PSInSAR como Ferramenta Complementar em Análise de Subsidências. Caso de Estudo: Bairro Guabirotuba–Curitiba–PR.
S da Conceição Alves, R Dalazoana, CP Krueger… - Rev. Bras. Cartogr, 2023 - seer.ufu.br
Para entender e monitorar adequadamente os riscos decorrentes de processos
deformantes, como a subsidência, é fundamental identificá-los e avaliar sua magnitude …
deformantes, como a subsidência, é fundamental identificá-los e avaliar sua magnitude …
[PDF][PDF] Remote Sensing Applications: Society and Environment
S Alyounis, DE Al Momani, FA Gafoor, Z AlAnsari… - researchgate.net
This research applies machine learning to predict soil coherence for Etihad Rail, marking
the first comprehensive study in the United Arab Emirates (UAE)'s arid regions. By …
the first comprehensive study in the United Arab Emirates (UAE)'s arid regions. By …