[HTML][HTML] Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility
In recent decades, data-driven landslide susceptibility models (DdLSM), which are based on
statistical or machine learning approaches, have become popular to estimate the relative …
statistical or machine learning approaches, have become popular to estimate the relative …
A bibliometric and content analysis of research trends on GIS-based landslide susceptibility from 2001 to 2020
J Huang, X Wu, S Ling, X Li, Y Wu, L Peng… - … Science and Pollution …, 2022 - Springer
To assess the status of hotspots and research trends on geographic information system
(GIS)–based landslide susceptibility (LS), we analysed 1142 articles from the Thomas …
(GIS)–based landslide susceptibility (LS), we analysed 1142 articles from the Thomas …
Combining rainfall-induced shallow landslides and subsequent debris flows for hazard chain prediction
W Zhou, H Qiu, L Wang, Y Pei, B Tang, S Ma, D Yang… - Catena, 2022 - Elsevier
Landslides, debris flows, and other destructive natural hazards induced by heavy rainfall in
mountainous regions are sometimes not independent but combined to form a disaster chain …
mountainous regions are sometimes not independent but combined to form a disaster chain …
[HTML][HTML] National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data
China is one of the countries where landslides caused the most fatalities in the last decades.
The threat that landslide disasters pose to people might even be greater in the future, due to …
The threat that landslide disasters pose to people might even be greater in the future, due to …
[HTML][HTML] Correlation does not imply geomorphic causation in data-driven landslide susceptibility modelling–Benefits of exploring landslide data collection effects
Data-driven landslide susceptibility models formally integrate spatial landslide information
with explanatory environmental variables that describe predisposing factors of slope …
with explanatory environmental variables that describe predisposing factors of slope …
Effectiveness of Newmark-based sampling strategy for coseismic landslide susceptibility mapping using deep learning, support vector machine, and logistic …
Non-landslide samples play a crucial role in landslide susceptibility mapping (LSM),
although unsuitable sampling methods may degrade the performance of the prediction …
although unsuitable sampling methods may degrade the performance of the prediction …
[HTML][HTML] Assessment of earthquake-induced landslide inventories and susceptibility maps using slope unit-based logistic regression and geospatial statistics
Inventories of seismically induced landslides provide essential information about the extent
and severity of ground effects after an earthquake. Rigorous assessment of the …
and severity of ground effects after an earthquake. Rigorous assessment of the …
Multivariate statistical algorithms for landslide susceptibility assessment in Kailash Sacred landscape, Western Himalaya
A Pandey, M Shekhar Sarkar, S Palni… - … , Natural Hazards and …, 2023 - Taylor & Francis
Landslide susceptibility mapping plays an imperative role in mitigating hazards and
determining the future direction of developmental activities in mountainous regions. Here …
determining the future direction of developmental activities in mountainous regions. Here …
[HTML][HTML] Rainfall-induced shallow landslide detachment, transit and runout susceptibility mapping by integrating machine learning techniques and GIS-based …
Rainfall-induced shallow landslides represent a serious threat in hilly and mountain areas
around the world. The mountainous landscape of the Cinque Terre (eastern Liguria, Italy) is …
around the world. The mountainous landscape of the Cinque Terre (eastern Liguria, Italy) is …
Debris flows modeling using geo-environmental factors: developing hybridized deep-learning algorithms
Although the prediction of debris flow-prone areas represents a key step towards reducing
damages, modeling debris flow susceptibility is complicated. In addition, the role of debris …
damages, modeling debris flow susceptibility is complicated. In addition, the role of debris …