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 …
[HTML][HTML] Landslide susceptibility maps of Italy: Lesson learnt from dealing with multiple landslide types and the uneven spatial distribution of the national inventory
Landslide susceptibility corresponds to the probability of landslide occurrence across a
given geographic space. This probability is usually estimated by using a binary classifier …
given geographic space. This probability is usually estimated by using a binary classifier …
[HTML][HTML] Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors
To perform landslide susceptibility prediction (LSP), it is important to select appropriate
mapping unit and landslide-related conditioning factors. The efficient and automatic multi …
mapping unit and landslide-related conditioning factors. The efficient and automatic multi …
An interpretable model for the susceptibility of rainfall-induced shallow landslides based on SHAP and XGBoost
X Zhou, H Wen, Z Li, H Zhang, W Zhang - Geocarto International, 2022 - Taylor & Francis
The machine-learning “black box” models, which lack interpretability, have limited
application in landslide susceptibility mapping. To interpret the black-box models, some …
application in landslide susceptibility mapping. To interpret the black-box models, some …
不同环境因子联接和预测模型的滑坡易发性建模不确定性
李文彬， 范宣梅， 黄发明， 武雪玲， 殷坤龙， 常志璐 - 地球科学, 2021 - earth-science.net
拟深入探讨滑坡与其环境因子间的非线性联接计算以及不同数据驱动模型等因素,
对滑坡易发性预测建模不确定性的影响规律. 以江西省瑞金市为例共获取370 处滑坡和10 …
对滑坡易发性预测建模不确定性的影响规律. 以江西省瑞金市为例共获取370 处滑坡和10 …
Efficient and automatic extraction of slope units based on multi-scale segmentation method for landslide assessments
The determination of mapping units, including grid, slope, unique condition, administrative
division, and watershed units, is a very important modeling basis for landslide assessments …
division, and watershed units, is a very important modeling basis for landslide assessments …
[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 …
Slow-moving landslide risk assessment combining Machine Learning and InSAR techniques
This paper describes a novel methodology where Machine Learning Algorithms (MLAs)
have been integrated to assess the landslide risk for slow moving mass movements …
have been integrated to assess the landslide risk for slow moving mass movements …
[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 …
[HTML][HTML] Uncertainties of landslide susceptibility prediction: influences of random errors in landslide conditioning factors and errors reduction by low pass filter method
In the existing landslide susceptibility prediction (LSP) models, the influences of random
errors in landslide conditioning factors on LSP are not considered, instead the original …
errors in landslide conditioning factors on LSP are not considered, instead the original …