Insights into geospatial heterogeneity of landslide susceptibility based on the SHAP-XGBoost model
The spatial heterogeneity of landslide influencing factors is the main reason for the poor
generalizability of the susceptibility evaluation model. This study aimed to construct a …
generalizability of the susceptibility evaluation model. This study aimed to construct a …
A review of earth artificial intelligence
Z Sun, L Sandoval, R Crystal-Ornelas… - Computers & …, 2022 - Elsevier
In recent years, Earth system sciences are urgently calling for innovation on improving
accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in …
accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in …
[HTML][HTML] Geohazards in the three Gorges Reservoir Area, China–Lessons learned from decades of research
H Tang, J Wasowski, CH Juang - Engineering Geology, 2019 - Elsevier
The impoundment of the 660-km long reservoir behind the huge Three Gorges Dam, the
world's largest hydropower station, increased regional seismicity and reactivated severe …
world's largest hydropower station, increased regional seismicity and reactivated severe …
[HTML][HTML] A review of statistically-based landslide susceptibility models
In this paper, we do a critical review of statistical methods for landslide susceptibility
modelling and associated terrain zonations. Landslide susceptibility is the likelihood of a …
modelling and associated terrain zonations. Landslide susceptibility is the likelihood of a …
[HTML][HTML] Landslide susceptibility map** using machine learning: A literature survey
Landslide is a devastating natural disaster, causing loss of life and property. It is likely to
occur more frequently due to increasing urbanization, deforestation, and climate change …
occur more frequently due to increasing urbanization, deforestation, and climate change …
[HTML][HTML] A hybrid ensemble-based deep-learning framework for landslide susceptibility map**
Landslides are highly hazardous geological disasters that can potentially threaten the safety
of human life and property. As a result, landslide susceptibility map** (LSM) plays an …
of human life and property. As a result, landslide susceptibility map** (LSM) plays an …
Landslide susceptibility prediction based on a semi-supervised multiple-layer perceptron model
Conventional supervised and unsupervised machine learning models used for landslide
susceptibility prediction (LSP) have many drawbacks, such as an insufficient number of …
susceptibility prediction (LSP) have many drawbacks, such as an insufficient number of …
[HTML][HTML] Landslide susceptibility zonation method based on C5. 0 decision tree and K-means cluster algorithms to improve the efficiency of risk management
Abstract Machine learning algorithms are an important measure with which to perform
landslide susceptibility assessments, but most studies use GIS-based classification methods …
landslide susceptibility assessments, but most studies use GIS-based classification methods …
[HTML][HTML] Predicting flood susceptibility using LSTM neural networks
Identifying floods and producing flood susceptibility maps are crucial steps for decision-
makers to prevent and manage disasters. Plenty of studies have used machine learning …
makers to prevent and manage disasters. Plenty of studies have used machine learning …
Review on landslide susceptibility map** using support vector machines
Y Huang, L Zhao - Catena, 2018 - Elsevier
Landslides are natural phenomena that can cause great loss of life and damage to property.
A landslide susceptibility map is a useful tool to help with land management in landslide …
A landslide susceptibility map is a useful tool to help with land management in landslide …