[HTML][HTML] Multi-hazard susceptibility mapping based on Convolutional Neural Networks
Multi-hazard susceptibility prediction is an important component of disasters risk
management plan. An effective multi-hazard risk mitigation strategy includes assessing …
management plan. An effective multi-hazard risk mitigation strategy includes assessing …
Assessing the imperative of conditioning factor grading in machine learning-based landslide susceptibility modeling: a critical inquiry
Current machine learning approaches to landslide susceptibility modeling often involve
grading conditioning factors, a method characterized by substantial subjectivity and …
grading conditioning factors, a method characterized by substantial subjectivity and …
Modeling landslide susceptibility based on convolutional neural network coupling with metaheuristic optimization algorithms
Z Chen, D Song - International Journal of Digital Earth, 2023 - Taylor & Francis
Landslides are one of the most common geological hazards worldwide, especially in
Sichuan Province (Southwest China). The current study's main purposes are to explore the …
Sichuan Province (Southwest China). The current study's main purposes are to explore the …
Applying a 1D convolutional neural network in flood susceptibility assessments—The case of the Island of Euboea, Greece
The main scope of the study is to evaluate the prognostic accuracy of a one-dimensional
convolutional neural network model (1D-CNN), in flood susceptibility assessment, in a …
convolutional neural network model (1D-CNN), in flood susceptibility assessment, in a …
A multi-criteria decision analysis (MCDA) approach for landslide susceptibility mapping of a part of Darjeeling District in North-East Himalaya, India
Landslides are the nation's hidden disaster, significantly increasing economic loss and
social disruption. Unfortunately, limited information is available about the depth and extent of …
social disruption. Unfortunately, limited information is available about the depth and extent of …
Development and assessment of a novel hybrid machine learning-based landslide susceptibility mapping model in the Darjeeling Himalayas
A Saha, VGK Villuri, A Bhardwaj - Stochastic Environmental Research and …, 2023 - Springer
Natural disasters like landslides risk people's lives and the environment. To mitigate these
hazards, scientists employ landslide susceptibility mapping that evaluates zones prone to …
hazards, scientists employ landslide susceptibility mapping that evaluates zones prone to …
Creation of wildfire susceptibility maps in plumas national forest using InSAR coherence, deep learning, and metaheuristic optimization approaches
Plumas National Forest, located in the Butte and Plumas counties, has experienced
devastating wildfires in recent years, resulting in substantial economic losses and …
devastating wildfires in recent years, resulting in substantial economic losses and …
[PDF][PDF] Recent advances of deep learning in geological hazard forecasting
Geological hazard is an adverse geological condition that can cause loss of life and
property. Accurate prediction and analysis of geological hazards is an important and …
property. Accurate prediction and analysis of geological hazards is an important and …
[HTML][HTML] Enhancing landslide susceptibility mapping incorporating landslide typology via stacking ensemble machine learning in Three Gorges Reservoir, China
Different types of landslides exhibit distinct relationships with environmental conditioning
factors. Therefore, in regions where multiple types of landslides coexist, it is required to …
factors. Therefore, in regions where multiple types of landslides coexist, it is required to …
Applying convolutional neural network to predict soil erosion: a case study of coastal areas
The development of ecological restoration projects is unsatisfactory, and soil erosion is still a
problem in ecologically restored areas. Traditional soil erosion studies are mostly based on …
problem in ecologically restored areas. Traditional soil erosion studies are mostly based on …