Results 31 to 40 of about 32,207 (198)

Landslide Susceptibility Mapping Based on Interpretable Machine Learning from the Perspective of Geomorphological Differentiation

Land, 2023
(1) Background: The aim of this paper was to study landslide susceptibility mapping based on interpretable machine learning from the perspective of topography differentiation.
Deliang Sun, Danlu Chen, Jialan Zhang, Changlin Mi, Qingyu Gu, Haijia Wen   +5 more
semanticscholar   +1 more source

Landslide susceptibility mapping using statistical methods in Uatzau catchment area, northwestern Ethiopia

Geoenvironmental Disasters, 2021
Uatzau basin in northwestern Ethiopia is one of the most landslide-prone regions, which characterized by frequent high landslide occurrences causing damages in farmlands, non-cultivated lands, properties, and loss of life.
Azemeraw Wubalem
doaj   +1 more source

Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran

Geoscience Frontiers, 2021
The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses. In this study, we applied two novel deep learning algorithms, the recurrent neural network (RNN) and convolutional
P. T. Ngo, M. Panahi, K. Khosravi, O. Ghorbanzadeh, Narges Karimnejad, A. Cerdà, Saro Lee   +6 more
semanticscholar   +1 more source

Landslide Susceptibility Mapping with Deep Learning Algorithms

Sustainability, 2022
Among natural hazards, landslides are devastating in China. However, little is known regarding potential landslide-prone areas in Maoxian County. The goal of this study was to apply four deep learning algorithms, the convolutional neural network (CNN ...
Jules Maurice Habumugisha, N. Chen, Mahfuzur Rahman, Md. Monirul Islam, Hilal Ahmad, A. Elbeltagi, Gitika Sharma, Sharmina Naznin Liza, A. Dewan   +8 more
semanticscholar   +1 more source

Predictive modeling of landslide hazards in Wen County, northwestern China based on information value, weights-of-evidence, and certainty factor

Geomatics, Natural Hazards & Risk, 2019
Landslide susceptibility mapping is essential in delineating landslide prone areas in mountainous regions. The primary purpose of this study is to evaluate landslide susceptibility mapping using three methods, information value (IV), weights-of-evidence (
Qiqing Wang, Yinghai Guo, Wenping Li, Jianghui He, Zhiyong Wu   +4 more
doaj   +1 more source

Landslide susceptibility mapping using machine learning for Wenchuan County, Sichuan province, China [PDF]

E3S Web of Conferences, 2020
Landslide susceptibility mapping is a method used to assess the probability and spatial distribution of landslide occurrences. Machine learning methods have been widely used in landslide susceptibility in recent years.
Yang Xin, Liu Rui, Li Luyao, Yang Mei, Yang Yuantao   +4 more
doaj   +1 more source

Development of landslide susceptibility mapping with a multi-variance statistical method approach in Kepahiang Indonesia

Terrestrial, Atmospheric and Oceanic Sciences, 2023
Landslides are an example of severe natural disasters that occur worldwide and generate many harmful effects that can affect the stability and development of society. A better-quality susceptibility mapping technique for the landslide risk is crucial for
Eli Putriani, Yih-Min Wu, Chi-Wen Chen, Arif Ismulhadi, Darmawan Ikhlas Fadli   +4 more
semanticscholar   +1 more source

Regional Rainfall-Induced Landslide Risk Assessment Using Susceptibility Mapping and Unexpected High-Intensity Rainfall [PDF]

BIO Web of Conferences
Landslides are one of the most common natural hazards in Malaysia, and besides geological conditions, rainfall intensity and duration are critical factors in assessing landslide risk.
Anees Mohd Talha, Bakar Ahmad Farid Bin Abu, Khan Mohammad Muqtada Ali   +2 more
doaj   +1 more source

An Application of Sentinel-1, Sentinel-2, and GNSS Data for Landslide Susceptibility Mapping

ISPRS International Journal of Geo-Information, 2020
In this study, we used Sentinel-1 and Sentinel-2 data to delineate post-earthquake landslides within an object-based image analysis (OBIA). We used our resulting landslide inventory map for training the data-driven model of the frequency ratio (FR) for ...
Omid Ghorbanzadeh, Khalil Didehban, Hamid Rasouli, Khalil Valizadeh Kamran, Bakhtiar Feizizadeh, Thomas Blaschke   +5 more
doaj   +1 more source

Naïve and Semi-Naïve Bayesian Classification of Landslide Susceptibility Applied to the Kulekhani River Basin in Nepal as a Test Case

Geosciences, 2023
Naïve Bayes classification is widely used for landslide susceptibility analysis, especially in the form of weights-of-evidence. However, when significant conditional dependence is present, the probabilities derived from weights-of-evidence are biased ...
Florimond De Smedt, Prabin Kayastha, Megh Raj Dhital   +2 more
doaj   +1 more source