Results 1 to 10 of about 18,543 (287)
Deep learning-based landslide susceptibility mapping. [PDF]
Sci Rep, 2021 AbstractLandslides are considered as one of the most devastating natural hazards in Iran, causing extensive damage and loss of life. Landslide susceptibility maps for landslide prone areas can be used to plan for and mitigate the consequences of catastrophic landsliding events.
Azarafza M +4 more
europepmc +6 more sources
A review on landslide susceptibility mapping research in Bangladesh [PDF]
Heliyon, 2023 Landslide susceptibility mapping is a common practice for landslide susceptibility assessment across the world. Like many other mountainous areas of the world, Bangladesh is facing frequent catastrophic landslides causing severe damage to the economy and
Md. Sharafat Chowdhury
doaj +2 more sources
An objective absence data sampling method for landslide susceptibility mapping [PDF]
Scientific Reports, 2023 The accuracy and quality of the landslide susceptibility map depend on the available landslide locations and the sampling strategy for absence data (non-landslide locations).
Yasin Wahid Rabby +2 more
doaj +2 more sources
Mapping landslide susceptibility at national scale by spatial multi-criteria evaluation [PDF]
Geomatics, Natural Hazards & Risk, 2021 The representation of terrain propensity to generate landslides, meaning the mapping of landslide susceptibility, represents a first step in the assessment of the risk induced by these geomorphological hazards.
Adrian Grozavu +1 more
doaj +5 more sources
Application of Transformer Models to Landslide Susceptibility Mapping. [PDF]
Sensors (Basel), 2022 Landslide susceptibility mapping (LSM) is of great significance for the identification and prevention of geological hazards. LSM is based on convolutional neural networks (CNNs); CNNs use fixed convolutional kernels, focus more on local information and do not retain spatial information. This is a property of the CNN itself, resulting in low accuracy of
Bao S, Liu J, Wang L, Zhao X.
europepmc +4 more sources
A Comprehensive Assessment of XGBoost Algorithm for Landslide Susceptibility Mapping in the Upper Basin of Ataturk Dam, Turkey [PDF]
Applied Sciences, 2021 The success rate in landslide susceptibility mapping efforts increased with the advancements in machine learning algorithms and the availability of geospatial data with high spatial and temporal resolutions.
Recep Can +2 more
doaj +2 more sources
Geoinformation-based landslide susceptibility mapping in subtropical area. [PDF]
Sci Rep, 2021 AbstractMapping susceptibility of landslide disaster is essential in subtropical area, where abundant rainfall may trigger landslide and mudflow, causing damages to human society. The purpose of this paper is to propose an integrated methodology to achieve such a mapping work with improved prediction results using hybrid modeling taking Chongren ...
Zhou X, Wu W, Qin Y, Fu X.
europepmc +4 more sources
The importance of input data on landslide susceptibility mapping [PDF]
Scientific Reports, 2021 Landslide detection and susceptibility mapping are crucial in risk management and urban planning. Constant advance in digital elevation models accuracy and availability, the prospect of automatic landslide detection, together with variable processing ...
Krzysztof Gaidzik +1 more
doaj +2 more sources
Landslide Susceptibility Mapping by Fusing Convolutional Neural Networks and Vision Transformer [PDF]
Sensors, 2022 Landslide susceptibility mapping (LSM) is an important decision basis for regional landslide hazard risk management, territorial spatial planning and landslide decision making. The current convolutional neural network (CNN)-based landslide susceptibility
Shuai Bao +6 more
doaj +2 more sources
Geomatics, Natural Hazards & Risk, 2017 Landslides are a pervasive natural disaster, resulting in severe social, environmental and economic impacts worldwide. The tropical, mountainous landscape in South-West Mexico is predisposed to landslides because of frequent hurricanes and earthquakes ...
Krzysztof Gaidzik +5 more
doaj +3 more sources