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[HTML][HTML] Parameters derived from and/or used with digital elevation models (DEMs) for landslide susceptibility map** and landslide risk assessment: a review
Digital elevation models (DEMs) are considered an imperative tool for many 3D visualization
applications; however, for applications related to topography, they are exploited mostly as a …
applications; however, for applications related to topography, they are exploited mostly as a …
A bibliometric and content analysis of research trends on GIS-based landslide susceptibility from 2001 to 2020
J Huang, X Wu, S Ling, X Li, Y Wu, L Peng… - … Science and Pollution …, 2022 - Springer
To assess the status of hotspots and research trends on geographic information system
(GIS)–based landslide susceptibility (LS), we analysed 1142 articles from the Thomas …
(GIS)–based landslide susceptibility (LS), we analysed 1142 articles from the Thomas …
The importance of input data on landslide susceptibility map**
Landslide detection and susceptibility map** are crucial in risk management and urban
planning. Constant advance in digital elevation models accuracy and availability, the …
planning. Constant advance in digital elevation models accuracy and availability, the …
[HTML][HTML] Landslide susceptibility map**: Machine and ensemble learning based on remote sensing big data
Predicting landslide occurrences can be difficult. However, failure to do so can be
catastrophic, causing unwanted tragedies such as property damage, community …
catastrophic, causing unwanted tragedies such as property damage, community …
GIS-based landslide susceptibility modelling: a comparative assessment of kernel logistic regression, Naïve-Bayes tree, and alternating decision tree models
W Chen, X ** integrating analytical hierarchy process and normalized frequency ratio methods with the cloud model
F Yan, Q Zhang, S Ye, B Ren - Geomorphology, 2019 - Elsevier
Landslides, which could cause huge losses of lives or property damages, result from several
different environmental factors whose influences on landslides are very complex. Therefore …
different environmental factors whose influences on landslides are very complex. Therefore …
Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model
Grid-based landslide susceptibility models at regional scales are computationally
demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based …
demanding when using a fine grid resolution. Conversely, Slope-Unit (SU) based …
Landslide recognition and map** in a mixed forest environment from airborne LiDAR data
T Görüm - Engineering Geology, 2019 - Elsevier
A precise, accurate and complete landslide inventory is indispensable for the establishment
of reliable landslide susceptibility and hazard maps. In the preparation of landslide …
of reliable landslide susceptibility and hazard maps. In the preparation of landslide …
[HTML][HTML] Comparison of support vector machine, Bayesian logistic regression, and alternating decision tree algorithms for shallow landslide susceptibility map** …
This paper aims to apply and compare the performance of the three machine learning
algorithms–support vector machine (SVM), bayesian logistic regression (BLR), and …
algorithms–support vector machine (SVM), bayesian logistic regression (BLR), and …
Explainable boosting machines for slope failure spatial predictive modeling
AE Maxwell, M Sharma, KA Donaldson - Remote Sensing, 2021 - mdpi.com
Machine learning (ML) methods, such as artificial neural networks (ANN), k-nearest
neighbors (k NN), random forests (RF), support vector machines (SVM), and boosted …
neighbors (k NN), random forests (RF), support vector machines (SVM), and boosted …