Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility
In recent decades, data-driven landslide susceptibility models (DdLSM), which are based on
statistical or machine learning approaches, have become popular to estimate the relative …
statistical or machine learning approaches, have become popular to estimate the relative …
[HTML][HTML] Evaluating urban flood risk using hybrid method of TOPSIS and machine learning
With the growth of cities, urban flooding has increasingly become an issue for regional and
national governments. The destructive effects of floods are magnified in cities. Accurate …
national governments. The destructive effects of floods are magnified in cities. Accurate …
[HTML][HTML] A review on spatial, temporal and magnitude prediction of landslide hazard
Over the last few decades, several landslide susceptibility and hazard mapping (LSHM)
techniques have been developed. Maps for the same region have also been generated by …
techniques have been developed. Maps for the same region have also been generated by …
Machine learning ensemble modelling as a tool to improve landslide susceptibility mapping reliability
Statistical landslide susceptibility mapping is a topic in complete and constant evolution,
especially since the introduction of machine learning (ML) methods. A new methodological …
especially since the introduction of machine learning (ML) methods. A new methodological …
Mapping landslide susceptibility using data-driven methods
Most epistemic uncertainty within data-driven landslide susceptibility assessment results
from errors in landslide inventories, difficulty in identifying and mapping landslide causes …
from errors in landslide inventories, difficulty in identifying and mapping landslide causes …
Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models
Gully erosion susceptibility mapping is a fundamental tool for land-use planning aimed at
mitigating land degradation. However, the capabilities of some state-of-the-art data-mining …
mitigating land degradation. However, the capabilities of some state-of-the-art data-mining …
Landslide susceptibility mapping at Golestan Province, Iran: a comparison between frequency ratio, Dempster–Shafer, and weights-of-evidence models
M Mohammady, HR Pourghasemi… - Journal of Asian Earth …, 2012 - Elsevier
The purpose of the present study is to investigate the landslide susceptibility mapping using
three statistical models such as frequency ratio, Dempster–Shafer, and weights-of-evidence …
three statistical models such as frequency ratio, Dempster–Shafer, and weights-of-evidence …
Mapping landslide susceptibility and types using Random Forest
Landslides are one of the most destructive natural hazards; they can drastically alter
landscape morphology, destroy man-made structures, and endanger people's life. Landslide …
landscape morphology, destroy man-made structures, and endanger people's life. Landslide …
A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at İzmir, Turkey
A Akgun - Landslides, 2012 - Springer
The main purpose of this study is to compare the use of logistic regression, multi-criteria
decision analysis, and a likelihood ratio model to map landslide susceptibility in and around …
decision analysis, and a likelihood ratio model to map landslide susceptibility in and around …
[PDF][PDF] GIS-based groundwater spring potential assessment and mapping in the Birjand Township, southern Khorasan Province, Iran
ZS Pourtaghi, HR Pourghasemi - Hydrogeol J, 2014 - academia.edu
Three statistical models—frequency ratio (FR), weights-of-evidence (WofE) and logistic
regression (LR)—produced groundwater-spring potential maps for the Birjand Township …
regression (LR)—produced groundwater-spring potential maps for the Birjand Township …