Challenges of analyzing multi-hazard risk: a review
Many areas of the world are prone to several natural hazards, and effective risk reduction is
only possible if all relevant threats are considered and analyzed. However, in contrast to …
only possible if all relevant threats are considered and analyzed. However, in contrast to …
Remote sensing for landslide investigations: An overview of recent achievements and perspectives
Landslides represent major natural hazards, which cause every year significant loss of lives
and damages to buildings, properties and lifelines. In the last decades, a significant increase …
and damages to buildings, properties and lifelines. In the last decades, a significant increase …
[HTML][HTML] Landslide susceptibility zonation method based on C5. 0 decision tree and K-means cluster algorithms to improve the efficiency of risk management
Abstract Machine learning algorithms are an important measure with which to perform
landslide susceptibility assessments, but most studies use GIS-based classification methods …
landslide susceptibility assessments, but most studies use GIS-based classification methods …
[HTML][HTML] Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China
There is no doubt that land cover and climate changes have consequences on landslide
activity, but it is still an open issue to assess and quantify their impacts. Wanzhou County in …
activity, but it is still an open issue to assess and quantify their impacts. Wanzhou County in …
Recommendations for the quantitative analysis of landslide risk
This paper presents recommended methodologies for the quantitative analysis of landslide
hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and …
hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and …
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 …
Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview
The aim of this paper is to discuss a number of issues related to the use of spatial
information for landslide susceptibility, hazard, and vulnerability assessment. The paper …
information for landslide susceptibility, hazard, and vulnerability assessment. The paper …
Mapping landslide susceptibility with logistic regression, multiple adaptive regression splines, classification and regression trees, and maximum entropy methods: a …
Four statistical techniques for modelling landslide susceptibility were compared: multiple
logistic regression (MLR), multivariate adaptive regression splines (MARS), classification …
logistic regression (MLR), multivariate adaptive regression splines (MARS), classification …
Integrating principal component analysis with statistically-based models for analysis of causal factors and landslide susceptibility mapping: A comparative study from …
Landslide susceptibility assessment is an important task in urban planning and risk
management. For mountainous areas where multiple types of landslides occur, the …
management. For mountainous areas where multiple types of landslides occur, the …
A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses
A Nandi, A Shakoor - Engineering Geology, 2010 - Elsevier
Bivariate and multivariate statistical analyses were used to predict the spatial distribution of
landslides in the Cuyahoga River watershed, northeastern Ohio, USA The relationship …
landslides in the Cuyahoga River watershed, northeastern Ohio, USA The relationship …