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Prediction of the landslide susceptibility: which algorithm, which precision?
HR Pourghasemi, O Rahmati - Catena, 2018 - Elsevier
Coupling machine learning algorithms with spatial analytical techniques for landslide
susceptibility modeling is a worth considering issue. So, the current research intend to …
susceptibility modeling is a worth considering issue. So, the current research intend to …
[HTML][HTML] Landslide map** from multi-sensor data through improved change detection-based Markov random field
Accurate landslide inventory map** is essential for quantitative hazard and risk
assessment. Although multi-temporal change detection techniques have contributed greatly …
assessment. Although multi-temporal change detection techniques have contributed greatly …
Comparison of four kernel functions used in support vector machines for landslide susceptibility map**: a case study at Suichuan area (China)
Suichuan is a mountainous area at the Jiangxi province in Central China, where rainfall-
induced landslides occur frequently. The purpose of this study is to assess landslide …
induced landslides occur frequently. The purpose of this study is to assess landslide …
Assessment of susceptibility to rainfall-induced landslides using improved self-organizing linear output map, support vector machine, and logistic regression
GF Lin, MJ Chang, YC Huang, JY Ho - Engineering Geology, 2017 - Elsevier
Quantitative landslide susceptibility assessment is necessary for mitigating casualties,
property damage, and economic loss. Identification of landslides and preparation of …
property damage, and economic loss. Identification of landslides and preparation of …
Derivation of long-term spatiotemporal landslide activity—A multi-sensor time series approach
R Behling, S Roessner, D Golovko… - Remote Sensing of …, 2016 - Elsevier
This paper presents a remote sensing-based method to efficiently derive multi-temporal
landslide inventories over large areas, which allows for the spatiotemporal analysis of …
landslide inventories over large areas, which allows for the spatiotemporal analysis of …
[HTML][HTML] Automated spatiotemporal landslide map** over large areas using rapideye time series data
In the past, different approaches for automated landslide identification based on
multispectral satellite remote sensing were developed to focus on the analysis of the spatial …
multispectral satellite remote sensing were developed to focus on the analysis of the spatial …
[HTML][HTML] A meta-learning approach of optimisation for spatial prediction of landslides
Optimisation plays a key role in the application of machine learning in the spatial prediction
of landslides. The common practice in optimising landslide prediction models is to search for …
of landslides. The common practice in optimising landslide prediction models is to search for …
Characterising the spatial distribution, frequency and geomorphic controls on landslide occurrence, Molise, Italy
An 815-km 2 area in Molise, central Italy, was used as a natural laboratory to characterise
the lithological, topographic, and fluvial controls on the spatial distribution and frequency of …
the lithological, topographic, and fluvial controls on the spatial distribution and frequency of …
Rainfall thresholds for the activation of shallow landslides in the Italian Alps: the role of environmental conditioning factors
The aim of the present work is to investigate the role exerted by selected environmental
factors in the activation of rainfall-triggered shallow landslides and to identify site-specific …
factors in the activation of rainfall-triggered shallow landslides and to identify site-specific …