abstract aim of this research is landslide hazard zoning in syahdare watershed using logistic regression. therefore, outset landslide points recognized using air photography and extensive field studies. then distribution of landslide map was makes. then each effective element on landslide occurred for example slope, aspect, elevation, litho logy, land use, distance of road, distance of drainage...

Landslide which is defined as the movement of a mass of rock, debris or earth down a slope,1 is known as one of the most destructive natural hazards all over the world2 but fortunately, it can be prevented through different available methods including prediction and wise constructions. Damages caused by landslides can be ranging from top soil loss to human death, they also can change the figure...

In this study, the support vector machine (SVM) was applied and validated by using the geographic information system (GIS) in order to map landslide susceptibility. In order to test the usefulness and effectiveness of the SVM, two study areas were carefully selected: the PyeongChang and Inje areas of Gangwon Province, Korea. This is because, not only did many landslides (2098 in PyeongChang and...

This paper introduces one current machine learning approach for solving spatial modeling problems in domain of landslide susceptibility assessment. The case study addresses NW slopes of Fruška Gora Mountain in Serbia, where landslide activity has been quite substantial, but not inspected in detail. Regarding this lack of precise landslide inventory, an expert-driven zoning of landslide suscepti...

A landslide susceptibility map plays an essential role in urban and rural planning. The main purpose of this study is to establish a variable-weighted linear combination model (VWLC) and assess its potential for landslide susceptibility mapping. Firstly, different objective methods are employed for data processing rather than the frequently-used subjective judgments: K-means clustering is used ...

The Generalized Likelihood Uncertainty Estimation (GLUE) is here incorporated into a deterministic landslide model (SHALSTAB) to generate 4000 landslide susceptibility maps which enclose various combinations of full range parameters. Furthermore, an improved index is adopted into GLUE as a criterion to measure model performance, and through that, 200 maps holding top 5% performance are retrieve...

A methodology for landslide susceptibility mapping using an integrated remote sensing and GIS approach is presented. A part of the Darjeeling Himalaya was selected for the model execution. IRS satellite data, topographic maps, field data, and other informative maps were used as inputs to the study. Important terrain factors, contributing to landslide occurrences in the region, were identified a...

GIS multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping for the prediction of future hazards, decision making, as well as hazard mitigation plans. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are prone to multiple types of uncertainty. In this paper, the spatiality explicitly method is emp...