Search results for "susceptibility mapping"

showing 5 items of 5 documents

Landslides and gully slope erosion on the banks of the Gauja River between the towns of Sigulda and Līgatne

2013

This study examines contemporary and past slope erosion processes in the Gauja River valley and adjoining area between the towns of Sigulda and Līgatne. In the field survey landslides and gullies were mapped. Spatial landslide and gully data were correlated with the landslide- and gully-related features (local relief, slope lithology, slope form, slope angle and density of gullies). A novel approach was applied to establish the relationships between slope processes and factors influencing them. This approach uses correlation between raster values of landslide-related factors in specific slope sections and the number of slope processes in these sections to determine the areas prone to slope …

landslidesgeographysusceptibility mappinggeography.geographical_feature_categoryLithologylcsh:QE1-996.5SedimentLandslideGully erosionlcsh:GeologyParaglacialTributaryErosionPeriod (geology)Gauja River valleyGeneral Earth and Planetary Scienceserosion network.GeomorphologyGeologyWater Science and TechnologygulliesEstonian Journal of Earth Sciences
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Strategies investigation in using artificial neural network for landslide susceptibility mapping: application to a Sicilian catchment

2013

Susceptibility assessment of areas prone to landsliding remains one of the most useful approaches in landslide hazard analysis. The key point of such analysis is the correlation between the physical phenomenon and its triggering factors based on past observations. Many methods have been developed in the scientific literature to capture and model this correlation, usually within a geographic information system (GIS) framework. Among these, the use of neural networks, in particular the multi-layer perceptron (MLP) networks, has provided successful results. A successful application of the MLP method to a basin area requires the definition of different model strategies, such as the sample selec…

HydrologyArtificial Neural NetworkAtmospheric Sciencegeographygeography.geographical_feature_categoryGeographic information systemArtificial neural networkComputer sciencebusiness.industrySettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaDrainage basinLandslideScientific literatureHazard analysisStructural basinGeotechnical Engineering and Engineering GeologyPerceptronGISArtificial Neural Network; GIS; Landslide Susceptibility MappingbusinessCartographyCivil and Structural EngineeringWater Science and TechnologyLandslide Susceptibility Mapping
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Water erosion susceptibility mapping by applying Stochastic Gradient Treeboost to the Imera Meridionale River Basin (Sicily, Italy)

2016

Abstract Soil erosion by water constitutes a serious problem affecting various countries. In the last few years, a number of studies have adopted statistical approaches for erosion susceptibility zonation. In this study, the Stochastic Gradient Treeboost (SGT) was tested as a multivariate statistical tool for exploring, analyzing and predicting the spatial occurrence of rill–interrill erosion and gully erosion. This technique implements the stochastic gradient boosting algorithm with a tree-based method. The study area is a 9.5 km 2 river catchment located in central-northern Sicily (Italy), where water erosion processes are prevalent, and affect the agricultural productivity of local commu…

HydrologyTopographic Wetness Indexgeographygeography.geographical_feature_category010504 meteorology & atmospheric sciencesLandformSettore GEO/04 - Geografia Fisica E GeomorfologiaElevationDrainage basinForecast skillGIS010502 geochemistry & geophysics01 natural sciencesSusceptibility mappingEarth-Surface ProcesseErosionSoil conservationSicilySettore GEO/05 - Geologia ApplicataStream powerGeologySoil Erosion0105 earth and related environmental sciencesEarth-Surface ProcessesGeomorphology
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Effect of raster resolution and polygon-conversion algorithm on landslide susceptibility mapping

2016

The choice of the proper resolution in landslide susceptibility mapping is a worth considering issue. If, on the one hand, a coarse spatial resolution may describe the terrain morphologic properties with low accuracy, on the other hand, at very fine resolutions, some of the DEM-derived morphometric factors may hold an excess of details. Moreover, the landslide inventory maps are represented throughout geospatial vector data structure, therefore a conversion procedure vector-to-raster is required.This work investigates the effects of raster resolution on the susceptibility mapping in conjunction with the use of different algorithms of vector-raster conversion. The Artificial Neural Network t…

Artificial neural networkResamplingEnvironmental EngineeringGeospatial analysis010504 meteorology & atmospheric sciencesComputer scienceArtificial neural network; Grid-cell size; Landslide susceptibility mapping; Resampling; Vector-to-raster conversion; Ecological Modeling; Environmental Engineering; Software0208 environmental biotechnologyComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONTerrain02 engineering and technologycomputer.software_genre01 natural sciencesArray data structureGrid-cell sizeImage resolutionLandslide susceptibility mapping0105 earth and related environmental sciencesArtificial neural networkEcological ModelingSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaVector-to-raster conversionLandslidecomputer.file_format020801 environmental engineeringPolygonRaster graphicscomputerAlgorithmSoftwareEnvironmental Modelling & Software
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Landslide susceptibility mapping: a comparison of logistic regression and neural networks methods in a small sicilian catchment

2012

Artificial Neural Network Landslide Susceptibility MappingSettore ICAR/02 - Costruzioni Idrauliche E Marittime E Idrologia
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