نتایج جستجو برای: landslide susceptibility
تعداد نتایج: 138978 فیلتر نتایج به سال:
Mapping of landslide susceptibility in forested watersheds is important for management decisions. In forested watersheds, especially in mountainous areas, the spatial distribution of relevant parameters for landslide prediction is often unavailable. This paper presents a GIS-based modeling approach that includes representation of the uncertainty and variability inherent in parameters. In this a...
Landslide, due to its dangerous nature in mountainous areas, usually causes morphology to suddenly collapse and causes major damage to residential areas, roads, agricultural lands, and so on. In this study, using the AHP model and fuzzy logic operators, we evaluated and zoned the landslide sensitivity in the Pseudogene basin in Razavi Khorasan province. The eight main criteria of elevation, slo...
In this research, machine learning algorithms were compared in a landslide-susceptibility assessment. Given the input set of GIS layers for the Starča Basin, which included geological, hydrogeological, morphometric, and environmental data, a classification task was performed to classify the grid cells to: (i) landslide and non-landslide cases, (ii) different landslide types (dormant and abandon...
The increasing availability of remotely sensed data offers a new opportunity to address landslide hazard assessment at larger spatial scales. A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that may experience landslide activity. This system combines a calculation of static landslide susceptibility with satellite-derived rainfall estimates and ...
Mass movements are usually natural erosion, but the human can aggravate it by operations such as mining, road construction and destroying the natural vegetation. The purpose of this study is to identify the factors influencing the occurrence of landslides by using a probabilistic model Weight of Evidence and Geography Information System in the Siyahbisheh Watershed. 132 landslide points are ide...
In this study, Neuro-Fuzzy model was used to prepare the map of Vaz watershed landslide susceptibility in GIS environment. Location of landslides occurred in the study area was determined through interpretation of aerial photographs and the field monitoring. In the nextstep, factors affecting landslide occurrence such as altitude, lithology, slope, aspect, distance to drainage, distance to ro...
In this study, a novel coupling model for landslide susceptibility mapping is presented. In practice, environmental factors may have different impacts at a local scale in study areas. To provide better predictions, a geographically weighted regression (GWR) technique is firstly used in our method to segment study areas into a series of prediction regions with appropriate sizes. Meanwhile, a sup...
Landslide susceptibility maps are helpful tools to identify areas potentially prone to future landslide occurrence. As more and more national and provincial authorities demand for these maps to be computed and implemented in spatial planning strategies, several aspects of the quality of the landslide susceptibility model and the resulting classified map are of high interest. In this study of la...
Availability of accurate and objective landslide susceptibility maps depicting zones defined on the basis of probability of occurrence of landslides is one of the critical inputs in assessing risk to property and lives in any mountainous region, particularly in the Himalayas. The aim of this study is to assess the utility of soft computing tools, namely, neural network, fuzzy and neuro-fuzzy ap...
Background and objective: Landslide susceptibility zoning using different methods is one of the landslide management strategies. The purpose of this study is to evaluate the landslides susceptibility in the Bar watershed in Khorasan Razavi province using the support vector machine (SVM) algorithm. Method: First, the landslide layer of the area was corrected through field visits and Google Earth...
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