List of Articles Shallow landslide

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  1 - The performance of the maximum entropy algorithm and geographic information system in shallow landslide susceptibility assessment
  Faezeh Rajabzadeh saeed ghiasi omid Rahmati
  Shallow landslide is one of the natural hazards that damage life and property of people in mountainous watershed. Due to the fact that a lot of landslides events have been occurred in this watershed, assessment the risk of shallow landslides by using appropriate methods More

  Shallow landslide is one of the natural hazards that damage life and property of people in mountainous watershed. Due to the fact that a lot of landslides events have been occurred in this watershed, assessment the risk of shallow landslides by using appropriate methods and determine of effective factors in reduce the hazards of it is so effective. The potential of using maximum entropy modeling for landslide susceptibility mapping is investigated. In the case study of west of Ardabil province, 74 landslide occurrences were identified, 52 landslides (70%) used for training and the 22 landslides (30%) applied for validation purpose. environmental factors including continuous (altitude, slope, aspect, plan curvature, drainage density, and rainfall) and categorical (lithology and landuse) data were used as inputs for modeling. From the optimal setting test based on cross-validation, a continuous data and its combination with categorical data showed the best predictive performance. The results of validation showed that the ROC and AUC for success and prediction rate of model was 96.1 and 97.6%, respectively. Factor contribution analysis indicated that altitude and rainfall layers were the most influential factors. From interpretations on a response curve, steeply sloping areas that consisted of excessively covered with old alluvial terrace soils were very susceptible to landslides. Predictive performance of maximum entropy modeling was slightly better than that other models like of a logistic regression which has been used widely to assess landslide susceptibility. Therefore, Maximum entropy modeling is shown to be an effective prediction model for landslide susceptibility mapping. Manuscript profile
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  2 - Shallow landslide hazard zonation using bivariate statistical methods and GIS(Case study: glandrood watershed)
  ali gilanipoor sadroddin motevalli
  Abstract Nowadays, landslides are treats for terrestrial ecosystems and their living organisms and they are present in the study area. The aim of current research is obtaining the most important effective factors on shallow landslide occurrence in northern Alborz (Noor More

  Abstract Nowadays, landslides are treats for terrestrial ecosystems and their living organisms and they are present in the study area. The aim of current research is obtaining the most important effective factors on shallow landslide occurrence in northern Alborz (Noor County). In the first place, landslide locations were determined by field monitoring and the inventory map of landslides was then prepared. Subsequently, the most effective factors on the landslide incident from 16 data layers, such as biotic and abiotic factors, were derived into ArcGIS 9.3 software. Three models including Landslide Index, Frequency ratio and Certainty Factor were considered to provide the landslide susceptibility map. ROC curve was used to evaluate the models. Results showed that hydrologic elements such as of soil humidity, soil infiltrability, and soil texture along have the highest amount of relationship with the occurrence of shallow landslides in the study region. The results of assessment of model analysis also showed that the shallow landslide zonation map obtained from frequency ratio mode is more accurate one.  Manuscript profile