Narges Javidan; Ataollah Kavian; Sajad Rajabi; Hamidreza Pourghasemi; Christian Conoscenti; Zeinab Jafarian
Abstract
Slope instability and landslides are important hazards to human activities that often result in the loss of economic resources, property damage and facilities. These hazards occur in the natural or man-made slopes. In the current study, the maximum entropy model was used which is one of the progressive ...
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Slope instability and landslides are important hazards to human activities that often result in the loss of economic resources, property damage and facilities. These hazards occur in the natural or man-made slopes. In the current study, the maximum entropy model was used which is one of the progressive data mining models, in order to modelling landslide susceptibility map for Gorganrood watershed. In the first step, the landslide inventory map was prepared consiste of 351 landslides. 18 geo-environmental factors were selected as predictors, such as: Digital elevation model, slope percent, aspect, distance from fault, distance from river, distance from road, rainfall, landuse, drainage density, lithology, soil texture, plan curvature, profil curvature, lithological formation, Topographic wetness index, LS factor, stream power index, Relative Slope Position and Surface roughness index. Three different sample data sets (S1, S2, and S3) including 70% for training and 30% for validation were randomly prepared to evaluate the robustness of the model. The accuracy of the predictive model was evaluated by drawing receiver operating characteristic (ROC) curves and by calculating the area under the ROC curve (AUC). The ME model performed excellently both in the degree of fitting and in predictive performance (AUC values well above 0.8), which resulted in accurate predictions. Furthermore, In this study the importance of variables was evaluated by the model. Dem (digital elevation model) (32.4% importance), lithology (22.9% importance) and distance from fault (14.8% importance) were identified respectively the main controlling factor among all other variables.
Narges Ghasemiamin; Nasim Arman; Hossein Zeinivand
Abstract
Land use involves exploitation type of land for resolving human different needs. Land use changes is the result of interaction between human and affective factors on environment which is considered in spatial and temporal scale. Awareness of land use rates and its change in time is one of the most important ...
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Land use involves exploitation type of land for resolving human different needs. Land use changes is the result of interaction between human and affective factors on environment which is considered in spatial and temporal scale. Awareness of land use rates and its change in time is one of the most important factors in planning and management. By knowing rate of land use changes time scale, forecasting feature changes will be possible and do appropriate act. In this research, 2014 land use map was prepared by RS with Kappa coefficient of 0.88 and overall accuracy of 0.86 which has high accuracy. For investigating each effective factor on land use in CLUE-S model logistic regression was used and for assessment of logistic regression, ROC curve was used. After determination of demand ratio according to past changes, land use map of 2025 was prepared. Assessment of CLUE-S model showed its high accuracy (Kappa coefficient is 0.88). Also, the results demonstrated that the most land use change are related to forests and ranges to farmlands, as range and forest lands decreases 28.12 and 82.20 present respectively and farmlands increases 10.33 percent until 2025.
Seid Saeid Ghiasi; Faezeh Rajabzadeh; Somayye Najirda; Sadat Feiznia; Aliakbar Nazari Samani
Abstract
Shallow landslide susceptibility assessment by using appropriate methods and determine of effective factors in reduce of its hazards is so effective. The aim of this study is to determine the effective factors on shallow landslide occurrence and investigation of Statistical Index Method (SIM) efficiency ...
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Shallow landslide susceptibility assessment by using appropriate methods and determine of effective factors in reduce of its hazards is so effective. The aim of this study is to determine the effective factors on shallow landslide occurrence and investigation of Statistical Index Method (SIM) efficiency for landslide susceptibility mapping. So, determination of each class of factors’ weights was accomplished by using SIM. That was done by adoption of inventory landslide map and ten initial factors including: slope, aspect, rainfall, altitude, drainage density, plan curvature, land use, geology, geomorphological faces and rock unit sensitivity to erosion in ArcGIS 9.3. Then model efficiency was evaluated by using percentage of area under ROC curve and the results showed high accuracy (0.95) of SIM. Principal Component Analysis (PCA) was used for determination of primary causative factors of shallow landslide occurrence. Results showed that five variables of rainfall, slope, aspect, rock unit sensitivity to erosion and plain curvature are the most effective factors on landslide occurrence, respectively.
