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Open Access Article
1 - Evaluation of the efficiency of artificial intelligence and bivariate statistical models in determining landslide prone areas in West Azerbaijan
Azad Aram Mohammad Reza Dalalian Siamak Saedi Omid Rafieian Samad DarbandiBackground and Aims: Landslide is one of the natural hazards that lead to a lot of human and financial losses. Researchers on the subject of landslide susceptibility are investigating the possibility of landslides with respect to topographic and geo-environmental condit MoreBackground and Aims: Landslide is one of the natural hazards that lead to a lot of human and financial losses. Researchers on the subject of landslide susceptibility are investigating the possibility of landslides with respect to topographic and geo-environmental conditions, and the obtained information is critical in landslide risk management Preparation of landslide sensitive points is an essential tool for assessing landslide risk and is very useful in better planning and management of these areas. In this research, models based on artificial intelligence and two statistical variables in determining landslide sensitive points in West Azerbaijan province have been studied and compared.Methods: Methods based on artificial intelligence and two statistical variables were used to prepare landslide-sensitive points in the province of West Azerbaijan, which is located in northwestern Iran. This study was conducted in four stages. The first stage: the study of landslides in the studied region based on the database of the Forests, Rangelands and Watershed Organization of Iran (FRWO) and the identification of 110 landslides through field surveys, interpretation of aerial photographs and Google Earth satellite images, the second stage: data collecting and creating a spatial databases of effective factors, the third stage: applying the Frequency Ratio (FR), Shannon Entropy (SE), Bagging (BA), Random Forest (RF) and hybrid model (RF-BA) and stage four: methods validating using the system performance curve (ROC). Based on field surveys and similar studies, 12 factors affecting landslide occurrence including altitude, slope angle, slope direction, distance from fault, distance from river, distance from road, drainage density, road density, rainfall, soil, land use and lithology were identified. In the field survey, 110 landslides were identified in West Azerbaijan. 70 percent of the data were randomly selected and used for modeling and 30 percent of the data were used for validation.Results: In terms of geographical directions, the southern direction with a weight of 1.49 had the greatest impact on the occurrence of landslides in the province. The least weight was related to flat areas where no landslide occurred. The results of slope factor showed that the middle slopes had the greatest effect on the occurrence of landslides, so that in low slopes due to low gravity, less landslides occur and too much slopes were related to mountainous areas that were covered with rocks and there was very thin soil that is not suitable for landslide. The study of land use factor showed that 48 percent of landslides occured in agricultural areas. The results showed that most of the landslides occurred near rivers and faults. Also, in some areas, the closest distances to the road had the greatest risk of landslideConclusion: The results of this study showed that the artificial intelligence models (RF and the combined model RF-BA) had the higher efficiency than the statistical models (FR and SE). The accuracy of the combined models was higher than the single models. The ROC curve results showed the accuracy of 0.92, 0.91, 0.89 and 0.88 with RF-BA, RF, FR and SE models, respectively. Manuscript profile -
Open Access Article
2 - Landslide susceptibility mapping using frequency ratio, logistic regression and AHP models in the part of Golestan province
Majid Mohammady Shantia Jamal Arman MansooriBackground and objective: Iran is always exposed to landslide hazard especially in the north because of climatic and topographic conditions. Identification of landslide prone areas and its hazards is one of the first works in natural resources management and development MoreBackground and objective: Iran is always exposed to landslide hazard especially in the north because of climatic and topographic conditions. Identification of landslide prone areas and its hazards is one of the first works in natural resources management and development programs. Policymakers pay high attention to landslide investigation in order to landslide susceptibility mapping and identifying susceptible areas and stable locations for development of new settlements in the future. The main goal of his research is landslide susceptibility mapping in the part of Golestan province.Material and Methodology: 78 landslides were identified from the field surveys in the part of Golestan province, and then landslide inventory map was created in year 2016. Effective factor maps such as slope degree, slope aspect, plan curvature, altitude, lithology, land use, distance from road, distance from fault, distance from drainage and slope-length (LS), were prepared in the GIS environment. Three methods such as analytical hierarchy process, frequency ratio and logistic ratio were applied to landslide susceptibility mapping. Also ROC curve was used to accuracy assessment of susceptibility mapsFindings: prioritization of effective factors using AHP showed that distance from road, slope, distance from drainage and distance from residential area have the most effect on landslide occurrence. Landslide susceptibility map obtained from three models was compared using Relative Operating Characteristic (ROC) and Area under Curve (AUC). The result showed that frequency ratio model with the AUC equal to 0.8 has the most accuracy to landslide susceptibility mapping.Discussion and Conclusion: In general, the results showed that the study area has a high potential for landslides occurrence. Identifying susceptible areas help to prevent changes in the natural state of these areas as much as possible. Manuscript profile -
Open Access Article
3 - Groundwater resource potential of Azna-Aligoudarz plain using environmental variables and frequency ratio (FR) model
Samira Ghorbani Nejad Mania Daneshfar Omid Rahmati Fateme Fallah Ali Haghizade Naser TahmasebipourPopulation increase and excessive use of different water resources, has led to special attention to groundwater resources. In this study, the efficiency of frequency ratio model in groundwater potential mapping in Azna-Aligoudarz plain, Lorestan was investigated. The 11 MorePopulation increase and excessive use of different water resources, has led to special attention to groundwater resources. In this study, the efficiency of frequency ratio model in groundwater potential mapping in Azna-Aligoudarz plain, Lorestan was investigated. The 11 effective groundwater potential factors, (altitude, lithology, curvature, slope, aspect, land use, distance from rivers, drainage density, fault distance, fault density, pedology, topographic wetness index; TWI) were prepared using GIS. The location of 370 wells in the study area with discharge more than 11 (m3/h) was choosed and were divided in two groups of training (70%) and validation (30%) wells. Then the layers of environmental variables were classified and based on the density of wells and frequency ratio model, the weight of each class was determined. Finally, the groundwater potential map was prepared based on the frequency ratio model. Validation of final map was performed using relative operating characteristic (ROC) method. The result shows that the generated groundwater potential map using frequency ratio with 72.1% accuracy value, showed the high ability of this model in groundwater potential mapping. The groundwater potential map of the region showed that classes with a low, moderate, high and very high potential have been estimated to be 210.79, 210.24, 210.29 and 209.24 km2, respectively. Manuscript profile -
Open Access Article
4 - Landslide hazard zoning using frequency ratio, entropy methods and TOPSIS decision-making methods (Case study: Fahliyan basin, Fars)
SEYED VAHID RAZAVI TERMEH Kourosh ShiraniDistinguishing the susceptible areas to landslide using appropriate experimental models of landslide susceptibility mapping is one of the primitive and basic works to reduce probable damages and reduce risk in country's watersheds. In this research, thirteen factors, in MoreDistinguishing the susceptible areas to landslide using appropriate experimental models of landslide susceptibility mapping is one of the primitive and basic works to reduce probable damages and reduce risk in country's watersheds. In this research, thirteen factors, including altitude, slope, aspect, rainfall, plan curvature, profile curvature, Topographic Wetness Index (TWI), Stream power index (SPI), distance from the river, distance from road, distance from the fault, lithology, and land use are identified as effective parameters in landslide occurrence in the studied area. The landslide landslide distribution map was prepared using Landsat 2017 satellite imagery and Field studies (2017). Then, the landslide susceptibility mapping was performed with three methods, including frequency ratio, entropy and TOPSIS. The results were evaluated using receiver operating characteristic (ROC) curve. The area under the curve (AUC) of applied models shows the accuracy of 84, 87.7, and 91 percent for entropy frequency ratio and TOPSIS models, respectively. The results are indicative statistical models have a better accuracy in comparison with MCDM models and expert approaches. The results of the present study could be useful for better managing the flood affected areas and to reduce its damage. Manuscript profile -
Open Access Article
5 - Landslide hazard zonation using the Frequency ratio model and fuzzy logic (Case Study: Central Section of Jam Township)
amir safari monireh Rayati Shavvazi maryam Jan Ahmadi laila Shirzad Malayeri -
Open Access Article
6 - Evaluation of the efficiency of Haeri-Audio experimental model and bivariate statistical in landslide risk zoning (Case study: Qazvin province)
Faramarz Sarfaraz Jamal Mosafaei Rohangiz Akhtari Amin Salehpour JamLandslides are one of the most destructive types of erosion on slopes, which causes a lot of financial and human losses. The purpose of this study is to evaluate the efficiency of landslide potential zoning models in Qazvin province and to provide management strategies MoreLandslides are one of the most destructive types of erosion on slopes, which causes a lot of financial and human losses. The purpose of this study is to evaluate the efficiency of landslide potential zoning models in Qazvin province and to provide management strategies to reduce landslide risk. The proposed relationships of this model were used for the Haeri-Samiei experimental model. For the statistical model, after preparing the layers of effective factors (land use, slope, slope direction, height, etc.) and cutting them with a landslide distribution map, the area and percentage of landslide in each floor were determined from the effective factors map. Then, using the frequency ratio, the importance of each class of effective factors was calculated and a map was prepared based on the importance of effective factors in the GIS environment. Finally, to prepare a landslide hazard map, the maps were grouped together based on the rate of factors and classified according to the method of intervals equal to seven floors. Density ratio and total utility indices were used to evaluate the efficiency of the models and select the superior model. The results showed that the bivariate statistical model with Qs equal to 0.938 has a higher accuracy than the Haeri-Samiei model with Qs equal to 0.622. To reduce damage and manage landslide risk, three non-action management policies for low risk classes, prevention for medium risk classes and treatment for high risk classes were considered and some necessary measures were provided for each management policy. Manuscript profile -
Open Access Article
7 - Landslide Risk Zoning using Frequency Ratio Model (Case Study: Fathabad Rectangular Map Area, Lorestan Province)
Siamak Baharvand -
Open Access Article
8 - Multihazard Rangelands Susceptibility Mapping (Drought, Flood, and Fire) in Siah Bisheh Watershed in North of Iran
Soodeh Miarrostami Hossein Arzani Seyed Akbar Javadi Mohammad Hassan Jouri -
Open Access Article
9 - Landslide Susceptibility Mapping for Subalpine Grassland Using Frequency Ratio and Landslide Index Model (Case Study: Masoleh Watershed, Iran)
Mohammad Hasan Jouri Mohammad Zare Diana Askarizadeh Mona FakhreGhazi Tina Salarian Soodeh Miarrostami
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