This research is concerned with the LANDSLIDE susceptibility of Khoramabad area using Geographical Information System (GIS). LANDSLIDE susceptibility ZONATION (LSZ) is able to identify areas prone to failure based on the characteristics of past events. Satellite data, topographic maps, field data, and other informative maps were used as data layer in this study. These data layers are including lithology, slope, aspect, land use, distance from fault, distance from road and density of river. A numerical rating scheme for the factors was developed for spatial data analysis in GIS method. The resulting LANDSLIDE susceptibility map delineates the study area are located into different zones of susceptibility classes including high, moderate and low. Based on the prepared LANDSLIDE hazard ZONATION map some 32% of the study area shows high LANDSLIDE susceptibility.

Sattarkhan Dam is constructed on Aharchai Stream in 15 km west of Ahar in East Azerbaijan province. Considering the susceptibility of the dam to LANDSLIDE hazard, it is critical to determine factors effective on such natural phenomena in this area. Different methods are applied to identify places with high LANDSLIDE susceptibility in order to prevent and reduce causalities of such natural phenomena. In this investigation, two methods including Overlap Index and Analytic Hierarchy Process (AHP) are implanted for LANDSLIDE hazard ZONATION. In this regard, first, the map of LANDSLIDE occurred in the area was prepared using the available LANDSLIDE occurrence maps, images, and field studies. Next, the thematic maps and then the associated susceptibility maps were prepared in GIS using eight effective factors including lithology, slope angle, slope direction, land use, average monthly rainfall, distance from faults, distance from streams, and elevation. The role of these factors was divided into several classes and the weight of each class was assigned to the corresponding raster layer and classes of each layer. Based on the obtained results, the study area was divided into four zones with different LANDSLIDE occurrence HAZARDS by overlapping different layers in GIS environment and preparing LANDSLIDE occurrence hazard. The data evaluation and processing show that around 38% and 4% of the area is located in zones with high and very high LANDSLIDE occurrence hazard, respectively. The result also reveals the susceptibility of the study area to such natural phenomenon, which must be considered in the dam lifetime for preventing damages and causalities.

Natural HAZARDS cause every year around the world, including Iran harmful damages. A Vark basin in the Lorestan province due to a variety of geological properties such as lithology, tectonic and climatic conditions, is taken as areas with potential environmental risks into account. To reduce the damage caused by these risks, earliest and foremost task is to determine areas with high potential risk. In order to evaluate environmental HAZARDS in this basin, each informational layer has been identified and registered using the satellite images ETM+ (2016 year), geological maps, topographic maps and field visits (2017 year). Then, using the informational layers of the slope, aspect, elevation, land use, geology, the epicenter of the earthquake, fault, drainage and rainfall in ArcMap software and based on an AHP-Fuzzy method of the map, the risk of LANDSLIDE, floods, erosion and earthquake have been prepared. In this study, in order to map the environmental risks using expert judgment, the Quartet HAZARDS of the region were weighted and then overlapped. Based on the results achieved, 9.03, 20.84, 27.68, 27.41 and 15.03 percent of the area ranked at-risk classes very low, low, medium, high and very high respectively. The results of the environmental risk map of the region show that LANDSLIDEs and flooding are a larger role in the creation of high-risk zones.

Instability of the slopes including the risk of LANDSLIDEs, are major HAZARDS due to the nature of the mountainous regions with great abundance. Of course, if this risk be accompanied with other risks such as earthquakes and floods produce a wider range of severity. Binalood mountainous zone is due to expanded shale and Hyalite formation, sensitive and high intensity land use and other anthropogenic activities have a particular sensitivity of LANDSLIDE HAZARDS. The Frizzy basin with large area in the context of two different types of litho logy Hyalite and lime has a special situation. In this article we use AHP model and fuzzy logic to LANDSLIDE risk assessment in the Frizzy basin. Total of 15 criteria associated with the occurrence of major LANDSLIDE phenomenon was analyzed. Each of these measures as a factor map, separately classifieds and statistical methods were rate. Production of final map for LANDSLIDE hazard ZONATION in the basin firstly showed that about 68 percent of the total area of the basin has critical and medium LANDSLIDE hazard. Secondly, has been determined that the Hyalite variable have high significant (R2=0.835), compared to other formations in the basin and has a stronger correlation with the dependent variable of LANDSLIDE. The GPS data have been determined a high level of compliance with the used technique based on fuzzy logic. Also the model application demonstrates a good suitability for slopes instability zoning in mountainous basins.

Identification of Regions Having Potential for LANDSLIDE Occurrence is One of The Basic Measures in Natural Resources Management. Different LANDSLIDE Hazard ZONATION Models are Proposed Based on The Environmental Condition and Goals. Nowadays in Countries Involved With LANDSLIDE Problem, There is an Increase Trend to Evaluation and ZONATION of Risk and dDamage of This Phenomena. Existing LANDSLIDEs As Earth Evidence Was Identified and LANDSLIDE Inventory Map Was Provided. Factors Layers As Geology, Slope, Aspect, Distance From River, Istance From Road, Distance From Fault, Land Use, Rain and Elevation in Arc-GIS Software Was Provided. The LANDSLIDE Hazard ZONATION Maps are Based on The Information Value, Certainty Factors and Multiple Regressinon Models in Arc-GIS Environment Provided. The Level of Similarity Potential Hazard Figures of These Models Were Compared With The LANDSLIDE Inventory Map in The SPSS Environments. Results of Research Showed That There are a Significant Correlation between the Potential Hazard Figures with the Area of LANDSLIDEs in Three Models. The Multiple Regression Model Have Hieghest Correlation in This Watershed So Multiple Regression Modl is The Best Model for Application in The Bagh Dasht Watershed.

LANDSLIDEs are major natural HAZARDS which not only result in the loss of human life but also cause economic burden on the society. Therefore, it is essential to develop suitable models to evaluate the susceptibility of slope failures and their ZONATIONs. This paper scientifically assesses various methods of LANDSLIDE susceptibility ZONATION in GIS environment. A comparative study of Weights of Evidence (WOE), Analytical Hierarchy Process (AHP), Artificial Neural Network (ANN), and Generalized Linear Regression (GLR) procedures for LANDSLIDE susceptibility ZONATION is presented. Controlling factors such as lithology, landuse, slope angle, slope aspect, curvature, distance to fault, and distance to drainage were considered as explanatory variables. Data of 151 sample points of observed LANDSLIDEs in Mazandaran Province, Iran, were used to train and test the approaches. Small scale maps (1:1,000,000) were used in this study. The estimated accuracy ranges from 80 to 88 percent. It is then inferred that the application of WOE in rating maps’ categories and ANN to weight effective factors result in the maximum accuracy.

Introduction: LANDSLIDE is a natural phenomenon that occurs due to falling down or movement of sediments materials along the hillsides. Velocity and wideness of the phenomenon cause attractive & tragedy one, which can affect on thousands of cubic meter of soil & stone. This phenomenon is the most Common natural earth change phenomena that occur in the geological period which is nowadays known as natural disaster. In present decade its importance is considered to deal with natural disaster and to reduce its risk. One of the important objectives of this research is to identify different parameters in LANDSLIDEs of sensitive area. This project also aims to identify high risk area and low risk area of LANDSLIDE in order to reduce harmful effects LANDSLIDE. Therefore, nowadays we need to provide LANDSLIDE hazard ZONATION in sensitive areas with unstable hillside because every year it causes huge damages. Therefore, research is necessary for which different methods that give acceptable results by the researchers such as systematic or map query from which statistical method is chosen. In this research, Marbor river basin is zonated by using two variants statistical method which includes value of information and density area.Methodology: In order to prepare the hazard ZONATION LANDSLIDE map, it is necessary first to prepare the distribution map of LANDSLIDE in the region. This is done by field study and using geological maps, topographic maps, digital elevation model (DEM) and land use maps using Ilwis software. The obtained data is then transferred to I1wis software and six information layers such as slope, lithology, rainfall, land use, and distance from roads were used. These layers were then intersected, and classified LANDSLIDE hazard ZONATION map with 2 statistical method.Discussion: This research attempts to zonate the Marbor River domain in the south of Semirom city with an area of 1438 km2 using Binary statistical method because of increasing instability of the slopes and LANDSLIDE phenomena, to prevent it from human and financial damages. Therefore, by collecting required information on LANDSLIDEs dispersion in the region, LANDSLIDE dispersion map is provided by preparing six informative layers which includes slope, aspect, lithology, landuse, distance from the road, and precipitation rate. These layers were then intersected, and classified LANDSLIDE hazard ZONATION map with Binary statistical method. These methods contain: 1) Information Value This method is based upon the following formula: Wi=Ln (Densclass/Densmap)=Ln(Npix(Si)/Npix(Ni))/(Npix(Si)/ ∑npix(Ni)) where, Wi = the weight given to a certain parameter class (e.g. a rock type, or a slopeclass). Densclas = the LANDSLIDE density within the parameter class. Densmap = the LANDSLIDE density within the entire map. Npix(Si) = number of pixels, which contain LANDSLIDEs, in a certain parameter class. Npix(Ni) = total number of pixels in a certain parameter class. 2) Density Area D=Nix (Sxi)/Npix(Xi) W=1000*(D-(∑Npix(Sxi)/ ∑Npix(Xi)) Afterwards, we analyzed the accuracy and precision of each method (P, QS). For the analyses and accuracy of the used method, two equations of accuracy and precision are used which are P method and QS method, and to compare the accuracy and precision of the two maps in linear regression and audit analysis, the best method is chosen. These relations are shown: (P) method''s accuracy: Area of land slide in medium and high hazard zone is divided by their area as shown by the correlation: P=KS/S where, P is method's accuracy in medium and high hazard zones, KS is the LANDSLIDE area in medium and high hazard zone and S is the related hazard zones area The (QS) method''s Precision is obtained by density ratio as shown in this equation: DR = percent of LANDSLIDE / percent of area QS=_(DR-1)2*Area(%) The result showed the Infomation value is better than other method for this region.Conclusion: 1. Using hazard ZONATION map of LANDSLIDE we can design road networks, technical structures, power lines, gas, etc, in sustainable zones and reduce damage 2. Map prepared by Information value method is an appropriate for LANDSLIDE hazard ZONATION in this area 3- The factors studied show maximum of LANDSLIDE Have occurred in 12-25 slope, South East, Daryan formation, 500-700 rainfall and and with 0-1500 metter distance to road. 4- Avoid building structures near the river. because in this area has high potential for occurrence LANDSLIDE. 5- East and South East region have minimum potential for occurrence LANDSLIDE.

It is very important to recognize the areas with high potential risk of LANDSLIDE in order to resist that. In a case study, thirty three LANDSLIDEs have been observed in Safarood watershed. The purpose of this study is to recognize factors and ZONATION of potential areas for LANDSLIDE. This paper covers specific factors including lithology, fault, height, slope, direction, rainfall, soil, vegetation and villages of the area. GIS is used to prepare and integrate thematic layers, combine them by weight model and finally to prepare a map of LANDSLIDE hazard. AHP statistic method is used for weighting the criteria. The criterion for weighting the existing elements in each layer has been based on the most important role played in the layer and in LANDSLIDE. after combining various layers in GIS medium, the map of LANDSLIDE hazard ZONATION is obtained in four ZONATION with every high hazard, high hazard, medium and low hazard. It has been determined that approximately 31% of the surface of the area is encountered very high and high hazard LANDSLIDEs. 94% of the cases observed in LANDSLIDE, based on the mentioned ZONATION and the model, are in the ZONATION of very high and high HAZARDS that show the high accuracy of this method.

LANDSLIDEs are one of the most important slope movements. One of the LANDSLIDE-prone areas is the area around the dams and their lake, which may cause damage to the dams. The purpose of this study was to identify areas prone to LANDSLIDEs in the area of Shahid Abbaspour Dam, Northern Khuzestan, Iran. This research was conducted using two methods of Hayeri-Samiei and Analytical hierarchical Process. Based on this, seven factors including lithological, slope angle, fault length, road and river length, rainfall factor, rainfall intensity and earthquake were prepared. In the Hayeri-Samiei model, these seven factors are investigated and the obtained weight of each of them is placed in the general equation and in the GIS environment is converted into a ZONATION map and potential areas in the range are identified. In the Analytical hierarchical Process method, based on pairwise comparisons between the seven factors mentioned, considering the opinion of experts, the weight of each factor is obtained and in Expert Choice software, pairwise comparison is performed and the final weight is obtained. After studies in two methods, the most LANDSLIDE-sensitive areas are in Quaternary young alluvium and lithological factor is the most important factor in the study area. In general, high-risk areas are in the southwestern part of the dam and a small part in the north. In AHP model, like Hayeri-Samiei model, the lithological factor has the greatest effect on LANDSLIDEs in the region. Gachsaran Formation also has very low resistance to LANDSLIDEs after Quaternary alluviums. In terms of slope angle, areas located at slope angles of 36-45 are prone to LANDSLIDE.

Forest road networks are essential structures to achieve the forestry aims, but these structures include most implemental and environmental costs. To minimize these costs, the effective factors have to be considered in forest road design which LANDSLIDE susceptibility is one of the major factors. Road construction on susceptible terrain increase road maintenance cost and environmental impacts. LANDSLIDE hazard ZONATION is a method that can be applied to recognize and avoid the unstable terrain. In this research, the LANDSLIDE hazard ZONATION map of Baharbon district in Kheyroud Research Forest was developed using a combined model, AHP and Density Area methods. First, LANDSLIDEs distribution map of study area was prepared in ArcGIS using field observations and then the map of effective factors in LANDSLIDE occurrence were prepared. To determine the weight of effective factors AHP was used. Afterward a bivariate statistical model, Density Area, was used for calculating the weight of classes of effective factors maps. By combining the effective factors maps and classifying the combined map with regard to breakpoints of frequency curve, the LANDSLIDE hazard ZONATION map was developed. According to the results, 14.7%, 26.9%, 38.9%, 15% and 4.5% of the district were classified as very low, low, moderate, high and very high hazard, respectively. Finally due to lack of LANDSLIDE occurrence in slope class of 0-15%, as well as it is suitable slope for road design, this class was suggested as positive control points. The other slope classes that were in low and very low hazard were defined as second priority for road design. Road building in high and very high hazard is possible, if increasing the number of culverts, also biological and mechanical reinforcements of cut and fill slopes.