Zoning of Landslide Hazard Using Entropy Model, (Case study: Nesar Anticline at North West Zagros)

Introduction
Entropy not only quantifies the quantity of energy but also quantifies the quality of energy and this quality is the measurement of disorder in a system (Mansly and Colleages, 2008: 145). In summary entropy in the meaning of quantification, discuss the disorder between causes and results and decisions in different topics (Van, 2009: 238).
Geomorphologic hazards as a threat cause a lot of damages to human societies. In this concept natural disaster is a harmful element that exists in the physical environment for human (Ayla, 2002: 408). Landslide as one of the geomorphologic hazard cause lots of destructions as direct and indirect costs and plays an important role in destructing human facilities and causes human death, forest destruction and sedimentation in watershed basins. Identifying and classifying the areas that are vulnerable in sliding and its danger has an important role in identifying environmental hazard.
According to destructive landslides that happen near Nesar anticline, the location of villages and City of Gilan-Gharb and development facilities in amplitudes anticline, it is necessary to provide the landslide map of the area for better management.
The purpose of this study is to quantify the occurrence of Nesar anticline landslides and also to know the amount of each five factors in landslide occurrence. It is also determined to provide the map of landslide risk by using entropy model. Finally the last aim of the article is to propose scientific management ideas of the area against landslide hazard.

Methodology
At first, by using visual interpretation of IRS satellite images, landslides of the studied area were identified. Then, by studying occurred landslides in the area with five factors: litho logy, distance from faults, slope topography, the slope and elevation were defined as effective factors in the landslide occurrence and five informational layers came in as raster data and the amount came in identity.
According to the landslide features of the area (shown in table 1), weights were given to the layers and then the entropy matrix were completed (Table 2). Decision matrix contains information in which entropy can be used as a criterion for evaluating it. After calculating the entropy matrix and the whole weight of five factors? w?_j, the amount of Hi which is the landslide risk occurrence was achieved and decisions were made to area based on landslide occurrence.

Results and Discussion
Finally, based on the landslide occurrence zoning map and area features analysis, some management ideas as basically and scientifically were given. The data container existed in matrix was generated as Pij and for every five elements the amount of Ej was calculated and after area model the amount of landslide risk in the area was generated as below: H=0 G+0.24987 S+,0.238713 DF+0.403101 E+108334 A that H: the risk of landslides in the area. G; lithology, S; slope, Df; distance from the fault, E: elevation and A is the slope. Based on the above relationship, map of landslide hazard zoning was prepared in the studied area (figure 4). As it has been mentioned in Table 3, areas with medium and high risk consist 98% of the area was suggested to have the high risk area in terms of landslide risk.
According to entropy model calculations based on distance, elevation, slope, fault distance, aspect and lithology had the greatest effect in the landslide occurrence in the area. High incident risk areas are located in high elevated places of anticline. These areas have the highest slope and the height and are located in territory of fault area and in territory of Asmari formation. Moderate-risk zone as longed tape has taken middle parts of anticline and has allocated most of the area. This area has a large slope and the classes of less than 1500 height and lithology Asmari formation has got the most places in this area. Low risk zone in the northern and southern anticline are in classes less than 1100 meter, and is based on the consistent of the soft match’s formations of the area including quaternary, low slope and a high distance of the faults in the area.

Conclusion
Final precision zone map with occurred landslide occurred in the study area shows that the 33.33% pitch slips occurred in the moderate risk zone, and 66.66% of landslides were located in high risk zones. This suggests optimal performance of the entropy zoning model in landslide hazard zonation. About 1.93 percent of the region across the low risk and 58.26 percent of the region across the moderate risk zone, and 39.8 percent are located at high risk. Finally, we can conclude that the studied area is a high-risk area. The factor of altitude with amount of 40% had maximum role and the lithology has no effect on landslides risks of occurrence. To manage the hazards of the area these two ideas are suggested:
Preparing landslide hazard zoning map of the region and preventing development activities at the margins of less than 2 km from anticline.
Prevention of excavation operations and watershed operations in the anticline as accelerating factors of the landslides.