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Saeed Fathi, Ph.d. Ali Mohammad Khorshiddoust,
Volume 8, Issue 1 (5-2021)

Zoning and Spatial Analysis of Potential Environmental Hazards
Case study: Silvana District
Natural hazards can be considered as one of the most important threats to humankind and nature that can occur anywhere in the world. Natural hazards are one of the main obstacles to sustainable development in different countries and one of the important indicators of the development of world countries is their readiness to deal with natural hazards. Therefore, it is important to pay attention to it and appropriate measures should be taken to reduce the vulnerability of human settlements. Nowadays with increasing population growth, population dynamics and the large number of people exposed to various types of disasters, the need to identify environmental potential hazards and identification of hazardous areas are felt more and more. Meantime, some people may not be aware of potential hazards of their place of residence. So by identifying and evaluating potential hazards and their Risks before the occurrence, we can significantly reduce the severity of the damages and contribute to sustainable regional development. The negative effects of natural disasters can be minimized by the availability of comprehensive and useful information from different areas and Multihazard mapping is one of the most effective tools in this regard.
According to the above mentioned, in this study, the spatial analysis of potential hazards in Silvana district in Urmia County has been studied. This study area due to specific geographic conditions such as position, complexity of topographic and ecological structures, in general, the existence of environmental factors for hazards has been selected as the study area. There have been a number of hazards in the past and assessing of this area is necessary, because of the lack of previous studies. For this purpose, by reviewing various reports and doing field observations, three hazards including Flood, Landslide, and Earthquake are identified as potential hazards of the study area.
For assessing hazards, 12 factors in 6 clusters such as Slope, Aspect (Topographic factors), Lithology, Soil type, Distance to Faults (Geological factors) Precipitation (Climatological factors), River Network Density, Groundwater Resources (Hydrological factors), Land use, Distance to Roads (Human factors), Observed Landslide Density and Seismicity (Historical factors) as the research factors has been selected. For weighting factors, Analytic Network Process (ANP) Method in Super Decisions 2.6.0 software environment has been used. The results of the analysis show that Slope (0.201), Precipitation (0.161), Lithology (0.112), Distance to Faults (0.106), Land use (0.096), Rivers (0.078), Seismicity (0.06), Soil Type (0.055), Landslide Density (0.047), Aspect (0.033), Groundwater (0.03) and Distance to Roads (0.016), Respectively have maximum to minimum relative weight. Then, weighted maps are standardized with using FUZZY functions. For this purpose, Fuzzy membership functions such as Linear, Large and Small has been selected based on each factor. For some factors such as Slope, Aspect, Lithology, Soil type, Rivers density, Land use, Seismicity and Landslide density, Fuzzy linear function has been used. For some others such as Groundwater and Precipitation, Fuzzy large function has been used and for distance to Faults and distance to Roads, Fuzzy small function has been used. Finally, weighted maps were overlay in ArcGIS 10.4.1 environment with Fuzzy Gamma 0.9 operator and potential hazards zoning maps is obtained.
Final results indicate that major parts in the Northwest, West and South of the study area located in high risk zones and 59 percent of the total area exposed to high risk. Based on hazard zoning maps, 44 percent of the area exposed to Flooding, 48 percent exposed to Landslide and 44 percent exposed to Earthquake. Also, 61 percent of the population or 37394 people exposed to one hazard, 7 percent or 3817 people exposed to two hazard and 8 percent or 4914 people exposed to three hazard. According to surveys, only 21 percent of the study area is considered as a low risk area but that does not mean that environmental hazards will never happen in these areas. In general, and based on results, it is concluded that Silvana district has a high potential for environmental hazards. Final results of the research show that potential hazards identifying and preparation of hazard zoning maps can be very useful in reducing damages and achieving sustainable regional development. Therefore, considering the ability of hazard zoning maps to identify areas exposed to risk and assess the type of potential hazards, These analyzes should be considered as one of the most appropriate and useful tools in different stages of crisis management that can be the solution to many problems in preventing and responding to natural disasters and therefore, it is recommended that they be used in the crisis management process.
Keywords: Spatial Analysis, Environmental Hazards, Silvana, ANP Method, Risk
Maasoud Akhavan Kazemi, Parvanh Azizi, Mohammadbagher Khoramshad Khoramshad, Mohammad Abolfathi,
Volume 9, Issue 2 (9-2022)

New Social Movements: A Case Study of Emerging Environmental Movements

The term modern social movements is used to describe movements that were active in France in the late 1960s through collective action in the social sphere. The most important new social movements are the civil rights movement, the women's movement, the peace movement and the environmental movement. The rapid growth of industrial and capitalist societies, regardless of environmental degradation, has created many problems. The most important problems are soil erosion, resource reduction, ozone depletion, greenhouse effects, extinction of animal and plant species and various types of soil and climate pollution. The combination of these factors has provided the basis for the formation and activation of environmental movements. The present paper tries to answer the question of how emerging environmental movements can be analyzed in the form of new social movements? And what are their effects on new social movements? Therefore, with the qualitative interpretive method, and the method of case studies, it examines the nature and why of emerging environmental movements. The research findings show that environmental crises and the need to solve environmental problems that have become a pervasive and global crisis, have provided the basis for the formation, activity and impact of emerging environmental movements. Therefore, in order to deal with the existing crises, emerging environmental movements first informed and increased public awareness, and then created pro-environmental organizations and groups, and finally, by entering In the field of politics, and using new tools and methods, they have expressed their demands and protests in a peaceful and non-violent way, in order to force governments to respond and finally enter directly into The field of politics as influential groups and political parties in the field of public policy. As a result, the volume and scope of social power and the political influence of emerging environmental movements have led to the revitalization and enrichment of new social movements; in a way that today they can be identified and analyzed as powerful social forces and influential actors in the field of political sociology.

Keywords: New Social Movements, Emerging Environmental Movements, Social Forces, Methods of Action, Political Nature.

Dr Alireza Mohammadi, Dr Lotfollah Maleki, Mr Ghasem Fathi,
Volume 9, Issue 4 (3-2023)

Spatial analysis models provide a single model and solution to solve various problems in the field of study, one of the applications of these models is in measuring urban risks. In recent years, with the occurrence of various crises in urban communities, the urban management system and development plans are seeking access to models of prevention and dealing with these crises. The purpose of this research is to review the literature about the use of spatial analysis models in measuring urban risks in a meta-analytical way, so this research is conducted by reviewing and summarizing foreign articles (research statistical community) in relation to this issue in order to identify, analyze and Analyzing and summarizing the solutions of the investigated backgrounds.
The statistical population is discussed with four standard criteria of spatial analysis, including description and identification of hazard dispersion, hazard dispersion argument, interpolation, and spatial planning. The statistical population is research, studies, and articles indexed in Sciencdirect, Willey, Web of Science databases in the period 2021-2000. Out of 99 articles, 78 articles have been selected and analyzed by screening method according to research objectives and indicators. The analysis was performed in two ways: descriptive statistics in SPSS software and inferential statistics in CMA2 comprehensive meta-analysis software.
The results indicate that in the component of hazard dispersion descriptions, most of the researches in their used models have not been able to provide a tangible and appropriate general description, but in the three components of hazard dispersion, interpolation, and spatial planning of urban hazards based on score The average effect size, the applied models used in the research, have been able to provide a proper justification and tangible results with the applied model of spatial analysis in their studies.

Nazanin Salimi , Marzban Faramarzi, Dr Mohsen Tavakoli, Dr Hasan Fathizad,
Volume 10, Issue 3 (9-2023)

In recent years, groundwater discharge is more than recharge, resulting in a drop-down in groundwater levels. Rangeland and forest are considered the main recharge areas of groundwater, while the most uses of these resources are done in agricultural areas. The main goal of this research is to use machine learning algorithms including random forest and Shannon's entropy function to model groundwater resources in a semi-arid rangeland in western Iran. Therefore, the layers of slope degree, slope aspect, elevation, distance from the fault, the shape of the slope, distance from the waterway, distance from the road, rainfall, lithology, and land use were prepared. After determining the weight of the parameters using Shannon's entropy function and then determining their classes, the final map of the areas with the potential of groundwater resources was modeled from the combination of the weight of the parameters and their classes. In addition, R 3.5.1 software and the randomForest package were used to run the random forest (RF) model. In this research, k-fold cross-validation was used to validate the models. Moreover, the statistical indices of MAE, RMSE, and R2 were used to evaluate the efficiency of the RF model and Shannon's entropy for finding the potential of underground water resources. The results showed that the RF model with accuracy (RMSE: 3.41, MAE: 2.85, R² = 0.825) has higher accuracy than Shannon's entropy model with accuracy (R² = 0.727, RMSE: 4.36, MAE: 3.34). The findings of the random forest model showed that most of the studied area has medium potential (26954.2 ha) and a very small area (205.61 ha) has no groundwater potential. On the other hand, the results of Shannon's entropy model showed that most of the studied area has medium potential (24633.05 ha) and a very small area (1502.1 ha) has no groundwater potential.

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