Various spatial instances and outcomes can be shown for every social phenomenon in the urban arena, and this indicates the spatial behavior of social phenomena. The examination of suchlike phenomena from the viewpoint of correlation and synergy reveals the existence of an interactional pattern among them. In this article, it is tried to provide a brief description of the spatial distribution of variables related to social harms such as joblessness, addiction, etc., in the form of spatial statistical analysis. The research method is descriptive-analytical, and it can be categorized as an applied study. In terms of data collection method, the study adopted library research. In order to analyze the data, we used spatial statistics tests in ARC GIS. In the light of the spatial structure of the social class and the spatial pattern of the variance of the rich and poor areas of Tehran, it was found that poverty and dispersion are among the main stimuli of the concentration of various social harms in poor neighborhoods.

In recent years, the infrastructure systems have been mostly failed due to the increase in natural or manmade disasters as well as the internal and external dependencies among system components. The mutual infrastructure dependencies might cause more vulnerability and bring about cascading failures. The main objective of this study was to develop scenarios of geographic interaction in critical infrastructure during urban hazards in Ahvaz. The study was developmental-applied in terms of purpose, while in terms of methodology, it was descriptive-analytical done based on field study and document analysis. The study indices were extracted and related via combining the results of expert opinion and existing records. To develop scenarios, after identifying the variables, the key factors affecting each topic were specified, and then various conditions were defined for each variable. The identification of driving forces in Ahvaz infrastructures interaction was done using models such as “cross-impact analysis” using MICMAC software. In order to identify, analyze, and adopt selected scenarios, cross-impact balance analysis was run in ScenarioWizard software. The inspection of scenario screen in ScenarioWizard software showed that from among 80 existing settings of critical infrastructure spatial interaction drivers, 26 cases (32.5 percent) were in statistic form and 25 cases (3.125 percent) in critical conditions.