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.

The risk of earthquake always influences the human communities and inflicts irreparable damages to them. Therefore, preparation against this crisis through the identification and elimination of vulnerable parts is effective in reducing the damages of earthquakes. As Iran is located on one of the two major seismic belts of the world and has many faults, the occurrence of earthquake in the Iranian plateau is natural. Iran is among the top ten countries with the highest rates of earthquakes. Urmia city, which is located on the skirts of Zagros mountain range, is not an exception in this regard, and every year many earthquakes with different intensities occur in this city. Therefore, in order to confront the foregoing issue, we need precise studies regarding construction and safety. In this study, to evaluate the rate of vulnerability to earthquakes, the effective parameters were identified and then were weighted using fuzzy hierarchical analysis. The vulnerability map was prepared using index and fuzzy logic overlay method for Urmia statistical blocks and was presented in the spatial information system environment. The obtained results indicated the vulnerability of nearly 50 percent of the city area to earthquake (i.e., 151574 m2), with .005 percent having a very high vulnerability grade and .40 percent (i.e., 11538359 m2) a high vulnerability grade to earthquake.

This study aimed at evaluating the supervised pixel-based classification of the maximum likelihood in the examination of the climactic changes of the Urmia Lake catchment area in 1-, 6-, 10-, and 14-year spans and then evaluating and modeling the changes in the gardens neighboring Lake Urmia during a 30-year span and its role in the changes at Lake Urmia water level. In this study, first the Landsat images of the years 1990, 2000, 2014, 2020, and 2021 were downloaded. Then, using the ENVI5.3 software, a classification was made based on the maximum likelihood method. Next, the IDRISSI TERRSET software and CA-MARKOV model were used to model conditions for the year 2051. This model was then analyzed in the GIS software. It was found that the classification based on the maximum likelihood method has been an appropriate one. The results of this classification showed that overall, the maximum changes from 1990 to 2021 has been related to the irrigated gardens and fields. In this period, 3495 square kilometers have been added to these lands, i.e., the number has doubled. Modeling the 2051-year conditions in the light of the transition probability matrix showed that the maximum likelihood of land use changes is in the irrigated garden and farm use. On the other hand, the modeling in this study indicated that there has been a reduction in the expanse of irrigated gardens and fields as well as salt lands in the region. Finally, the model predicted an increase in water area in 2051.

The progress of smartening cities on the one hand and the requirements of urban sustainability on the other hand have paved the way for transition to the sustainable smart city. The study at hand was carried out to present an optimal model of smart city from the viewpoint of sustainable urban development. This study was an applied research project in terms of purpose and a cross-sectional survey in terms of research method and data collection timespan. The statistical population included urban management managers and experts. The optimal sample size was determined to be 384 using Morgan’s table and the participants were selected via simple random sampling method. The data was collected through a questionnaire that had been validated through construct, convergent, and divergent validity measures. Using Cronbach’s alpha and combined reliability measures, the dependability of the questionnaire was confirmed. To validate the smart city model from the viewpoint of sustainable urban development, the partial least squares regression and Smart PLS software were used. According to the obtained results, the smart urban infrastructure and smart governance are the two cornerstones of the model that have the strongest effects on the creation of a smart city based on sustainable development. The effectiveness rate is decreased in the subsequent levels and the variables at the same level show mutual interaction. By affecting the smartening of transportation and influencing the technology-based smart businesses, these factors lay support to smart economy and environment. Then, through smart structures and smart people, the sustainable urban development can be attained, which in turn leads to smartening the city.