نشریه تحلیل فضایی مخاطرات محیطی
سال یازدهم شماره 3 (پاییز 1403)

Dust storms affect different regions of the globe countries and Iran. The dust storm events were considered as one of the climatic components in arid and semi-arid regions and it is called one of the most important environmental problems of these regions. Therefore, in this research, the activity class of sand dunes were investigated based on the Lancaster index in Iranshahr city in Sistan and Baluchistan province. The aim of this study is to investigate the climatic different conditions on the mobility of sand dunes in Iranshahr city. Meteorological data for synoptic station of Iranshahr were collected from the Iranian Meteorological Organization for 15 years (2003 to 2018). After examining the wind speed velocity in Iranshahr, and extracting the seasonal and annual Wind rose diagrams, Dust Storm Index (DSI) was calculated.  Finally, the effects of possible changes in climatic elements on the mobility of sand dunes were predicted. The results showed a significant correlation between the Lancaster index and the amount of annual rainfall, wind and drought index. The results of the sensitivity analysis also showed that if the frequency of erosive winds and potential evaporation and transpiration increases to 30%, the activity of sand dunes in Iranshahr station increases by 25 and 23%, respectively, on the other hand, with a 30% increase in rainfall, the activity of sand dunes decreases by 30%.

Air pollution can have serious negative effects on human health, including cardiovascular and respiratory diseases. Monitoring and controlling air pollutants is very important to protect public health and the environment. Like many developing countries, Iran is facing air pollution, especially in its big cities and industrial cities. One of the powerful tools in air pollution monitoring is remote sensing methods. The aim of this study is to use relatively high-resolution satellite data to monitor air quality and air pollution using Sentinel-5 (Sentinel-5P) sensor images. In this study, a comprehensive monitoring based on the values of some of the most important air pollutants (including AI, O3, NO2, SO2, CH4 and CO) has been done using Sentinel-5 satellite images for Iran in 2019-2023. The results of this research showed that the emission of carbon monoxide and sulfur dioxide gases had a decreasing trend (in the months of June as an example of the examined month), but nitrogen dioxide gas, methane gas, ozone gas and aerosols had an increasing trend during the month. from June 2021 to 2023. In general, air pollution is more serious in the northern parts of the country, especially in big cities and several large urban gatherings. In this study, it was investigated how the levels of six air pollutants in Iran vary and differ from June 2019 to 2023. Another important result of this research is that the total amount of air pollution in 2020-2023 has faced an increasing trend compared to 2019. Also, the monitoring by Sentinel-5 satellite images shows that in recent years, Tehran has had the most polluted air in terms of carbon monoxide, nitrogen dioxide, sulfur dioxide and suspended particles (dust). Also, changes in the concentration of pollutants do not follow a specific pattern. It was also found that the GEE system is able to process a large amount of data in a very short time with high accuracy.

The growth of settlements and the increase of human activities in the floodplains, especially the banks of rivers and flood-prone places, have increased the amount of capital caused by this risk. Therefore, it is very important to determine the extent of the watershed in order to increase risk reduction planning, preparedness and response and reopening of this risk. The present study uses the common pattern of the machine and the classification of Sentinel 2 images to produce land cover maps, in order to construct sandy areas and determine land issues affected by the flood of March 2018 in Aqqla city. Also, in order to check and increase the accuracy of the algorithms, three software indices of vegetation cover (NDVI), water areas (MNDWI) and built-up land (NDBI) were used using images. The different sets of setting of each algorithm were evaluated by cross-validation method in order to determine their effect on the accuracy of the results and prevent the optimistic acquisition of spatial correlation from the training and test samples. The results show that the combination of different indices in order to increase the overall accuracy of the algorithms and to produce land cover maps, the forest algorithm is used with an accuracy of 83.08% due to the use of the collection method of higher accuracy and generalizability than compared to. Other algorithms of support vector machine and neural network with accuracy of 79.11% and 75.44% of attention respectively. After determining the most accurate algorithm, the map of flood zones was produced using the forest algorithm in two classes of irrigated and non-irrigated lands, and the overall accuracy of the algorithm in the most optimal models and by combining vegetation indices (MNDWI) was 93.40%. Then, with overlapping maps of land cover and flood plains, the surface of built-up land, agricultural land and green space covered by flood was 4.2008 and 41.0772 square kilometers, respectively.

The zoning of phenomena in order to recognize and evaluate the current situation as a basis for decision-making is one of the of scientific management essentials of natural resources. In the management of desert areas to prevent paying exorbitant costs and making incorrect decisions, strong and well-reasoned methods are needed to understand the current situation and the development process. Therefore, the main goal of the current research is to provide a suitable model for zoning the spatial distribution of desertification risk by using Moora, Aras scoring techniques and the use of geographic information system in Yazd-Khizrabad sub-basin. At first, after determining the working units by geomorphological method, the importance of indicators in each unit was obtained based on the Delphi method. Shannon's entropy method was used for the relative importance of indicators. Then the decision matrix was formed and after weighting, the potential of desertification intensity was estimated by calculating the desirability coefficient from Moora and Aras scoring method. The results of the analysis of both models showed that the land units of Mountain Agricultural Grounds (MAG) and Plan Agricultural Grounds (PAG) have the highest desertification potential, which covers 7135 ha (9.11%) of the entire study area and Quantitative value of desertification potential for the whole region based on the all of indicators was placed in the middle class (IV). It is suggested that the obtained results and ranking should be taken into consideration in the plans for controlling and reducing the effects of desertification and rehabilitating degraded lands.

This research employs a systematic review approach to comprehensively evaluate environmental inequalities in Middle East cities. The Middle East, due to rapid urbanization and unsustainable development, faces complex environmental challenges that disproportionately affect low-income and marginalized populations. In this study, 60 scientific articles published between 2013 and 2023 from Scopus, Web of Science, and Google Scholar databases were examined. Statistical analyses revealed that environmental inequalities in this region have been exacerbated by weaknesses in coordinated policymaking and cultural-geographical differences. Temporal patterns indicated an increasing trend in these inequalities over the past decade, while thematic analyses uncovered detrimental impacts on public health, air quality, and access to water resources.Geographical assessments demonstrated that specific areas are more vulnerable to environmental hazards due to climatic and economic conditions. By identifying gaps in existing scientific literature and current policies, this research proposes strategies to enhance environmental justice and improve conditions in Middle Eastern cities. The results of this study can serve as a foundation for developing effective policy strategies and future research in the field of environmental justice in the region. By presenting a comprehensive analytical framework, this research contributes to a deeper understanding of the dynamics of environmental inequalities in the Middle East and paves the way for targeted interventions

Considering that there are different forms of mass movements in the ChamGardlan watershed, especially along communication routes, agricultural and residential areas, it is necessary to create refugee maps Therefore, it is impossible to examine the factors influencing its situation in order to prevent and control this phenomenon. Therefore, during the field visits, geographical, physiography, land use, vegetation cover, soil, climatology, geography and geomorphology maps were produced in the GIS environment. The method of this research has been accomplished base of distinction of the geomorphological units while using aerial photos and crossing  basis maps. Then, the effective factors on the occuration of mass movements were studied using logistic regression equations. So that, the factors such as slope, geological formation type, pedologic, climatic, etc. were taked into consideration as independant variables, and mass movements occurance frequency as function of mentioned factors.The result indicated that the effective factors related to frequency of land sliding happening in the area in arrangement, are slope, geological formation type and mass  movements  type (both kind and amount of salts in soil) and also landuse.

Natural biological crises are a constant threat to human societies; Therefore, it is considered important to be prepared to control and prevent such disasters. In dealing with such urban crises, addressing the category of non-pharmacological interventions against infectious diseases can be a way forward. Therefore, the aim of the current research is to find the main effective indicators in the epidemic and to explain the environmental components resulting from the interaction and correlation of the relevant measurable indicators at the locality level based on previous environmental studies. In this research, in order to obtain a community of opinion about effective indicators in epidemiological crises, a systematic search was first conducted using the keyword of pandemic resilience. For this purpose, several widely used databases such as Web of Science, Scopus and Elsevier were searched between 2013 and 2023. After checking the quality of the conducted researches, 42 indicators were selected. Further, in order to find out the underlying variables and identify the basic factors or criteria in order to explain the correlation pattern between the observed variables, the exploratory factor analysis method was used and SPSS version 26 software was used to analyze the data. Data from 118 Tabriz neighborhoods were used for exploratory factor analysis. After collecting the data, the process of change, standardization has been done to prepare the data and convert the raw data into percentage, growth rate, average and ratio. Then, the status of urban resilience components against epidemic diseases was calculated and normalized separately based on factor load for each neighborhood. Finally, the results were illustrated using Arc GIS software. The findings of the research indicate that 42 indicators affecting the spread of epidemic diseases at the level of localities can be re-categorized into 8 components of accumulation, diversity and design, social factors, density, economic factors, health infrastructure, environmental pollution and green spaces. Also, based on the findings, it can be said that the condition of most of the components in the neighborhoods of Tabriz city is at an average level. Based on the results, the effects of environmental factors on the transmission of Covid-19 are differentiated spatially. These components represent more than 82% of the changes in effective environmental factors.

The purpose of this study is to investigate one of the supporting services of the ecosystem, called habitat quality, and to assess the spatial vulnerability of natural landscapes in the city of Khorramabad using the InVEST habitat quality module. To achieve this objective, it is essential to identify the sources of threats, the relative weight of each threat, the maximum distance of its effect in space, the types of habitats, and the sensitivity of each to the source of the threat. In addition, one of the most important inputs of InVEST is the land use/land cover (LULC) of the study area. The Local Climate Zone classification method has been used for the creation of this map. Finally, the model generates spatial distribution maps of habitat quality and degradation across the landscape by combining LULC and different threat sources. The findings indicated that the city, airport, and highway factors are the most destructive threat factors to all habitats with an average score of 0.51, 0.345, and 0.33, respectively. Compared to other LULC, water, dense trees, and scattered trees suffered the most destruction, with sensitivity ratings of 0.47, 0.39, and 0.36, respectively. The results also revealed that habitat quality in Khorramabad is at a medium to low level, and the habitat quality is in very good condition in only 3% of the landscape area.