فهرست مطالب vahid isazade

In this research, the aim of this research is to the environmental, political and security consequences of the drying up of Lake Urmia using remote sensing on the barracks of the Islamic Republic of Iran Army in Lake Urmia. In terms of the purpose, the present research is in the category of applied research, and in terms of the nature and method of the research, it is a descriptive survey type of research. The statistical population of the current research is the army barracks of the Islamic Republic of Iran in the area of Lake Urmia. To monitor salt particles in Urmia Lake, Sentinel 5, Madis and Landsat 8 satellite images for 2000 to 2022 from the Google Earth Engine system were used. In this research, the spatial descriptions and analyses available in the geographic information system (GEE system and Gis Arc software) have been used. According to the results of Moran's spatial autocorrelation analysis of salt dust dispersion and their impact on army barracks in Lake Urmia basin during 2010, Moran's coefficient showed 0.816328%. This percentage has reached its highest level by 2022. The highest concentration of hot spots (dispersion of salt particles) can be seen in only one high cluster in the northeastern parts of the Urmia lake basin, which includes Tabriz's 2nd Shekhari Barracks and Tabriz's 121st Brigade. In addition, the results of the research show that the security consequences of the mini-guns in the two barracks of Mahabad and Saqzaz Nazar show the defence and security aspect in 2015, which include an increase in the amount of unauthorized traffic, the creation of security loopholes, disruption in the movement of patrolling personnel, a decrease Field of vision, especially in times of wind and visibility, disturbance in standby and support, and disturbance in telecommunication networks are the most important security consequences of crisis defence. In 2022, the spatial dispersion of salt dust was not specific to one barrack, and most of the army barracks in the region were affected by the harmful dust of the lake, in this year, the highest amount of salt dust was found in the barracks of Urmia, Shekhari, Tabriz, Ghoshchi, Saqez and Mahabad is scattered. The security consequences of micro-rounds in the whole region in terms of defence, security and political dimensions, including ethnic-religious differences between the Turks and Kurds, increasing public discontent, decreasing the social solidarity of citizens with the government, increasing street protests and urban riots in the region, ethnic incitement. and more dissatisfaction, security crimes have increased.

Thermal remote sensing, as a branch of remote sensing science plays an important role in environmental studies. Thermal sensing is one of the new and low cost methods against ground surveys in remote areas, which provides valuable information from the study area to researchers in the shortest time. It is possible to prepare a surface temperature map to identify areas prone to geothermal and plant stress by using an infrared thermal band. Which provides the basis for further exploratory studies. In this research, we used the ETM + and ASTER sensors to map the vegetation anomalies using the NDVI index of Khoy city. And plant seasonal variations were examined. Two datasets, one in early summer 2002 and the other in late summer and fall 2002, were derived from Landsat 7 data. By calculating the LST for the ETM + sensor, in this study, changes beyond the normal seasonal changes were considered as thermal anomalies. Also, by calculating the surface temperature by ASTER data, the surface manifestations of these anomalies under dense vegetation were revealed. MODIS sensor images were used to validate LST calculated by ASTER sensor and NDVI and ALI were calculated using it. The results of the present study showed that the identification of geothermal regions has a good spatial correlation with plant stress in Khoy city. ETM + and ASTER sensors, due to their high resolution in the infrared thermal band, 60 meters and 90 meters, respectively, are suitable sensors for calculating the surface temperature and detecting thermal anomalies. Therefore, the image difference method in this study was not a suitable method and did not show good results.

Typically, in developing countries, urban growth exceeds the capacity of governments and municipalities to provide services and infrastructure suitable for the population. This category will exacerbate urban poverty in cities, especially large cities in these countries.

 The purpose of this study is to empower poverty in the neighborhood of Ismail Abad, District 19 of Tehran Municipality. This research is applied in terms of purpose and part of descriptive-analytical research in terms of method. The statistical population of the present study is the Ismailabad neighborhood, District 19 of Tehran Municipality. First, using economic, socio-cultural, and physical indicators, the areas of urban poverty in the Ismail neighborhood, District 19 of Tehran Abad Municipality were identified.

The weighting of the research indices was taken using the Shannon entropy method, then the Vikor quantitative leveling model was used to rank the indices. ARC GIS software has been used to display and analyze the poor urban space in the neighborhood of Ismail Abad, District 19. Also, using the QSPM model, internal and external strategies were identified in which non-governmental organizations and non-governmental organizations were considered as the most important motivating factor in empowering poverty at the neighborhood level and after identifying the target neighborhood. The use of the SWOT technique has been done to improve this place due to planning problems and limitations.

The results indicate that urban poverty has been discovered in neighborhoods located on the outskirts of the city. To solve the problems of the residents of the target neighborhood, local spontaneous reinforcers in creating solidarity and maintaining the neighborhood identity, recognizing development potentials, educating residents and raising people's awareness, implementing empowerment plans to control the neighborhood.

Surface temperature is one of the important indicators in the study of models of energy balance at the surface and interactions between the earth and the atmosphere on a regional and global scale. Today, satellite imagery in thermal infrared and red wavelengths is a good source of information for water and land surface thermal mapping due to its extensive coverage. Today, the phenomenon of thermal islands in cities causes many human and financial losses to citizens. One of the problems in cities is that to study and control this phenomenon, you can use appropriate satellite images and identify and manage the infected parts of the city. Therefore, the purpose of this study is to prepare the changes made in urban constructions and the uncontrolled increase of buildings and their relationship with the ground surface temperature using the data of ETM and OLI sensors of Landsat satellite in 2002 and 2019 for Tehran. In this study, the Gram_Schmidet method, which was developed to combine these images, was used. And data for 2002 and 2019, all captured in winter, were prepared, analyzed and evaluated. Correlation coefficient and kappa coefficient indices have been used to verify the method and classification accuracy. The results show; The VbSWIR_BI and IBI indices have the highest accuracy compared to other indices while the results of VbSWIR_BI index show the temporal and spatial changes of Tehran in an acceptable result. Also, according to the results obtained through the surface temperature, with the increase in construction, the increase in temperature in Tehran has been extended to the northern and central regions of the city.

Today, the flood phenomenon is one of the most complex and dangerous events that, more than other natural disasters, leads to human and financial losses and destruction of agricultural lands in different parts of the world every year.

Due to the flooding of Zolachai Watershed, Salmas County, it seems necessary to study and simulate the risk of floods in this area. Therefore, in this study, a combination of artificial perceptron neural network (MLP) and GIS has been used. First, the effective parameters in simulating flood areas such as: slope layer, height, flow direction, soil and land use were examined and these information layers were entered into GIS software. The information layers were processed with the Fishnet command. And each layer became a point.This data, along with the educational data received from Google Earth, was introduced to the perceptron neural network.

In the perceptron neural network, the input layers including 5 neurons and 16 nodes entered the model and the results showed that the height has the lowest weight (R2=0.713) and the highest weight related to the flow direction (R2=0.913) in simulating the Zolachai Watershedflood., Is the city of Salmas.

It can be said that the combination of GIS and artificial neural network can be very useful for modeling and simulating floods in different spatial environments to prevent and reduce environmental hazards.

Ground surface temperature is one of the important criteria in regional and regional planning. Surface temperature can be used in many environmental, agricultural, meteorological and other applications. In this research, Landsat 8 satellite images have been used to monitor the surface temperature in Dezful city. After performing radiometric corrections to calculate emissions based on vegetation and soil fraction (PV), emission calculations were performed based on FVC. As a result, ground surface temperature was estimated using a separate, single-channel window algorithm. While the separate window method shows a much higher value than the Planck method a very low value. It seems that the error of these two methods is much more than other methods. According to the approximate temperature extracted from the synoptic stations of Dezful city, the value of which is considered to be 308.95 Kelvin. But in general, it should be noted that the methods of calculating LST through satellite images are very different from the temperature obtained from meteorological and synoptic stations and do not offer high accuracy.

The basic elements that are considered as social factors of health have different structures in political, socio-economic fields. While socio-economic and political contexts are directly related to social, economic, public and health policies at the national level. In addition, this structure includes socio-economic dimensions such as income, education, occupation, social class, gender and ethnicity. Experience has shown that children who grow up in low-income or unfavorable environmental conditions, including residential structures, are more likely to become ill than children who live in better environmental, social, and economic conditions. This situation shows the importance of city planning in terms of providing better conditions for children's health. The purpose of this study is to evaluate the environmental factors of children's health using geographic information technology (GIS). For this purpose, various social determinants in terms of political (quality and quantity of medical services), structural (educational and social class) and mediators (physical environment, housing and neighborhood) in Tehran were studied. A total of 6 criteria were selected by experts and surveys among families with children, including air pollution, pediatric hospitals, parks, congested traffic, and pediatric population in areas of Tehran. Citizen-centered data used by 10 households in Tehran for validation. The fuzzy product model was almost in line with the people's spatial surveys, indicating that areas with greater well-being and areas with heavy rules were better placed on these criteria.

Following the increase in population and the growth of urbanization in recent decades, the natural landscape is becoming a human landscape, and the urban open space has become a constructed area. The aim of this study was to investigate the performance of four widely used urban spectral indices in order to separate the areas built from other uses in two different cities and compare it with the results of object-oriented classification to extract the constructed areas. For this purpose, the normalized difference indices of the constructed areas, the urban index, the normalized index of the constructed areas and the extraction index of the constructed areas from the OLI satellite images of Landsat 8 satellite for the two cities of Tehran and Gorgan have been calculated. Autos automatic thresholding method has been used to separate the constructed and un constructed areas. The research findings showed that spectral indicators in different urban areas do not have the same performance and the accuracy of extraction of constructed areas by applying these indicators does not exceed the accuracy of object-oriented classification. The overall accuracy of the object-oriented classification in extracting the constructed areas in Tehran is 92% and in Gorgan is 91%. The best spectral index of the constructed areas for the city of Tehran was the extraction index of the constructed areas with an overall accuracy of 82% and for the city of Gorgan, the normal index of the constructed areas with a total accuracy of 86%