فهرست مطالب علی خدمت زاده

Quality of life is one of the important issues that was first brought to the attention of scholars by the extensive development of technology and industrialization process in the Western countries, and it is increasingly being studied in this field, and this is important due to the increasing increase in quality of life studies in public policy monitoring. Quality of life can be used as a powerful tool for monitoring community development planning. The existence of spatial and spatial inequalities in the city has caused many problems, including the weakness of resources, inappropriate housing, the problems and damage caused by social inequalities, and undermined the quality of life. In this research, that of terms methodological, descriptive-analytic and in terms of purpose, it is functional used the statistics blocks of Urmia, in the census of 1395, and remote sensing data in combination with GIS have been to understand the quality of life in the 5 regions of Urmia. The criteria defined in this research are in 4 sections: social (including 9 sub-criteria), access to public services (5 sub-criteria), physical (4 sub-criteria), natural (4 sub-criteria), which are based on decision analysis Multi-criteria and integration of layers in the GIS environment. Weights obtained for social dimensions, access to public, natural and physical services derived from network analysis model  are respectively 0.506, 0.323, 0.116 and 0.055. The results show that as far as the southwest is moving along the northeastern part of the city, blocks that have a better quality of life are rising.  In the urban regions of the region 2, quality of life is more favorable than other urban regions. The results of such studies can help urban planners to better understand and prioritize urban issues as a dynamic environment.

The occurrence of natural disasters such as earthquakes, in urban texture and in population density region has caused hard damage. Regarding the country’s location on the earthquake zone, the current study has studied Urmia city due to natural features and the risk of seismicity in order to identify the most important damaging factors in order to manage the urban disaster caused by an earthquake.

This research is descriptive and analytical in method and applied in purpose. In the descriptive section, the results of the general census of population and housing in 1395, documents and library studies have been used, and in the Analytical section, the Network Analysis process (ANP) and fuzzy operators in ARC GIS software have been applied.

Geographical area of research:

The study area (statistical blocks) with an area of 4854.91 ha contains 91% of the total area of Urmia city, which has a population of 727066 people (other than Golmankhaneh Town).
Based on the 2016 census and based on the information obtained from statistical blocks, the rate of population and the number of families in the area were 727066 people and 222737 families, respectively. The study area includes 97.83% of the population of Urmia city.

The highest vulnerability is in areas with a slope of more than 20% and areas with high population density are observed. Areas with very high vulnerability with 34.12%, high with 11.81%, medium with 30.47%, low with 20.89% and very low with 2.7% accounted for the area of statistical blocks. In general, it can be said that 45.93% of the study area is vulnerable based on the criteria used in the analysis.

In vulnerable earthquake zoning in Urmia, 5 vulnerable classes were obtained. The very high vulnerability class in the Zone 2 urban area with an area of 341.09 hectares (13.19%) has the most vulnerable uses, Zone 3 with 8.24%, Zone 1 with 7.57%, Zone 4 with 2.76% and Zone 5 with 1.92% have the most uses with very high vulnerabilities, respectively.

The growth of the urban population has been led to increasing of the urban spaces and growth of the city size. as a result of further construction and alteration of the land available to the benefit of its built-up spaces. Special location the city of Urmia at proximity of the Urmia lake and unfavorable condition of this lake reveals the necessity of the proper landuse planning at this city. One of the required tools for proper planning in this field is the use of remote sensing techniques. The present study aims to evaluate these changes (period 1989-2015) and predict its future trend. SVM and neural network methods are used to evaluate changes in 5 classes Due to the high accuracy of the classification of the neural network, the results of this classification have been used to predict changes for the 2045 horizon. Land constructed in 1989 is 7469.1 hectares, reaching 9217.3 and 94366.9 hectares in 2002 and 2015 respectively, and by2045, according to the prediction model, the neural network is equal to 22449.6 hectares, which is built on lands 13012.7 Shows hectares of increase. The determination coefficient (0.73) and rock curve (82.55%) also indicate the high accuracy of the neural network model to predict urban development changes. The Heldern method results shows that all of these constructions are not based on the real needs of the city And the sparse phenomenon has happened.

Population growth and urbanization are factors influencing the increase in air temperature in urban areas, which creates an thermal island in these areas relative to the surrounding area. These changes lead to the formation of a city's thermal island. A phenomenon in which urban areas experience warmer temperatures than their surroundings. Remote sensing with the use of infrared thermal radiation and the use of physical models is a suitable tool for calculating the surface temperature in vast areas. In this research, that of terms methodological, descriptive-analytic and in terms of purpose, the ETM+ Sensor of Landsat 7 satellite imagery and OLI and TIRS Sensor of Landsat 8 Satellite used to determine the Formation range of Thermal Island in Urmia city and The relationship between land use changes and the formation of thermal islands, during the period of 2010 to 2018.  As well as the support vector machine classification method was used to extract land use in three classes of residential, Vegetation and gardening and agricultural.Surveys show that the temperature in residential areas in 2010 was 32.90 degrees Celsius in the warm season, which reached 35.17 degree in 2018. That is an increase of 2.27 ° C. However, the area of residential areas is also showing an increasing trend and increased by6.09%. In 2010, garden lands and vegetation cover is 43.53 percent of the total land area and agricultural lands is 39.36 percent of the total land area, which will be 40.49% and 36.30% respectively in 2018. These values ​​in2018 are 40.49% and 36.30% of the area, that means a decreasing trend. Therefore, It can be concluded that agricultural and agricultural lands have been declining as a result of increasing residential areas. There is also a significant relationship between the surface coverage and the surface temperature of the study area, which indicates the formation of heat island on coatings made in the city exclusion.

Drought is one of the most complicated disaster, its adverse effects on dryland agriculture are more pronounced than other sectors.. The aim of this study was to investigate the drought situation in the Simineh river basin watershed at four stations Synoptic Bukane, Mahabad, Miandoab and Saqez conditions for moisture content of wheat dried grapes in the four years 2007-2010 were analyzed and analyzed to determine the drought stress on the yield of wheat from the 22nd to the 43rd week in the light of the growth and development of rain fed wheat in the region The study was conducted weekly using Palmer's Moisture Index (CMI).. CMI results indicate that in the period of grain filling between 20May and 15June, there is a negative moisture drought index (CMI), which indicates the effect of drought on the performance of the wheat field. Drying plant is in good moisture conditions, but the stations of Bookan, Mahabad and The midsection is tense and the amount of moisture in 2010 is negative in all stations and the area is in severe drought.

In recent years, lower than the water level of Lake Urmia, the study of changes in temperature, humidity and drought stress thresholds in the area of inevitability is inevitable.Drought is a difficult weather event and a "crawl" disaster. From the agricultural perspective, drought has occurred when the soil moisture is less than the actual needs of the product and leads to damage in the product. For drought analysis, the existence of an indicator for the accurate and reliable determination of wet and dry periods is very necessary.

In this descriptive-analytical and purpose-oriented study. The MODIS sensor data based on the Terra satellite was used. In these images, 8-day composite products with a resolution of 1 km and 8-day surface reflectance with a resolution of 250 m at time interval (2005 to 2008) were used for five consecutive months from June to October. Linear regression was used to derive the results. Also in this study 5.1ENVI, 10.5ARC GIS was used for analysis.The purpose of this study is to use MODIS sensor to evaluate the spatial relationship between NDVI-Ts and NDVI-ΔT for extracting real-time agricultural droughts in the Simineh River watershed from the catchment area of Lake Urmia, The VTCI Index (Vegetable Temperature Index) and WDI (Water Deficiency Indicator), which are capable of identifying regional drought stress. The second component of the material used in this research are:1. MODIS/Terra Land Surface Temperature/Emissivity8-Day L3Global 1km SIN Grid V004MODIS/Terra Surface Reflectance 8-Day L3 Global 250m SIN Grid V004 .2MODIS products produce surface temperature and reflectivity, their reflection and pixel magnitude. The VTCI index (duration of drought) is based on a simplified NDVI-TS triangular space in which the "cold edge" (non-stressed conditions) is considered as a line that has the lowest temperature in the NDVI axis (X-axis) and the "hot edge" (non-availability of water) is interpreted as a negative link with the NDVI. The WDI index (drought severity) can be further labeled as the wet line or ETR with a maximum of ΔLST NDVI min and the dry line or ETR is at least equal to Δ LST NDVI max.

The vegetation temperature index (VTCI) is calculated based on the relationship between the NDVI-TS triangular space. The hot and cold edge pixels are derived as linear regression equations for calculating VTCI using ENVI software in mathematical data, in which ground temperature (LST) and NDVI index images are used as input parameters for the VTCI equations Is In all these years, it is observed that the gradient for the hot edge is negative, while for the cold edge it is slightly negative or no appreciable change. The gradient shows that when the NDVI value increases for any time interval, the maximum temperature decreases. The gradient on the cold edge indicates that when the NDVI value increases.The Water Deficit Index (WDI) is calculated on the basis of the ΔTs-NDVI spatial relationship, the wet line pixels and the dry line are determined by the linear regression equation, and the extracted equations were used to calculate WDI. In calculating this index, the difference between the surface Temperature (TS) extracted from the satellite imagery and the temperature of the weather stations (Ta) as a parameter (ΔT), and NDVI images are used as another input parameter for the WDI equations. Therefore, the wet and dry line is obtained from the NDVI-ΔTS triangular barrier. The slope obtained from the NDVI-ΔTS spatial relationship is negative for the dry line, while the gradient obtained for the wet line is positive and in the rest of the years there was no significant change. The negative slope shows that ΔT Max decreases with increasing NDVI index and positive slope shows that ΔT Min increases with increasing NDVI index.The study period shows that the 2005-2006 period in the study area has a higher VTCI content than the years 2007-2008, which means less stress. The low VTCI has a tendency to stress and its high value indicates favorable conditions. The low VTCI value is less than its higher value in the obtained maps, which expresses the relative favorable condition of drought stress throughout the studied region. Generally, the lower Simineh, upstream of Bookan County, and to some extent the Hajiabad Plain, Miandoab, are areas that show less moisture conditions during 2005-2007. These areas, namely the Simineh River (between Miandoab and Bookan), show lower VTCI than the Simineh Rivers (between Mahabad and Bookan) and Simineh River higher (between Bookan and Saggez). The more northerly regions with high VTCI levels are less humid and have good conditions. VTCI is higher in these areas due to irrigation options that vegetation does not tend to moisture.The WDI spatial pattern has also been studied in the Simineh River watershed from the main catchment area of Urmia Lake for the July 153 day in 2005-2008. The lower WDI represents the optimal conditions, while the higher VTCI represents the favorable conditions in that area, and the range of this index is the exact opposite of the VTCI index. According to the maps drawn from the WDI index, it can be seen that during the period from 2006 to 2008, the WDI spatial pattern is similar to the VTCI index. Although the spatial patterns of both indicators are similar, the WDI index offers a distinct class of this situation. In the entire catchment area of the Simineh River, the water stresses were severe in 2005, but gradually increased from 2006 to 2008. In the middle and upper part of the upper part, the WDI is high, indicating that all areas between Bookan and Mahabad are exposed to moisture stress. The northern Bookan districts of the northwest and the Haji-Abad area of Miandoab show relatively good conditions, and in 2008, all mid-zone regions such as the eastern, western and northern Akhtachi show a higher WDI.The overall analysis shows that the duration and severity of stress are similar according to the VTCI index as well as the WDI index from favorable conditions to stress conditions, and shows that in general, in 2005-2007, the temperature and humidity stresses in the study area gradually, the tensions peaked in 2008.

In this research, the Fuzzy_ANP model has been applied to flood zoning of Urmia Chay basin. The variables studied are eight parameters that include: slope, vegetation density, elevation, precipitation, slope direction, distance from the river, land use and geology. The information layers are provided in ARC GiS and ENVI software, and the fuzzy ANP model has been used to weigh the variables. According to the results of the research, the southeastern parts of the basin are located in zones with high potential and very high due to low The presence of vegetation density, gradient, and type of formation, have been introduced as the flood of the tallest parts of the basin, which are respectively 66.17 and 37.36 from the basin area respectively. Low and very low potential sectors are the western part of the basin, often with agricultural use and gardens. These areas comprise 10.41 and 1.63% of the total area of the basin respectively.

Drought is one of the most complicated disaster, its adverse effects on dryland agriculture are more pronounced than other sectors.. The aim of this study was to investigate the drought situation in the Simineh river basin watershed at four stations Synoptic Bukane, Mahabad, Miandoab and Saqez conditions for moisture content of wheat dried grapes in the four years 2007-2010 were analyzed and analyzed to determine the drought stress on the yield of wheat from the 22nd to the 43rd week in the light of the growth and development of rain fed wheat in the region The study was conducted weekly using Palmer's Moisture Index (CMI).. CMI results indicate that in the period of grain filling between 20May and 15June, there is a negative moisture drought index (CMI), which indicates the effect of drought on the performance of the wheat field. Drying plant is in good moisture conditions, but the stations of Bookan, Mahabad and The midsection is tense and the amount of moisture in 2010 is negative in all stations and the area is in severe drought.

The effects and evidence of tectonic activity can be seen in most parts of the planet; particularly if these activities have occurred during the Quaternary period and thereafter, the evidence would be readily recognizable (Guarnieri and Pirrotta, 2008:264). Iran is tectonically an active region. Many indices have been developed, tested and validated for quantitative geomorphic analyses to identify topographic fingerprints of surface and sub-surface processes. Morphometric analyses of river networks, drainage basins and relief using geomorphic indices, as well as geostatistical analyses of topographical data have become useful tools for investigating landform evolution. GIS platforms and high-resolution digital elevation models (DEM) facilitate the computation and charting of this type of information (Hayakawa & Oguchi, 2009:31). The stream length gradient index (SL), describes the morphology of the drainage network using a topographic gradient along a river. This index is sensitive to tectonic and lithology activities and is used as an indicator for tectonic areas. In this study, the morphometry of the catchment in north of Damghan was estimated and their stream – length gradient (SL) indexes have been mapped using GIS.

The studied area is located in northern mountain range of Damghan (East Alborz). In order to study the morphometry and tectonic indexes of the area, geological maps (1:100000), topographic maps (1:25000), and DEM 12.5m were used. The computation of SL was based on the interpolation of a discrete value. For a segment of a given river, the SL has been defined as: SL= (ΔH/ ΔL) Ltc. where ΔH is the variation of elevation, ΔL is the length of the segment, and Ltc is the total channel length from the midpoint of the segment where the index is calculated from upstream to the divide; actually, (ΔH/ΔL) is the slope of the considered segment. The drainage network was automatically delineated from the DEM, and SL was computed using ArcGIS 10.6®with the Spatial Analyst® extension, supported by several freeware packages including Arc Hydro Tools and ET Geowizard. The obtained point dataset of SL was interpolated using the ordinary kriging (OK) algorithm to estimate the spatial distribution of SL for the whole river basin.

Geologically, the studied area is located on the southern slopes of Eastern Alborz. The southern parts of the area are located between the two structural units of Alborz and Central Iran. This has caused the complexity of this part, lithologically and tectonically. A large part of the studied area consists of the Mesozoic formations, especially Jurassic. These formations consist mainly of sandstone, coal shale and gray to dark-colored limestone. Tectonically, the area is active and there have been several earthquakes in and around this area. The main systems of the faults of the region are thrusts and then strike-slip faults. In sub basins, the hypsometric integral values range from 0.18 to 0.66. Unlike the average height of the sub-basins, which has a natural trend, the hypsometric integral in the region is heterogeneous and has been distributed depressively. The average slope of the sub-basin is 18 degrees and its maximum slope is 33 degrees. The values of SL index range from 72 to 985 m. High values of SL are observed in the center, east and southwest of the region. The core of the high values is located in the center of the region, where major and minor faults are observed.

The purpose of this study was to provide a map of SL index in northern mountain of Damghan. The indicators used in this research, such as slope, hypsometric integral, longitudinal elevation and river gradient, were automatically calculated using GIS and digital elevation models. The results showed that the presence of faults and their uplift were related to the high values ​​of the SL, indicating a different uplift in hole parts of the region. The maximum values ​​of the SL index were observed around the faults, especially in the central part of the studied area. The results also showed that sub-basins with high slopes also had high hypsometric integral values. This can also indicate the high degree of erosion processes. Considering that in this study DEM, topographic maps and interpolation methods were used to calculate the longitudinal gradient of the river, it seems to be more comprehensive than the longitudinal profile of the river, and provides a broad view of the geomorphological processes of basins and sub-basins

Flood is one of the most complex and destructive natural phenomena that causes many damages each year. The zoning of flood potential as classified maps is one of the most important tasks in reducing flood risks and preventing it.The area under study is Ghasemlou watershed located in the watershed of Lake Urmia in West Azarbaijan province. The variables studied are eight parameters that include: slope, vegetation density, elevation, precipitation, direction of gradient, distance from the harbor, geology land use. The information layers are provided in the ARC GIS and ENVI software and ANP model has been used to weigh the variables in relation to the risk of flood events.The results show that in relation to the risk of flood, the factor of precipitation was 0.49665%, the distance from the river with 0.20516 and vegetation factor with 0.17956%, due to the large amount of control on the amount and how to discharge the runoff from the surface The basins are of the highest importance and impactand slop factor and land use have the lowest impact level of 0.00727 and 0.00856%, respectively.The studied basin is divided into 5 classes, very high, medium, low and very low, with very high and very high flood potential, respectively, 0.51, 22.31%, and very low and low flood talents of the region were 21.72%, 0.73% of the subbasin area respectively.

Investigating the changes in the water level of the lakes in order to protect them in terms of the importance, nature and position of these water bodies and as a natural heritage in recent years between countries at national and regional level has gained special importance .The drying crisis of Lake Urmia with an area of about half a million hectares as Iran's largest inland lake has become a national issue due to its consequences. Due to the changes in precipitation and temperature and the occurrence of severe droughts and wetlands in this basin and its morphological features (low coastal slope) its elevation level is subject to many fluctuations and changes .In recent years, the development of water resources projects, and in particular the construction of reservoir dams on the rivers leading to the lake, has had a major impact on the water inlet and ultimately its water level.In this study, we used and processed Landsat 7 and 8 satellite weather data (including ETM + and OLI sensors) from 2001 to 2019 to evaluate the changes in the Urmia Lake area. Different time periods were extracted. The results show that the area of Lake Urmia declined from 4346.71 sq km in 2001 to 2285.76 sq km in 2015 and increased to 3705.88 sq km in 2019. Lake water volatility also declined by 47.39

Remote sensing technology is one of the efficient and innovative technologies for agricultural land use/cover mapping. In this regard, the object-based Image Analysis (OBIA) is new method of satellite image processing which integrates spatial and spectral information in satellite image process domain. This approach make use of spectral, environmental, physical and geometrical characteristics (texture, shape) context of images for modeling of land use/cover classes. Current study, aims to classify micro land use/cover of Meyandoab County by applying appropriate algorithms and parameters in the object based approach. For this goal, Quick Bird and Aster satellite images were used for processing and land use modeling. Accordingly, land use map was classified in 9 class based on spectral and spatial characteristic. The segmentation was performed in the scale of 10, shape parameter of 0.7 as well as the compactness of 0.3. In order to apply classification, fuzzy based algorithm and operators (AND, OR) was applied to detriment the membership functionality of segments for each class as well as classifying the related objects. We also applied textures, geometric, NDVI, GLCM, Braitnese algortims based on fuzzy operators. In order to validate results, the accuracy assessment step was performed and the finally overall accuracy of 93.6 was obtained for derived map. The Kappa coefficient was also detriment to be 0.92. The area under cultivation included respectively for lands of wheat and barley, prunes and plums, apples, vineyards and alfalfa hay2622.42, 4505, 4354.55, 4457.85, 14110.58 hectares.