کاربری اراضی

Determining the runoff coefficient in a distributed way can be used to identify the runoff producing areas. The runoff coefficient represents the ratio of runoff to total precipitation in different areas, where the previous soil moisture is not taken into account. The runoff coefficient without considering the effect of soil moisture is called the potential runoff coefficient, which is determined based on different parameters in hydrological studies. The changes in the watershed runoff coefficient depend on the topographic characteristics and especially the slope. Assessing the spatial changes of runoff coefficient at the watershed scale is very important for understanding the hydrological cycle under natural and disturbed condition. The location of homogeneous and similar units in terms of hydrological behavior in the watershed is determined and identified by determining the spatial map of runoff production. Meanwhile, determining the watershed response is important in the production of flood runoff volume. It should be noted that the similar units based on hydrological response are usually defined based on runoff production using field measurements. In this regard, the spatial data mapping provides the possibility of preparing a map of the runoff coefficient in a short time and will increase the accuracy of the work. Anthropogenic intervention in the natural water cycle through the destruction of vegetation in watershed areas, land use change, development of impervious surfaces lead to increasing the possibility of flooding in various areas. Various factors affect the occurrence of floods, which can be mentioned the intensity of rainfall, the slope of the land permeability, relief, characteristics of vegetation and different soil conditions. The runoff coefficient is one of the important parameters for estimating the peak flood of hydrological models and identifying important areas of sediment production and pollutants in runoff producing areas. Several factors have been used in determining homogeneous hydrological units with similar runoff coefficient, e.g., rainfall distribution, soil moisture, bedrock depth, evaporation, geology, land use, soil and slope.

The purpose of this research is to surface runoff potential mapping using combined table and the soil conservation service curve number (SCS-CN) method in the Mohammadabad Katul watershed in Golestan province. The area of study area watershed is 404 square kilometers and a main river length is 30.5 kilometers. The minimum and maximum elevation of the study watershed is 455 and 3671 meters above sea level, respectively. The average annual precipitation of the study watershed is 530 mm, and the average annual temperature is 16.5 centigrade degrees. Also, the average slope of the study area is 41.6%. The land use map of the study area was obtained from the General Office of Natural Resources and Watershed Management of Golestan province and the land use types were modified during the field surveys, then the land use map was digitized in the GIS environment. The soil map of the study watershed was also prepared based on previous studies and then digitized using GIS and the soil map has been prepared. The digital elevation model of the study area with a cell size of 30x30 meters has been obtained from topographic map with a scale of 1:25000. The slope map of the watershed was prepared from the DEM and then classified into four slope classes according to runoff coefficient table. Based on this, the necessary information to determine the runoff coefficient including the land use map, slope and soil texture was prepared. Then, the values of the potential runoff coefficient were determined using the combined table in the study watershed. Also, by incorporating the required layers, the curve number map of the study area has been prepared. The maximum 24-hour precipitation data of the nearest rain gauge station (Fazel abad) has been analyzed. After statistical analysis, the best probability distribution function fitted to the data has been selected for further analysis. Then, the runoff height and the value of the runoff coefficient were determined in 5, 10, 25, 50 years, return periods using the SCS-CN method. In the next step, the results of the combined table method and the SCS method were compared in estimating the amount and spatial distribution of the potential runoff coefficient.

The results of this study showed that the runoff coefficient was 39% according to the combined table method. The maximum coefficient of potential runoff in the study watershed was estimated to be 0.55, corresponding to the steep and agricultural land use of the study areas. Also, the minimum runoff potential value coefficient was 0.13. Based on the results, the combined distributed method incorporating land use, soil texture, and slope layers has the ability to determine the spatial changes of the runoff coefficient. In the following, the fitted frequency distributions were evaluated based on the goodness of fit criteria, and the Combined Laplace frequency distribution was chosen as the best frequency distribution to calculate the rainfall values in different return periods. The value of the runoff coefficient was 0.29 in 50-year return periods.

In the present study, the runoff coefficient map was prepared using the combined table method and SCS-CN method. In this regard, the GIS layers of slope, soil, land use and combined table were used to prepare the potential runoff coefficient map of the watershed. It seems that the calculated runoff coefficient based on the integration of the influencing maps takes into account the main and effective factors on runoff production, and provide an accurate spatial runoff coefficient map. As a concluding remark, it can be said that the combined and SCS-CN methods have provided similar results, but the runoff coefficient numbers provided by the combined method are higher than the SCS method. Considering the effect of several factors, including rainfall characteristics, relief, land permeability, vegetation characteristics and physiography on the flooding of a region, it is necessary to develop a method that can be used to map the runoff coefficient to the flooding map based on the affecting available factors. The integration of different layers in GIS and the use of a combined method is a useful tool for determining the runoff coefficient in ungauged watersheds, which allows the use of the runoff potential map in reducing the possible effects of floods.

Urbanization changes natural landscapes to human-made spaces and uses. With the expansion of cities, many of these spaces give way to roads, buildings and urban facilities and cause changes in different levels of the city, and these changes have very important effects on weather conditions (Shamsipour et al. 2013: 59). )The development of urbanization is one of the effective factors in increasing the air temperature in urban areas, which causes the creation of thermal islands in these places compared to the surrounding environment. This factor can have a negative effect on air quality and endanger the general health of society. (Mousavi Baighi et al., 2010. 190). What is considered as a fundamental defect in monitoring the temperature of the earth's surface is the lack of sufficient meteorological stations to know the temperature values. Today, this shortcoming has been solved by remote sensing and it can cover a large area of the earth's surface.

The study area is Amol city. The city of Amol is located in the Mazandaran province and the sides of the Heraz River with a height of 76 meters above sea level at 52 degrees and 21 minutes east longitude and 36 degrees and 25 minutes north latitude and at a distance of 70 kilometers west of Sari, the capital of the province, 18 kilometers south of the Caspian Sea and 6 It is located one kilometer north of Alborz mountain and 180 kilometers northeast of Tehran.In this research, Landsat 8 satellite images and Landsat 5 satellite images were used for 1990 in order to extract the land use map and surface temperature of 2020. In order to remove the effect of cloud cover from the images as well as the high intensity of sunlight, the desired images were taken from the summer season. Google Earth software was used for better accuracy of images, ENVI 5.3 software was used for atmospheric and radiometric corrections, and finally ARC GIS 10.8 software was used to prepare relevant maps.Using the atmospheric correction model (FLAASH), the data were qualitatively controlled and the radiometric error of the satellite images was corrected. In order to obtain a statistical set that represents the spectral pattern of land cover, training data must be selected before supervised classification of images. At this stage, information from the uses and topographical maps of the region were prepared using the visual interpretation of the images for all five floors, to prepare educational data for use in supervised classification operations. Maximum likelihood classification method was used for land use classification. This method is considered a part of the supervised methods for classification and for this purpose it uses a set of training data. In this method, after evaluating the probabilities in each class, the pixels are assigned to the classes that have the most similarity, and if the probability values are lower than the introduced threshold, they are considered as unclassified pixels.After that, the brightness temperature of the sensor is done by converting the digital values of band 6 in Landsat 4 and 5 and also band 10 in Landsat 8 to spectral radiance and converting the spectral radiance to the brightness temperature of the sensor in terms of Kelvin.Then, red and near-infrared bands were used to calculate NDVI to obtain the normalized vegetation difference index. After calculating NDVI we need to get Emissivity. Emissivity is the amount of reflection of a phenomenon relative to the black body. Then the land surface temperature (LST) is calculated. By using LST, it is possible to calculate the temperatures near the surface of the earth. In order to know and evaluate the correctness and accuracy of the classification, the user's accuracy, overall accuracy and Kappa coefficient were calculated in 1990 and 2020.

In this research, in the first step, the classification and the resulting changes were done in a specific time frame in Amol city and its surroundings. The classification results indicate that the classification in both periods, especially in 2020, was highly accurate, and its kappa coefficient and overall accuracy were at their highest coefficient, i.e. 100.After classification, the changes obtained in the area were examined for a period of 30 years and the changes were extracted for each land use in terms of hectares. The change of use from agriculture to the city and also from the city to roads and streets have the most changes. These changes indicate that the increase in urban use has caused a decrease in agricultural use and the size of urban areas has increased.Using Landsat satellite images, the temperature of the earth's surface has been studied in relation to land use and the results showed that the temperature is different in different uses. The highest temperature recorded for the years 1990 and 2020 in Amol city is related to urban use, the recorded temperature of which is 32.6 and 40.5, respectively, which shows the concentration of heat in urban areas. Urban use has the highest temperature due to the presence of man-made factors and heat absorbers such as asphalt, concrete and the presence of machinery. Also, the presence of tall buildings acts as a barrier to the heat escaping to the surroundings and in some way traps the heat inside the cityWith the development of urbanization in Amel city, a significant part of the area of natural and forest areas has been replaced by industrial areas, buildings and other infrastructures. The lowest temperature recorded in Amol city is related to forest use with 23.8 and 28.4 degrees Celsius. In forest areas, due to high albedo, high humidity and more open space, the temperature is lower and heat absorption is low there.The relevant researchers and experts in the region can use the results of this research to obtain information about the temperature of the earth's surface, land use, and also the changes that have occurred in the region, In order to predict the future situation of the region, they will take appropriate and correct policies.

Soil erosion is a natural process (Lee et al., 2021). which causes the level of soil loss by various environmental factors such as weather, soil, topography and vegetation (Chen et al., 2019). However, human interventions through land use change and agricultural and construction activities can accelerate this flow (Wenker et al., 2019; Barley et al., 2017). For this reason, nowadays, soil erosion caused by land use change has become the most important issue of land degradation all over the world, and the transformation of the land form and the disruption of the main functions of the natural environment are the consequences of these geomorphic reactions (Paul et al., 2019). T (2017) aimed to study and estimate the spatial and temporal soil erosion in the periods of 1994-1999-2008-2015 in the Manderjan sub-basin located in the west of Isfahan province. Using remote sensing and GIS technologies, they concluded that the amount of soil erosion in 1994-1999-2008-2015 was 0.001 to 233, 0.001 to 297, 0.001 to 231, 0.001 respectively. It is up to 215 tons per hectare per year. Also, the height and height factor in the region with a correlation coefficient of 80% has the greatest effect in B The annual soil erosion rate was estimated by the RUSLE model. Nejad Afzali et al. (2018) used the Revised Global Model of Soil Erosion (RUSLE) to estimate soil erosion in Dehkhan watershed south of Kerman. Their results showed that the annual soil erosion in the study area is estimated at 50 tons per hectare per year. Khosravi-Aghadam et al. (2018), in order to estimate the soil erodibility factor and its relationship with some land characteristics, using the USLE model in a part of the Nazlu Chai watershed of Urmia. Their results showed that the value of K factor varies in the range of 0.079 to 0.029 tons per hour per megajoule mm. Also, in terms of erodibility, the soils of the region are in low and very low erodibility classes.

Ateshgah watershed is located in the southwest of Ardabil city at the position of 47°50' to 48°2' east longitude and from 38°12' to 38°16' north latitude. The main branches of this basin originate from Sablan heights in the west of the basin. The area of this basin is 40.5 square kilometers and the maximum height of this basin is about 3596 meters at the extreme end of the western part of the basin and its minimum height is 1798 meters at the outlet of the basin in the eastern part. The location of Atashgah watershed is shown in Figure 1. Research data and tools The current research is of an applied type and its research method is an analysis based on the integration of data analysis, geographic information system, remote sensing and the use of the revised global model of soil erosion (RUSLE). The data and tools used in the research include 1:25000 digital layers of the National Mapping Organization, digital elevation model (DEM), with a spatial resolution of 30 meters, rainfall data from the National Meteorological Organization, Landsat OLI 8 satellite image for 2020 with a spatial resolution of 30 meters, the studied area from the website www.usgs.gov, the collection of educational samples was also done through field visits and the creation of false color combinations, and the soil laboratory data of the studied basin is from the watershed deputy of the country's organization of forests, pastures and watershed. In this research, ArcGIS 10.3 software was used to draw maps and analyzes related to it, as well as ENVI 5.3 software to prepare vegetation and land uselayers of the study area, and statistical software such as Excel 2016 and SPSS 17 for statistical calculations and The regression relations of the equations have been used.Landsat satellite images include the longest archive of global images with moderate resolution, multispectral data from unique sources for functional planning at various scales, including land use and land cover, change detection and monitoring of natural environment dynamics (Taherparour et al. , 2015). Therefore, Landsat OLI 8 satellite images were used in this research. The specifications of the satellite image used in this research are presented in Table After classifying the satellite image using the Support Vector Machine (SVM) method, the obtained land use map was separated into seven land use classes, including good, poor pastures, irrigated agriculture, rainfed, residential and irrigated areas (Figure 2). The accuracy of the obtained map for 2020 was checked using the Google Earth image and ground control points, as well as the false color image of the same year. In this research, the overall accuracy for the land use map of Atashgah basin was 0.90 and the Kappa coefficient was 0.87. 3-2- Soil erosion (RUSLE) According to (Figure A), the results of the rain erosive factor (R) vary from 74 to 34.98 MJ/mm/hectare/hour per year, the highest value of which is related to the north and southeast parts and the lowest value is related to the central parts. and southwest. The average amount of soil erodibility factor (K), according to figure (b), varies between 0.12 and 0.37 tons/hectare per year in the study area. According to figure (c), the value of LS factor in the studied area varies between 0 and 3.98, which is higher in steep slopes, especially around waterways. Using the Normalized Vegetation Index (NDVI), the vegetation factor (C) of the Atashgah basin was prepared based on equation 4 and 5, which is presented in (Figure d and e). Based on this figure, the value of the C factor varies between -0.16 and 0.74. In general, it can be said that the eastern and central half of the basin has lower amounts of C due to the presence of dry and unused lands, and the southern and western parts of the basin have the highest amounts due to the presence of pasture lands. The soil protection operation factor (P) was also considered to be 1 due to the lack of available information from the region for the entire region.Annual soil erosion (RUSLE), to prepare the average annual soil erosion map of Atashgah watershed through the product of rain erosion factors (R), soil erodibility (K), topography (LS), vegetation cover (C) and soil protection operations (P) It was calculated in the Raster Calculator plugin in the ArcGIS 10.3 environment using (Relation 1). The annual soil erosion values in the studied basin vary between 0.09 and 11.02 tons per hectare per year. Also, the average amount of soil erosion in the studied area is 0.16 tons per hectare per year and its standard deviation is 0.55 tons per hectare per year. In (Figure 3), the average annual soil erosion (RUSLE) map of Atashgah basin is presented.

Land use is one of the important factors in causing soil erosion, and in recent years, the mutual impact of land use change and soil erosion has become a major environmental concern. Considering the importance of the topic, in the current research, the amount of soil erosion on land use in the Atashgah watershed has been investigated using the RUSLE model. For this purpose, first, the land use map was classified using the Landsat OLI 8 satellite image and using the support vector machine algorithm into seven land use classes, including barren land, good pastures, poor pastures, rainfed agriculture, water, residential areas, and water. The overall accuracy and Kappa coefficient for the prepared land use map were obtained as 0.90 and 0.87%, respectively. Then the maps of R, K, LS, C and P factors of the RUSLE model were prepared in the GIS environment and after combining these layers through the Raster Calculator in the Arcmap environment, the average annual soil erosion map for the entire Atashgah watershed between 0.09 and 11.02 tons It was calculated per hectare per year. The results of the evaluation of the soil loss map on the land uses of the studied area showed that dry land use with an average soil erosion of 0.48 tons per hectare per year has the highest soil loss and good pastures with an average erosion of 0.21 tons per hectare per year has the lowest. They have soil waste among other uses in the region. In this research, it was tried to use GIS capabilities to create the required data of RUSLE model. Finally, it is suggested to control the process of land use changes in the Atashgah watershed by determining grazing capacity, vegetation management, and take steps to restore, improve and develop pastures. Therefore, it is expected that this study and the results of this research will pave the way for the implementation of better and more scientific management by competent managers and planners in this field.

Desertification asone of the most important of environmental threats in the present century,is one of the main obstacles to meeting the needs of the inhabitants of arid and semi-arid areas.better understanding of desertification severity and determining the most effective factors on it are the first steps to de-desertification. For this purpose, the severity of the Jiroft plain to desertification was investigated using IMDPA method on the basis of geological and geomorphological criteria. Firstly work unit map was created using geology, land use map, Landsat 8 satellite imagery and Google Earth data. In each unit the "slope", "land use" and "erodibility" indices scored and combined with each other by calculating geometric mean of indices, finally the map of desertification hazard was generated in GIS10.3 software. The results of this study showed that Jiroft plain was classified in moderate class (II) of desertification hazard. Accordinglyalthoughin the Jiroft plain the geological and geomorphological factors have moderate intensity on desertification but it can be turning a risk to an environmental crisis by unsustainable use of lands and natural resources. According to findings, it can be concluded that the management strategies and landuse activities in Jiroft Plain needs to consider the spatial planning.Desertification asone of the most important of environmental threats in the present century,is one of the main obstacles to meeting the needs of the inhabitants of arid and semi-arid areas.better understanding of desertification severity and determining the most effective factors on it are the first steps to de-desertification. For this purpose, the severity of the Jiroft plain to desertification was investigated using IMDPA method on the basis of geological and geomorphological criteria. Firstly work unit map was created using geology, land use map, Landsat 8 satellite imagery and Google Earth data. In each unit the "slope", "land use" and "erodibility" indices scored and combined with each other by calculating geometric mean of indices, finally the map of desertification hazard was generated in GIS10.3 software. The results of this study showed that Jiroft plain was classified in moderate class (II) of desertification hazard. Accordinglyalthoughin the Jiroft plain the geological and geomorphological factors have moderate intensity on desertification but it can be turning a risk to an environmental crisis by unsustainable use of lands and natural resources. According to findings, it can be concluded that the management strategies and landuse activities in Jiroft Plain needs to consider the spatial planning.Desertification asone of the most important of environmental threats in the present century,is one of the main obstacles to meeting the needs of the inhabitants of arid and semi-arid areas.better understanding of desertification severity and determining the most effective factors on it are the first steps to de-desertification. For this purpose, the severity of the Jiroft plain to desertification was investigated using IMDPA method on the basis of geological and geomorphological criteria. Firstly work unit map was created using geology, land use map, Landsat 8 satellite imagery and Google Earth data. In each unit the "slope", "land use" and "erodibility" indices scored and combined with each other by calculating geometric mean of indices, finally the map of desertification hazard was generated in GIS10.3 software. The results of this study showed that Jiroft plain was classified in moderate class (II) of desertification hazard. Accordinglyalthoughin the Jiroft plain the geological and geomorphological factors have moderate intensity on desertification but it can be turning a risk to an environmental crisis by unsustainable use of lands and natural resources. According to findings, it can be concluded that the management strategies and landuse activities in Jiroft Plain needs to consider the spatial planning.Desertification asone of the most important of environmental threats in the present century,is one of the main obstacles to meeting the needs of the inhabitants of arid and semi-arid areas.better understanding of desertification severity and determining the most effective factors on it are the first steps to de-desertification. For this purpose, the severity of the Jiroft plain to desertification was investigated using IMDPA method on the basis of geological and geomorphological criteria. Firstly work unit map was created using geology, land use map, Landsat 8 satellite imagery and Google Earth data. In each unit the "slope", "land use" and "erodibility" indices scored and combined with each other by calculating geometric mean of indices, finally the map of desertification hazard was generated in GIS10.3 software. The results of this study showed that Jiroft plain was classified in moderate class (II) of desertification hazard. Accordinglyalthoughin the Jiroft plain the geological and geomorphological factors have moderate intensity on desertification but it can be turning a risk to an environmental crisis by unsustainable use of lands and natural resources. According to findings, it can be concluded that the management strategies and landuse activities in Jiroft Plain needs to consider the spatial planning.Desertification asone of the most important of environmental threats in the present century,is one of the main obstacles to meeting the needs of the inhabitants of arid and semi-arid areas.better understanding of desertification severity and determining the most effective factors on it are the first steps to de-desertification. For this purpose, the severity of the Jiroft plain to desertification was investigated using IMDPA method on the basis of geological and geomorphological criteria. Firstly work unit map was created using geology, land use map, Landsat 8 satellite imagery and Google Earth data. In each unit the "slope", "land use" and "erodibility" indices scored and combined with each other by calculating geometric mean of indices, finally the map of desertification hazard was generated in GIS10.3 software. The results of this study showed that Jiroft plain was classified in moderate class (II) of desertification hazard. Accordinglyalthoughin the Jiroft plain the geological and geomorphological factors have moderate intensity on desertification but it can be turning a risk to an environmental crisis by unsustainable use of lands and natural resources. According to findings, it can be concluded that the management strategies and landuse activities in Jiroft Plain needs to consider the spatial planning.Desertification asone of the most important of environmental threats in the present century,is one of the main obstacles to meeting the needs of the inhabitants of arid and semi-arid areas.better understanding of desertification severity and determining the most effective factors on it are the first steps to de-desertification. For this purpose, the severity of the Jiroft plain to desertification was investigated using IMDPA method on the basis of geological and geomorphological criteria. Firstly work unit map was created using geology, land use map, Landsat 8 satellite imagery and Google Earth data. In each unit the "slope", "land use" and "erodibility" indices scored and combined with each other by calculating geometric mean of indices, finally the map of desertification hazard was generated in GIS10.3 software. The results of this study showed that Jiroft plain was classified in moderate class (II) of desertification hazard. Accordinglyalthoughin the Jiroft plain the geological and geomorphological factors have moderate intensity on desertification but it can be turning a risk to an environmental crisis by unsustainable use of lands and natural resources. According to findings, it can be concluded that the management strategies and landuse activities in Jiroft Plain needs to consider the spatial planning.

The type of land use, the amount of vegetation and their management, play an important role in the carbon sequestration capacity of the ecosystem. Therefore, in order to estimate soil carbon sequestration over time affected by vegetation type, in Gonabad city, first using remote sensing data of ETM and TM satellite images, land use map of the city for the years 1387 and 1397 based on the maximum probability classification method. Similarity was provided. Vegetation index was also calculated for the images. In order to estimate the amount of soil carbon sequestration in the two years studied and to investigate the relationship between depth, texture and percentage of soil nitrogen with the amount of carbon sequestration in pistachio and wheat, soil test results and GPS points of these uses were prepared using independent t-test And regression relations data analysis was performed. The results showed that different land uses with different vegetation levels have different effects on soil carbon sequestration. So that the total amount of soil carbon sequestration in pistachio orchards in 1397; It had the highest rate of carbon sequestration per hectare. The study of the relationship between depth, texture and percentage of soil nitrogen with carbon sequestration showed that there is a positive relationship between the percentage of nitrogen, silt and soil clay and a negative correlation between sand and carbon sequestration.

Today, industrial units have become industrial complexes and towns and are expanding rapidly. In most of these areas, comprehensive and appropriate studies have not been conducted from the perspective of land use planning, therefore environmental parameters such as proper distance from aquifers or other water sources such as wells, springs and aqueducts and proper privacy have not been studied. Also, most of the wastewater of industrial will being injected directly into the ground through absorption wells without treatment, and consequently, it will pollute the groundwater sources. Therefore, knowing the status of groundwater vulnerability is one of the important principles in groundwater resource management. Vulnerability The possibility of groundwater pollution is a qualitative concept and cannot be measured and must be deduced from other information that can be measured. Various methods have been proposed for groundwater vulnerability. Overlap methods combine the parameters that control the movement of pollutants from the ground to the saturated area and determine an index called the vulnerability index in different parts of an area. One of the most widely used and well-known methods is the DRASTIC model overlap index (Rouhi et al., 2017). In Najafabad city, due to having an arid and semi-arid climate and providing most of the water needs from groundwater resources, attention to the vulnerability of groundwater resources is essential. On the other hand, in the study area, the presence of land uses such as Alavijeh city, Alavijeh industrial town and agricultural land use on the aquifer increases the probability of point and non-point source pollution entering the aquifer environment and its vulnerability. Therefore, in this study, the vulnerability of the aquifer was investigated using the correct model to be informed of its status, the necessary measures are taken.

 Scope of the study Alavijeh industrial town is located at km 70 of Isfahan-Alavijeh road and the closest residential area to this option is Alavijeh city, 2 km east of it (Figure 1). The existing Alavijeh industrial town with an area of 200 hectares, due to its location in Najafabad city, has greatly contributed to the economy of this city. DRASTIC model It is the numerical ranking model of the US Environmental Protection Agency and the American Water Wells Association to assess the strength of groundwater vulnerability. This model consists of seven measurable and effective hydrological characteristics in the transfer of pollution to groundwater, including groundwater depth, artificial recharge, aquifer, soil environment, slope, unsaturated zone constituents and electrical conductivity. These layers are provided in the GIS environment (Rahman et al., 2021). To determine the relative importance of each layer, according to the importance of the impact on the pollution of the groundwater system, a relative weight of 1-5 is considered. In this model, the ranks of each of the hydrological characteristics are assigned a rank based on their impact on vulnerability. At the end, seven prepared layers are stacked and the final layer of groundwater vulnerability is obtained.

 Assess the risk of aquifer vulnerability Alavijeh industrial town is located in the study area of Morchekhort and Zayandehrood grade 4 basin. The wells in the study area are of smallholder type and have been drilled mainly for agricultural purposes. Based on the analysis of groundwater level curves in the area, the maximum groundwater level is 2135 meters, which gradually decreases to the east of the groundwater level and reaches at least 1805 meters (average: 1971 meters). It is also the direction of groundwater flow in the region, from northwest to southeast. According to the Piscopo method, the artificial recharge index is ranked 3rd and 6th in the industrial town. The constituents of the aquifer environment have a score of 4 (sand particles with clay (50%) with conglomerate) and the unsaturated area has a score of 3 (sand, rubble and clay). Due to the granulation and characteristics of sediments between the surface and groundwater, the presence of fine-textured materials such as clay and loam reduces the ability to transfer contaminants from the soil surface to groundwater. Therefore, the probability of migration and transfer of pollutants in the area to groundwater has been moderate to low. On the other hand, due to the low slope of the area, the contact time of surface water and pollutants with the ground surface is increased and there is a greater chance of infiltration, which increases the vulnerability in the area. In general, the Drastic index is in the range of 23-230. In the study area, this index was obtained between 50-130.Aquifer vulnerability was divided into 2 zones of low and medium vulnerability. As shown in Figure 1, about 30% of Alavijeh industrial town is located on the aquifer and the western part of the industrial town has a higher potential forvulnerability than the eastern part. In the western part of the study area, the aquifer in the western part is more vulnerable due to the higher rank of aquifer nutrition and soil environment.Due to the establishment of metal, non-metallic and textile industries up to grade 5 in the industrial town, wastewater pollution caused by the activities of these industries, if environmental standards are not observed and discharged to absorption wells can cause severe groundwater pollution. It is noteworthy that the existing town has more than 80% of the units connected to the town's treatment plant system and 20% of the remaining units are not connected to the treatment plant system. These units have either pre-treated, purified and recycled water in the production process and a number of units are also used absorbing wells and not connected to the wastewater treatment system. However, it is necessary to require all units to connect to the industrial town treatment plant to prevent the transfer of contaminant load to groundwater sources. Another land use in the study area that can increase the vulnerability of the aquifer is the presence of the city of Alavijeh on the aquifer, which is located two kilometers from the industrial town of Alavijeh. Although the city is in a low vulnerability zone, it does not have a treatment plant and sewage is discharged to absorption wells. Also, the area around this city and the industrial town are covered with agricultural lands and gardens, and agricultural lands are located on the aquifer, which in case of excessive use of pesticides and chemical fertilizers, especially nitrate fertilizer, pollution of groundwater sources will occur.

One of the goals of urban planning is to provide appropriate types of public services, so the quantity and quality of access to these services is one of the most important indicators to assess whether or not regions have urban land use facilities, which in the case of balanced distribution can lead to spatial justice. Accordingly, this study was conducted to investigate and assess the status of informal settlements in Ardabil in terms of public welfare services in the land use system and prioritize them for future planning. The research method is applied according to the purpose and in terms of nature and descriptive-analytical method. The data required for this study have been collected through field and documentary methods. The statistical population of the study corresponds to 15 neighborhoods of informal settlements in Ardabil. Excel and Spss software were used to analyze the data. Then, in order to assess the status of public welfare services, the target area was weighted using entropy method and ranked using Vikor technique, and finally, ArcGIS software was used to display it on the map. Based on the criteria used and the results of the implementation of the Vikor technique, among the informal settlements of Ardabil, Salmanabad neighborhood with the highest score and Iranabad neighborhood with the lowest score are in the first and last level, respectively. Findings of the study reflect that the most weakness and inadequacy among the studied indicators are related to green space uses as well as sports and recreation. Therefore, development-oriented planning in accordance with the strengths, weaknesses and priorities of each neighborhood is necessary.

Air pollution has a serious impact on human health and the effects of different land use parameters and physical urban structure can not be ignored in the distribution and emission of air pollutants. To this end, in this study, the effect of land use pattern on spatial changes of pollutants in Tehran in the period 2011-2020 has been investigated..To achieve this goal Landsat satellite images as well as pollution data of Tehran Air Quality Control Center in 2011 and 2020 were used. The artificial neural network method was used in ENVI software to classify satellite images and determine the type of uses and Kriging model in Arc GIS software for zoning air pollution concentration in Tehran. The findings of this study show that Increased construction in the west and north of Tehran in these parts of the city has increased the concentration of pollutants. In return Land use change from barren lands to urban green spaces in the east and southeast of Tehran has reduced the concentration of urban air pollutants in these areas.

Sustainable land management depends on preparing a multi-time land cover map, it is necessary to determine the process of destruction or improvement of the natural covers for these areas by identifying the type of land cover / land use at different times. One of the most important and serious issues that endanger the sustainable development is land degradation. Man-made destructive activities in nature, including deforestation, overgrazing and pasture conversion, unprincipled construction, and increased agricultural cultivation, which may also have important socio-political consequences, are increasingly destructive. Land degradation and destruction of natural resources in developing countries is much more than other countries, so that natural resources and the environment are the most vulnerable parts of these countries, and usually the first part of poor and developing countries that are destroyed and occupied in line with economic growth and development, is their natural resources. Population and urbanization growth is one of the most important factors in the destruction of natural resources in developing countries. In fact, the most important ecological impact of urbanization and distribution urban areas is the destruction of natural resources and encroachment on the natural environment. Iran's natural resources have also been severely disrupted over the past five decades, and in many cases, irreparable effects have been inflicted on it. So that, according to the reports published by the Forests, Rangelands and Watershed Management Organization (FRWO), the level of the country's rangelands since the nationalization of forests and rangelands has increased from about 100 million hectares to less than 85 million hectares. On the other hand, Sustainable land management depends on the preparation of land use maps at different times. In fact, land classification results are the basis of many environmental and socio-economic programs. The study of changes in natural areas provides valuable information for better management of natural resources in order to protect, rehabilitate, develop and even utility them. Therefore, it is necessary to identify and monitor the process of destruction or improvement of the natural cover of these areas by classifying the type of land cover / land use of the target areas during different times and determining the amount of possible changes. This study aims to determine the tenure and conversion of natural areas using coverage / land use maps of the city of Sisakht and its surroundings and also to analyze the extent of its changes during the years 1988 to 2020 with the use of remote sensing.

Detection of change, the process of determining and / or describing changes in land cover / land use characteristics are performed on the basis of rearranging multi-time remote sensing data and satellite data. On the other hand, the appropriate spatial resolution of satellite data is determined by the user needs and the scale of the study area. Therefore, Landsat satellite data with moderate spatial resolution and appropriate time coverage is the most widely used data on a regional scale that is widely used in different parts of the world to classify land use to determine land use. Is placed. In order to prepare the land use map in this research, appropriate quality data in terms of cloudiness and dust of Landsat 5 and 8 satellites related to July 1988, 2000, 2011 and 2020 were used. For this purpose, the necessary radiometric, atmospheric and geometric corrections were applied to the satellite data. Then, to increase the accuracy of classification and increase the accuracy of land use map, a data set layer was created by combining different spectral and spatial bands. In order to increase the accuracy of detecting land cover types with a wide range of spectral characteristics, the thermal band of satellite data was also included in the data set. Finally, in order to classify as accurately as possible and prepare a map corresponding to the reality of land cover / land use in the study area, two powerful monitored base pixel methods including maximum likelihood and support vector machine were used to compare their accuracy.All corrections, data preparation, data collection, classification and analysis, and extraction of maps were performed using ENVI® 5.3, ArcGIS® 10.7, Google Earth Pro 9, Excel 2016 software.

The results of this study showed that the level of natural areas of forests and ranges in the study area has decreased by at least 24% during the 32-year period. In contrast, the gardens, construction and human intervention, and occupation has increased. So that the natural covers of the region, including the forest and range, has decreased from 4678 hectares in 1988 to 3327 hectares in 2020. While, the area of orchards has increased from 583 hectares in 1988 to 1331 hectares in 2020. In general, the destruction of natural resources or their conversion to other land uses is affected by economic and social issues. The results also show that while the effect of increasing the population of Sisakht city on the destruction and tenure of natural areas, the factor of turning forests and ranges into gardens and orchards plays a more prominent role in the destruction and tenure of natural resources. In other words, according to demographic statistics published by the Management and Planning Organization of Kohgiluyeh and Boyer-Ahmad Province, although the city of Sisakht, unlike many other cities in the country, is not considered a major city in accepting immigrants and its population growth relative to many cities have not been many (7856 people in 2016 compared to 6814 people in 2006), the level of destruction of natural resources is significant. The main factor can be considered in the attractiveness of gardening and increasing the garden areas by utilizers. Undoubtedly, the process of destruction and tenure of forests and ranges, and natural resources will not stop as long as profiteers and opportunists hope for the transfer of natural areas. Considering the economic costs and environmental considerations, the change of national land use and natural areas will have serious consequences on the path of sustainable development. Therefore, any humanizing change in the environment of the natural areas of each region and its conversion to other land uses should be based on the land use plan of that region.

Challenges of water resources and surface changes of Lake Urmia and the society under its influence are serious concerns about the dangers and destruction of the environment of the basin. Paid. Therefore, in a recent study, using Landsat satellite images from 2000, 2010 and 2020, it has dealt with the trend of changes in the six major uses. And with the help of spatial and temporal analysis, the method of dispersal of territorial measures has traced the footprint of destruction and water needs and environmental degradation. Therefore, the results show that during the last 20 years, the area of man-made buildings has increased by 40%. Also, forests have experienced a reduction rate of only 5%. Therefore, water bodies have reduced their area by 15%, and finally the speed of these changes in the first period was much more severe than the period 2010 to 2020. In the second period, pastures and poor soil cover or pastures have undergone the most changes. This trend is mostly dependent on climate change.

The aesthetic evaluation of the landscape shows that in the process of planning and intervention in the community to promote a healthy and active lifestyle In evaluation, consider both the environmental structure and the views of individuals in relation to the environment and the landscape.The aim of this study was to determine the indices of visual and aesthetic landscape of landscape ecology approach to economic valuation of landscape was. The indicators considered include the complexity index, the index of naturalness, the monitoring index, and the visibility indicator. The method of valuation was used for economic valuation and the analysis of the parameters was performed using the Logit model. The results showed that the indicator of naturalness is better than other indicators of the status of the landscape surface. People who prefer to keep Preserving the natural landscape prefer to others. They are willing to pay a monthly fee of 21054.82 Rials to maintain the landscape. Finally, the total value of the landscape in the study area was estimated at 24,952 billion rials.

Rising ground temperatures and the creation of urban thermal islands are an important issue in the 21st century. Because it deals with the complex challenges of urban population growth, global climate change, public health, and increasing energy demand for cooling. Therefore, the purpose of this study is to estimate the surface temperature using remote sensing methods such as the Sinlge Chaneel algorithm. For this purpose, satellite images related to the study area were obtained for 9/22/2019. After performing radiometric and atmospheric corrections in Envi software, the satellite image was called in Qgis software, and with this algorithm, the Land surface temperature was estimated, and the results showed that the Land surface temperature fluctuated between 20.55 and 50.55. ° C. Also, from the study of the impact of land use on the temperature of the region, it was found that water resources and natural cover, including Aghgol wetland, have the greatest role in reducing the temperature of the region and the lower classes have a temperature. But, residential uses and barren lands have increased temperatures due to higher heat absorption and are at higher temperatures classes.

Albedo is a very important physical component in meteorology and climate, radiation transfer studies and calculation of Earth's radiation reserve and plays a very important role in climate change research and land surface models. In this study, Landsat 8 images during the summer of 2013 to 2016 were used to investigate the land surface albedo in different land uses in Yazd-Ardakan plain. Then, land use map of the study area was prepared using a variety of supervised classification methods for satellite imagery. The results showed that the map prepared with the maximum likelihood method had the highest accuracy and that map was used as the basis. The results showed that the highest albedo belonged to the Barren lands with an average of 0.31 and the lowest to the agricultural land with an average of 0.20 and respectively, from the highest to the lowest albedo coefficient for Barren lands, residential, sand dune, pasture, mountain, and agricultural land uses and Landsat image can be used with great confidence to estimate the surface albedo.

Human activities such as agriculture and urban development (particularly settlement expansion and road construction) as well as biological and environmental processes, structure and pattern of the landscape. The aim of this study was to investigate the effects of land use changes on the landscape pattern of Malayer in the twenty years term. In this research, Landsat satellite imagery of 1997, 2007 and 2017, and the RS for producing land use maps and FRAGSTATS software were used to calculating and quantify Landscape metrics.The metrics used include CA, MPS, LSI, LPI, NP and IJI. The results showed that from 1997 to 2017 the area of residential use and water resources decreased and the area of agricultural use and bayer lands increased. So that increased of the residential use of 75373.11 hectares with an area of 14675.04 and water resources with an area of 23918.31 hectares with a total area of 248.76, the water resources of this city have decreased by 32/58 percent over the course of twenty years, and the Bayer lands from 66717150 in 1997 to 1820,86 in 2017, and agricultural use has increased from 13,30029 to 38388 in area. Also, decreased NP, LSI, and IJI in whole landscape.

Land use mapping is the basic tools for administrators and land planners. Different methods have been proposed for land-use mapping. The latest and most important methods is using remotey sensed data for Land-use mapping. The aim of the present study was performance evaluation of classification decision tree and maximum probability methods using Landsat 8 image of 2013 for land-use mapping of Yazad- ardacan plant. Different land use classes were difined using training samples comperison of classification. results of four different methods of, Gini decision tree, entropy, Cta and maximum probability respectively thus, Show that Kappa coefficient of 85.78, 88.95, 76.78 and 91.15 the maximum probability than decision tree methods has a higher accuracy. Map area defined by the different methods of classification, are similar in sandy lands and rocky lands. The greatest differences were observed in area of medium sand dunes and minimum differences were related to the rocky lands. Therefore, the present study proves the efficiency and feasibility of thed maximum probability method in the better classification of remote sensing images.

In the recent years, International Anzali wetland has been exposed to changes by dumping sewage water, land uses changes and sediment deposition that caused the reduction of the wetland depth and the aquatic growing up. In this study, the effects of land uses changes on wetland's water quality was investigated from 1985 to 2014 by determining the land uses on wetland using GIS and measuring the water quality parameters. The results showed that most part of the forest was replaced with agricultural fields and urban areas respectively. Based on Principal Component Analysis (PCA), urban and agricultural area were the most related with the first principal component (PC1). Nitrate, total alkalinity, BOD5, COD and conductivity were less related respectively. The result showed that during these years, forest lands changed to agricultural fields and urban area.
Keywords: