تصاویر لندست

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.

Heyran Ardabil road is one of the areas with potential for range movements due to various geological characteristics such as tectonics, lithology, seismicity and climatic conditions. For this purpose, radar images of the European Space Agency's Sentinel 1 satellite have been used to identify and estimate the speed and amount of movements of unstable slopes overlooking the Heyran-Ardabil communication routes over a six-year period from 2015 to 2021. In order to process the information, it has been used using interference technique and SARSCAPE software. Landsat 8 image was used to prepare the land use map of the study area using the object-oriented classification method in eCognition Developer64 software. Was extracted. The results obtained in this study showed that radar satellite images and interferometry techniques are very suitable for detecting slope instability and calculating the amount of displacements due to their extensive coverage, high accuracy and abundance of data. The maximum amount of material movement is in the range of 30 cm in the study area. Which indicates that the area is active in terms of amplitude movements. Land use maps using Landsat 8 image were used using object-oriented classification in the study area. Co-institutionalization of landslide maps with land use layers also confirms the maximum occurrence of landslide area related to forest areas and residential area shows the highest amount of landslide. The reason for this is the climatic conditions and the potential for rainfall in all seasons of the year, the infiltration and direction of rainwater to the lower classes.IntroductionContinuous monitoring of land surface changes and identification of areas prone to slip movements, especially in the area of human settlements and communication infrastructure such as roads and railways, is one of the most effective factors in reducing casualties and natural hazards such as landslides and slopes. So far, several techniques have been proposed such as using the Global Positioning System, geodesy and tachometry, mapping cameras, laser scanning and lidar to monitor surface changes. However, due to the high cost of implementation, time consuming and limited coverage of the use of these methods, in the limited, the use of these methods in a wide range is not cost effective. But in addition to these methods, the radar interference technique with the ability to work in all weather conditions and the duration of day and night and with the ability to cover the ground and high spatial and temporal resolution, today is one of the most accurate (in millimeters) and least expensive Remote sensing techniques for detecting and monitoring surface changes, slow and unstable movements of amplitude around the world.MethodologyHeyran Pass is located on the Ardabil-Stara communication route. This pass is located in the northeast of Ardabil and west of the border city of Astara. Tectonically, the region has obvious faults such as Astara fault. Different formations can be identified in the route of Heyran pass from Namin to Astara. From near Namin to the village of Hiran, the main rock is the Eocene pyroxene andesitic volcanic section. In a part of this route, conglomerate sediments with loose cement with volcanic fragments have been placed on andesitic volcanic sections as igneous discontinuities. From Hiran village to 15 km from Astara, tuff sandstones with a layer of Paleocene andesitic lava and Quaternary sediments are located, respectively.Optical satellite imagery, including Landsat satellite imagery for 2021. In the image processing phase, the 2015 and 2021 Sentinel 1 time series were used in the C-bar. Using image processing with SARSCAPE 5.2 plugin in ENVI 5.3 software platform and using radar interferometry method, landslide affected areas in each area were determined. In the next step, using the survey operation, landslide effects in the area were identified. In order to explain the causes of landslides in the study area, land use data as well as information about observation wells were compared and statistically analyzed with results in the area.Results The results in accordance with the land use map and the landslide map showed that the highest landslides are in the residential area with 30 cm and the forest with 30 cm. The amount of lift in all three uses indicates the amount of 2 to 30 cm of landslide. Sudden landslides and the destruction of vulnerable structures are possible landslide accidents that cause casualties in urban areas. In some cases, these accidents can cause severe and irreparable damage due to high population density or widening of the radius of collapsed lands. However, by institutionalizing the forms, it can be concluded that the highest rate of landslides in residential and densely populated areas as well as forests has the highest rate of landslides.Discussion & ConclusionsThe results of this study showed that radar images have a good potential for detecting slope instability and calculating their displacement. The maximum amount of material movement is 30 cm in the study area. Which indicates that the area is active in terms of amplitude movements. Land use maps using Landsat 8 image were used using object-oriented classification in the study area. The results of matching the land use map and landslide map in Table 3 showed that the highest landslide rates The highest landslide rates are in residential area uses with a value of 30, forest with a value of 30 and rangeland with a value of 24 cm, respectively. . It shows the minimum value for agricultural use with 21 cm and barren with 20 cm. The sudden collapse of the earth and the destruction and collapse of vulnerable structures are possible accidents caused by landslides that face human casualties in urban areas. In some cases, these accidents can cause heavy and irreparable losses due to high population density or the expansion of the radius of the collapsed lands. However, by institutionalizing the shapes, it can be concluded that the highest landslide rate occurred in residential and densely populated areas, and also in forest use, it has the highest landslide rate.