Extended abstract:Introduction:Since Industrial Revolution in late 18th century, the world population has increased exponentially in an astonishing rate. Human population from 1 billion in 1830 reached around 7 billion in 2010. Importantly, the world’s urban population has increased much faster than the rural one, rising from 14% in 1900 to 47% in 2005, and will be about 61% by 2030. Furthermore, future population growth will occur primarily in urban areas. Although urbanized areas cover only about 3% of earth’s land surface, they cannot be ignored as urban growth causes very large changes in environmental conditions.

Introduction: Ecosystems provide a wide range of services that vary in quantity and quality depending on the type of ecosystems and their status. Estimating the ecosystem services value (ESV) is very important to support land use planning processes. Ecosystem services are under great pressure due to urban growth and its effects. The human activities that reduce ecosystem services include land use/land cover (LU/LC) change driven by agricultural activities and urban growth. In this paper, we assessed LU/LC dynamics in Golestan Province using change detection and Markov chain as inputs for ESV of different land use types to estimate the amount of services. We also used sensitivity analysis to explore the robustness of results by 50% adjustment of value coefficients. Material and methods: Golestan Province is one of the 31 provinces of Iran, located in the south of the Caspian Sea. In this study, multi-temporal data of LU/LC were produced from multispectral Landsat imagery acquired on two separate years (1984 and 2015). We also analyzed ecosystem service values for 2035. Markov chain was used for quantity forecasting. Markov Chain Analysis is a convenient tool for modeling land use change, when changes and processes in the landscape are difficult to describe. LU/LC data were analyzed using Ecosystem Services Value (ESV) for different biomes. Results and discussion: Land cover classification indicated that settlements were the most increased land cover over the study period. From 1984 to 2014, ecosystem service values of forests decreased from 1722 to 952 million dollars. Annual value of 22 ecosystem services was estimated. In terms of the estimated ESV, food production, raw materials, climate regulation, nutrient cycling, biological control, genetic diversity and recreation were reduced while the rest of ESVs were increased/decreased. The effect of using different coefficients to evaluate the total ESV in Golestan Province was evaluated. The coefficient of sensitivity (CS) of these analyses was less than one in all cases. Our results of analyses indicated that the total ecosystem values estimated for Golestan Province were relatively inelastic, which also suggests that our ecosystem value evaluation is reasonable. According tothe LU/LC within the landscape, our results indicate that rangelands and forests provide a higher level of ecosystem service than others due to the relatively larger area coverage and higher value coefficients and hence a reduction in this particular component of the ecosystem hampers a balanced flow of services from the landscape. Conclusion: Ecosystem service value estimation based on LU/LC analysis is very important to indicate the changes in the amount of services through urban growth on spatial and temporal scales. Such estimationsin local, regional and global scales are important in influencing land use planning processes through modifying national accounting systems to reflect the true values of ecosystem services so that it will be ultimately used as a basis for sustainable development. Another benefit could be related to land use optimization projects to increase ecosystem services.

Extended AbstractIntroductionLand use and land cover change includes the conversion of natural land cover to impermeable surfaces (concrete and asphalt), a product of the rapid growth of cities and human settlements. One of the topics that has attracted the attention of researchers in recent years is the impacts of these changes on the temperature of the earth's surface as a vital parameter for the environment and human life. The cities and settlements of Mazandaran province in Iran have struggled in recent years due to the significant increase in the arrival of tourists and migrants with the increase in environmental and human heat released due to changes in land use and land cover. The purpose of this study is to investigate the impacts of land use and land cover changes on the land surface temperature in Mazandaran province in a ten-year period. The results of this study can play an important role in better planning the regional development of Mazandaran province and create healthier residential environments and provide very useful information to help manage and plan the development of residential land to achieve environmental sustainability and development.  MethodMazandaran province with an area of 23756 square kilometers, located in the southern part of the Caspian Sea. According to the last general census in 2016, the population of the province was 3283582 with 1084798 households. In terms of geomorphological situation, Mazandaran province can be divided into three main units: plains, foothills and mountains. The processed images of the Madis sensor on the Google Earth Engine platform have been used to prepare images related to the land cover and surface temperature of Mazandaran province in a 10-year period (2012-2022). Detection of land use and land cover changes based on the land cover classification scheme by the International Geosphere-Biosphere Program (IGBP) with a resolution of 500 meters and daily and nighttime surface temperature data and by recalling and processing Madis sensor images with a resolution of 1km were obtained. In order to analyze the spatial distribution of earth surface temperature data, Moran's statistic index was calculated using Moran's spatial autocorrelation analysis tool in ArcGIS. Also, hot spot analysis tool was used in ArcGIS, which is used to discover spatial cluster arrangements in land surface temperature data. Result and discussionThe findings of the land cover classification have shown that the urban lands of Mazandaran province have increased by 1244 hectares during the 10 years, which shows the increase in constructions and the expansion of urban and rural areas. The results of calculation of night and day surface temperature changes show lower temperature at high altitudes and higher temperature at lower altitudes. Urban lands, settlements and peripheral parts of the main communication axes have higher temperatures than other parts of the province. In general, from 2012 to 2022, the night temperature of the province has increased by 1.02 degrees Celsius, the daily temperature by 1.89 degrees Celsius, and the day and night temperature by 1.46 degrees Celsius. In 2022, urban lands with an average temperature of 21.04 degrees Celsius were the hottest parts of the province. The findings of the Moran's statistic index, calculated using the Moran's spatial autocorrelation analysis tool, showed a cluster pattern for the province's night and day land surface temperature data. Also, the findings of analysis of hot spots (Getis-Ord Gi*) based on day and night temperature data showed the accumulation of hot clusters in urban areas, especially in plains. What is most important is that more than 98% of urban land is in hot clusters and the area of hot clusters of urban land has also had an upward rate during the studied period in terms of land cover area. ConclusionThe article focused on identifying the changes in land cover and surface temperature of Mazandaran province using remote sensing and GIS techniques, the relationship between them has been investigated using Moran's index and hot spot analysis from 2012 to 2022. According to the findings, in addition to the increase in the day and night temperature of the province by 1.46 degrees Celsius, more than 98% of urban land is located in hot clusters, which confirms the existence of the phenomenon of urban heat islands in the cities of Mazandaran province, and these areas introduced as one of the main factors in increasing the temperature of the earth's surface. The high population density of the province, the influx of migrants which accompanied by construction of seasonal and monsoon houses, have threatened the environment friendly land covers into urban and residential covers that minimized the possibility of surface water infiltration, contributed to increasing the surface temperature of the province. So that the area of hot clusters of urban land has had an upward rate during the studied period in terms of land cover area. Considering this destructive trend, it is necessary for urban planners and decision-makers to direct the development plans of urban and rural areas for the future to minimize the increase in the temperature of the earth's surface and the threats caused by climate change.

Fast population growth in urban areas has resulted in a significant shortage of aboveground spaces and has led to an increase in underground structures. Different types of underground spaces and structures, including underground utility tunnels, subway tunnels, subway stations, underground shelters, culverts and etc., may exist in any large city.The presence of subsurface structures has static and dynamic interaction with their environment and adjacent constructions. Recently, the effect of underground structures on the acceleration response of the ground surface has attracted the attention of researchers, since it has been concluded that the presence of these subsurface structures also affects the seismic response of nearby ground.There are many parameters affecting the presence of underground structures on the acceleration response at the ground surface. These parameters include soil medium characteristics, excitation frequency and amplitude, tunnel diameter, depth of construction, and flexibility ratio of the lining.In this paper, a nonlinear numerical model was first verified against dynamic centrifuge test results performed at the Korean Advanced Institute of Science and Technology (KAIST) on an underground subway tunnel and, then, the effect of underground structure lining flexibility on the acceleration response at the ground surface was investigated. In this regard, the acceleration response at ground surface for three different materials of the lining was studied. From parametric studies, it was concluded that the same values of flexibility ratio for two tunnel systems with different lining material resulted in the same acceleration response at the ground surface. The flexibility of the lining affects the acceleration response at the ground surface; however, it depends on the frequency content of the input motion and the natural frequency of the system. Stiffer lining resulted in amplification of motions with short periods, which threatens short buildings, whereas, softer lining amplifies motion with longer periods, which can be dangerous for tall buildings. Therefore, the flexibility of the lining plays an important role in acceleration response at the nearby ground acceleration response.

Following the fisher’s hypothesis about the relationship between asset returns and inflation, numerous studies have tried to test the hypothesis with various data sets. Contradiction in the findings resulted to the proxy hypothesis of Fama (1981). In present article, survey the theoretical and empirical literature, and conduct a test for inflation hedging ability of land, gold and stock in Iran. Considering the seasonal characteristics of the data (1385-1355), we use the HEGY (1990) unit root test, and VECM methodology to estimate long and short run relationships. Our findings show that in the long run, all three types of assets hedge against inflation. However, in the short run, we observe that money reserve, oil prices and real GDP are significant determinants of the assets returns.

Extended abstract:Introduction:Land is one of the primary natural resources required for many activities in cities. A city is expanded not only by population, but also by changing in the spatial dimensions. Changes of land are a natural process and can't be stopped, but it can be organized. Supervising land zoning in the rules of city zoning to residential, commercial, industrial, and administrative areas is one of the important issues of urban life. Land use is one of the basic concepts in urban and regional planning. Thus, in optimized urban and environmental management, it is necessary to know about the proportion of land use changes / land cover and their causes. Remote sensing is considered for monitoring and supporting decision making for effective tools related to urban planning. The modeling for prediction of land use changes by remote sensing data is also a helpful tool that can manifest a good recognition of land use changes and present good solutions for management. The goal of the current article is to survey changes of Kermanshah city's zones through Landsat satellite images in the past three decades (1985-2013) and to predict changes until 2026 by using a combination of regression logistic, Markov chain and Markov CA models.

In environmental models, Vegetations are considered as an important part in controlling environmental changes. To determine the importance of vegetation on land surface temperature (LST), preliminary preprocessing was performed on Landsat 8 image and a split window procedure was used to determine surface temperature. Temperature difference with the surrounding synoptic stations was estimated to be about 2. 5 ° C, which confirmed the accuracy of the computational temperature. In addition to Normalized difference vegetation index (NDVI), other variables such as Normalized difference water index (NDWI), elevation, Aspect, Landuse/Landcover (LU/LC) and heat loading index were used to show the effect of vegetation on temperature. LU/LC map of city area was obtained by using a 7 categories training samples by Neural Network Classification (MLP). Total Kappa index was calculated 0. 82. Then, the points were randomly extracted by stratified sampling method separated for 7 LU/LC categories and divided into two groups of testing and training. Values of the mentioned variables were extracted for these points and random forest regression was used to investigate their effect on surface temperature. Performance of the model was evaluated and validated using mean absolute error (MAE), mean square error (MSE) and root mean squared error (RMSE). Based on sensitivity analysis by Mean decrease accuracy, NDVI, Aspect and NDWI had the most effect on surface temperature distribution. Highest surface temperature with 29 ° C was for uncoated rangelands and its lowest with 25 ° C was for human-made areas, including Javanrud and peripheral villages. The results of this study showed that the NDVI plays a very important role in land surface temperature changes.

The main objective of this research is to improve the distribution of electrical potential on spacecraft surfaces by changing the surface coatings to reduce the risk of electrostatic discharge in the spacecraft. For this purpose, SPIS software, the EU standard software for modeling and simulating the interaction of space plasma with the spacecraft is used. The spacecraft has 8 nodes, and each node is related to a particular substance. The simulations were compared with the variation in the materials of these nodes in terms of differential electric and floating potential. Investigating materials that differed in the differential electric potential of zero showed that they are conductive materials. In order to choose among several conductive materials, these materials were compared in terms of electric floating potential. Simulations on satellite surfaces showed an average of 11% improvement in the electrical potential on surfaces