مدل سازی

The emergence and manifestation of the consequences of climate change in recent decades and the importance of global warming, lead to research in the field of climate change simulation using general circulation models (GCMs) for future periods of time. A review of the references that have dealt with this matter in Iran, and evaluating of these researches, can identify their methodology and strengths and weaknesses and guide the compensation of shortcomings. The articles that have been published in the field of projection of climate change in Iran; are reviewed and almost 110 articles that were closer to the subject and purpose of the current research analyzed and the content changes of the articles in the last two decades were also compared and evaluated. the results identified the most widely used GCM models and down scale methods and the amount of content changes of the articles in using several models and scenarios and compared the validation of outputs in the last two decades and revealed their improvement and the shortcomings of the researches. also, the results showed the attention of many researchers in this field on the future of agriculture and water resources of Iran as a semi-arid country

By employing urban growth and development modeling, it is feasible to delineate a developmental trajectory that aligns with the specific circumstances of a city, considering environmental factors, natural elements, and population dynamics. The aim of this research is to propose an urban development model for Shushtar, which can serve as a valuable tool for analyzing the intricate processes of urban transformations. To accomplish this objective, two datasets were utilized: urban land use maps (including educational spaces, healthcare facilities, residential areas, etc.) and Landsat satellite imagery for key land uses such as rivers, barren lands, and forests, spanning three time periods: 1991, 2004, and 2014. These datasets were processed using GIS and MATLAB software. Existing urban land use maps were digitized and subsequently updated using Landsat satellite imagery. Subsequently, influential parameters in urban development were introduced as inputs to the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm. After training the model for the years 1991 and 2004, the predicted results of urban development using the algorithm were compared with the actual situation in 2014, demonstrating a high accuracy of 93.7%. The land use change map, resulting from the change detection process, can be generated based on multi-temporal remote sensing images and their integration with urban land use maps, enabling an analysis of the associated consequences. The use of intelligent algorithms in this research has facilitated modeling with a high level of accuracy. The obtained results are deemed acceptable, and this development has also been predicted for the upcoming years.

In areas with special characteristics such as desert areas, the development of sports is one of the most important options for the development of infrastructure as well as the expansion of the economic origins of these areas. These areas can develop and improve the proposed options for regional tourism. For the development of sports in specific areas such as the desert, it is necessary to provide specific cultural and economic plans that will ultimately lead to the regional development of sports as well as the economic development of the region and the satisfaction of tourists. Desert climate regions in Iran are located among one of the largest desertification belts in the world. Iran is one of the most important countries with significant deserts, whose deserts have high tourism and ecotourism potentials. Tourism in the desert is not only one of the main options for the development of desert and desert sports, but it can contribute to the prosperity of that region based on economic factors that include the costs of desert tourism, the amount of investment in this part of tourism, the rate of return on investment and other issues. also help a lot. 2. Research MethodologyThe current research was qualitative and applied in terms of purpose. Since in this research, in terms of the lack of theoretical foundations, it was not possible to gain sufficient knowledge about the important indicators related to the problem and their relationship with each other, the qualitative approach and the foundational grounded-theory method became the basis of the work; Because it is believed that the grounded-theory of the foundation is beyond all descriptive methods due to its conceptualizations of social phenomena. The foundational grounded-theory method is inductive in terms of approach and based on it, the theory is formed from the concepts obtained from the data. In this research, the approach of Strauss and Corbin (1998) was used, because it has a systematic method for data analysis. The statistical population included all experts and specialists related to sports tourism, desert tourism, sustainable development of tourism and topics related to them. Based on this, academic staff members and researchers in the field of sports tourism, senior managers and experts of sports and youth departments and tourism organization of Yazd province were selected as the statistical population. In the current research, the theoretical sampling method was used, which is one of the main features of the foundational groded-theory. This method is a combination of purposeful and snowball sampling methods, which is done by considering the theoretical saturation index compared to sampling from the research population, thus, finally, 22 people from the statistical population were interviewed. The analysis of the collected data was done through three stages of open coding, central coding and selective coding..3. Results and discussionThe open coding stage started at the same time as the end of the first interview. In this way, all the interview transcripts were prepared and examined word by word and this work was done for all the interviews. Then, in the axial coding stage, the data that were broken down in the open coding stage, are classified based on thematic and conceptual similarity, and this work continues until the concepts assigned to each category, a comprehensive concept and be abstract in this stage, one of the categories obtained in the open coding stage is selected as the main category or phenomenon and placed in the center of the process, and then other categories are related to it. In the current research, the central category, sustainable development of sports tourism, was determined with an emphasis on the capacities of the desert. After performing all the steps related to open and axial coding, a total of 396 primary codes were extracted from the transcripts of 22 interviews and their analysis, which by examining their similarities and classification, 127 more abstract concepts and finally through Classification of similar concepts, 29 main categories were identified; All these categories and concepts were divided under 5 general categories of causal conditions, contextual conditions, intervening conditions, strategies and consequences. The causal conditions included employment based on entrepreneurship, socio-cultural factors, emotion management, a global position of sports and global tourism, and economic growth. Concepts and categories related to background conditions included geographical and security conditions, socio-cultural conditions, political conditions, existence of fans and volunteer forces, natural and artificial roads, laws and regulations, and economic and budget problems. Concepts and categories related to intervening conditions included managerial and structural factors, service-facility conditions, human resources, political conditions, media and information systems, and financial and economic conditions. 4. ConclusionToday, tourism has found a global scope and is considered one of the phenomena arising from the all-round development of technological innovations in the modern era. What has turned tourism into a factor in the development process is the flow of capital, culture and information in an overlap with factors such as increased income, level of well-being, more leisure time and improved communication. One of the determining factors in the tourism industry is to pay attention to sports and its development and strengthening, as well as organizing competitions and events at various domestic and international levels. The role of sports in many economic, social and cultural fields is the necessity of investing in this category, and an economic look at sports seems necessary today. Sports tourism takes place in different regions and includes various propositions according to the type of region and the type of regional options; One of the most important and most powerful of these areas are the deserts, which also form an important part of the nature of this country in Iran, and the present research has investigated the issue of sustainable development of sports tourism with emphasis on their capacities.

This research examines spatial poverty in the rural settlements of Zanjan Province through a descriptive-analytical approach. The study investigates the impact of geographical, infrastructural, and socio-economic factors on the spatial distribution of poverty by utilizing official census data, satellite images, and upper-level plans. Data analysis was conducted using spatial statistical methods, including the Ordinary Least Squares (OLS) model, which identifies relationships between independent variables such as elevation, slope, and distance from urban centers, thereby explaining local variations in poverty indices. Furthermore, the Spatial Poverty Degree Index (SRPDI) was employed to evaluate the influence of these factors on spatial poverty, followed by the synthesis of components through the Spatial Poverty Index (SPI) and clustering analysis. The results indicate that over half of the settlements are situated in high-altitude and steep slope areas, leading to limited access to infrastructure and natural resources. Additionally, low literacy rates and a lack of an active population contribute to unfavorable social conditions in these regions. The findings highlight the need for multidimensional strategies and targeted policies to reduce poverty, including improvements in service access, infrastructure development, and social capital strengthening. This research provides a scientific basis for policymaking aimed at sustainable development and reducing regional inequalities by identifying the complex interrelationships among various factors.

Cultivating new development paths in urban areas requires a strategic planning process. Strategic planning is considered as one of the executive steps of futures research through the presence of citizens, their participation, and their awareness raising in different fields. In this sense, futures research is not a substitute for strategic planning; rather its content upon which the strategy is formulated is of importance. This research is applied in terms of its purpose, and descriptive-analytical research in terms of its methodology. By studying the theoretical foundations and using the Delphi method, influential indicators and variables in strategic planning in the form of 4 general dimensions (physical, socio-cultural, institutional management, and structural-process), and 39 items or sub-indices were extracted. The analysis of the data collected in the current research was done using statistical tests, such as cross-effects analysis and structural equations, GWR tool from the spatial statistics collection, etc., using Micmac, Smart PLS, GIS, and SPSS software. The results of modeling the effects of official institutions on the futures research indicated that "transparency of goals, policies, and official and unofficial instructions of the organization" have the greatest contributions to the direct and indirect effectiveness of futures research in Isfahan. Furthermore, the results of the effective spatial analysis on the expansion of strategic planning in the city of Isfahan showed that the managerial-institutional dimension would have significant effects on the expansion of strategic planning in this city, and the socio-cultural index is among the most important indicators influencing strategic planning at the level of this city.

Urban weathering refers to the processes of loosening, decay, and eventual deterioration of materials used in various urban constructions. This study focuses on assessing the degree of weathering in gravestones from the Joy-e-Horhor and Khold-e-Barin cemeteries in Yazd. A combination of petrographic analyses and longitudinal monitoring of Schmidt hammer rebound values for hundreds of gravestones was employed to achieve this. The findings indicate that in addition to the petrographic characteristics of the stones, such as mineralogical composition, mineral diversity, and rock texture and fabric, local climatic conditions significantly influence the weathering and degradation of these materials. Key processes contributing to the loss of stone durability include temperature fluctuations leading to thermal expansion and contraction, the albedo effect of the stone, wet-dry cycling, and the crystallization and dissolution of secondary minerals like calcite and gypsum. Gravestones made of travertine and marble, characterized by a predominance of calcite minerals and light-colored surfaces, exhibit higher resistance to weathering compared to other lithologies, provided they are not exposed to excessive moisture or frequent washing. In contrast, low-grade metamorphic rocks such as slate and phyllite are the least suitable for gravestones due to their high density of fractures and cleavage planes. Similarly, dark-colored igneous rocks are prone to rapid durability loss, as the differential thermal expansion and contraction of their constituent minerals in response to temperature changes accelerate their weathering processes.

Dry Spells are a defined as a sequence of days without rain. It is very important to evaluate and determine the efficiency of statistical models to estimate the start and end of dry periods and it is widely used in research related to different sectors such as water resources, agriculture, watershed management. Therefore, it is very important to identify the most appropriate models for displaying rainfall distribution to determine the beginning and end of dry periods, because it can be used in various applications such as water resources management, agricultural planning and hydrological departments. The main and important aim of this research is to modelling behavior of dry Spells and determine the appropriate model to evaluation of periods.

At first, 12 rain gauge stations with a period of 1991-2020 were used to analyze precipitation and extract dry spells lasting 15 days or more. The threshold of 5 mm was used as the final threshold in the analysis because the explanation of more than 50% of the weight of the period. Using the IF function in MATLAB software, dry sequences were calculated for the two criteria of maximum and average length of periods. In the next and important step of this research, in order to determine the efficiency and Performance of the best model in fitting and estimating dry periods, it was necessary to examine the probability distribution and relationships of the models. for weight the models we used, SWARA method.

The climatic behavior of dry spells based on the past and present situation showed that in the future, the average dry spells will increase from east to west and from north to south. The results showed that the average annual dry spells change between 7 and 9 days and the deviation from their average change between 9 and 12 days. In general, the decreasing trend of dry spells has a steeper slope in the direction from north to south. The negative binomial distribution has the most weight in the estimation of the eastern and northeastern regions of the province (on average 87% of the weight of courses in each station) and the combined Markov distribution model of order 1 to 10 has the most weight in the tropical regions of the south and southwest of the province (83% of the weight of the courses). And also the distribution of Weibull fit explained 91% of the weight of the courses for the central regions of the province. In the province as a whole, the negative binomial distribution between observed and estimated values has explained a good weight.

The results of this research, based on several statistical methods and their weighting, showed that the behavior of statistical models in estimating the length of dry spells is strongly influenced by the type of climate of the regions and topographical conditions related to it. The combined fitting of the results of the models showed that for proper and accurate evaluation of dry periods, using the results of several models and then their final weighting can provide a correct explanation of the behavior of the periods. In most of the studies about dry spells, weighting of models has not been considered. In Kohgilouyeh and Boyer Ahmad provinces, due to the different topographical conditions and uneven rainfall in the provinces, the length of long-term dry spells, especially in the central, southern and western dry regions, is a function of the rainfall weight and its behavioral fluctuations. Determining the weight of course criteria such as; The length of periods, probability of occurrence and reversibility indicate that the border of dry areas will be vaster and more northerly in the future climate of the province. In most of the studies about dry Spells, weighting of models has not been considered. In Kohgiluyeh and Boyer Ahmad province, due to the different topographical conditions and uneven rainfall in the provinces, the length of long-term dry spells, especially in the central, southern and western dry regions, is a function of the rainfall weight and its behavioral fluctuations. Determining the weight of course criteria such as; The length of spells, probability of occurrence and reversibility indicate that the border of dry areas will be extended and more northerly in the future climate of the province.

The traditional method of chemical analysis has high accuracy and precision. However, it is time-consuming and laborious, and it is not possible to obtain continuous information about the pollutant status over a large area. Therefore, there is an urgent need for a reliable and environmentally friendly method to quickly identify and investigate the distribution of heavy metals in soil and thus identify suspected contaminated areas (Scheuber & Köhl, 2003:33). Remote sensing is one of the ways that can provide a cost-effective and quick solution to investigate the distribution of heavy metals on a large scale using spectroscopic techniques (Bi et al., 2009:16). Habibi et al. (2023:4) also measured and evaluated the concentration of heavy metals in the aerial parts and soil of the tree species of Bandar Abbas city and also identified the species that has the highest potential for absorbing heavy metals. The results showed that the pattern of heavy metals in soil and leaves of tree species was Mn>Zn>Pb>Cd. (Nikolaevich, 2023:30) they addressed the modeling of heavy metal pollution in Central Russia based on satellite images and machine learning. Al, Fe, and Sb contamination were predicted for 3000 and 12100 grid nodes in an area of 500 km2 for the Central Russian region for 2019 and 2020. Estimating the amount of this pollution requires time and high cost. Considering the traffic on the Aleshtar -Khorramabad highway near Kakareza forests and the effect of heavy metal concentration in the soil and leaves of the oak species which can be caused by natural and human pollution, the accumulation of heavy metals in the species Iranian oak is a serious threat to this forest. Therefore, it is necessary to study and discuss pollutants and their effects on the environmental cycle. In this regard, considering the cost and time-consuming nature of traditional methods and since remote sensing methods are a suitable complement to traditional methods; the aim of the present research is to use remote sensing techniques and spectral analyses to evaluate and model the accumulation of heavy metals in Iranian oak species.

The present study is located on the road of Aleshtar -Khorramabad, 20 kilometers northwest of Khorramabad. For this purpose, five transects were created at distances adjacent to the road, 500 and 1000 meters on both sides of the road, and 10 x 10 m sample pieces were planted. Inside the sample plots, 30 soil samples were randomly collected and 30 leaf samples were collected from trees in all directions of the crown. To extract heavy metals from soil samples and plant samples, the acid digestion method was used and the physical characteristics of the soil were measured using standard methods. After preparing the samples, the concentration of Pb, Cu, and zinc heavy metals in soil and leaves was measured and the index of biological concentration of heavy metals from soil to leaves was calculated. Then the relationship between the concentration of heavy elements measured and the reflectance in different bands or band ratios at the corresponding sampling points was obtained. Non-parametric methods and generalized multiple linear regression models were used in order to model quantitative variables and spectral values corresponding to sample parts in satellite data. ArcGIS software was used to implement sample parts on the image, ENVI software was used for image processing, and STATISTICA software was used for modeling.

Cu and Pb in Iranian oak leaves had significant differences at different distances at the 0.05 level, but Cu did not have significant differences at different distances at the 0.05 level. Cu and Pb did not have significant differences in different soil intervals at the 0.05 level, but Cu had significant differences in different soil intervals at the 0.05 level. The bioconcentration factor was obtained as (0.2, 0.5, 0.2) mg/kg. The study of modeling of non-parametric methods using Sentinel-2 satellite data showed that the highest explanatory coefficient values (0.85, 0.88, and 0.97) were obtained for the three metals Cu, Pb, and Cu, respectively. The artificial neural network (ANN) algorithm obtained the highest accuracy. Also, according to the results of the random forest algorithm, for the three mentioned metals, PSRI, HMSSI, and PSRI indices are the most important in modeling.Based on the findings, the concentration values of Cu and zinc were significantly different at different distances, but the Cu values were not significantly different at different distances. In this regard, Mansour concluded in 2014 that there is a significant difference between the concentration of Cu and zinc in the leaves of the species, which can be attributed to traffic density and human activities, and the high amount of zinc metal in this study is the wear of car tires؛ and stated that the concentration of Cu is caused by the production of greenhouse gases and the use of vehicles using Cu gasoline. Based on the findings, the values of Cu and zinc concentrations at different distances did not have significant differences, but the Cu values had significant differences at different distances. Sources of input of Cu element to the soil are urban, industrial, and agricultural waste, fertilizers, and chemicals that add it to the soil through liquid, solid, or mineral fertilizers. These findings are with the results of some researchers including Wu and colleagues (2010:38), Botsou et al. (2016:17) are consistent. Based on the findings obtained from the calculation of the bioconcentration index and their comparison with the classification proposed by Ma et al. (2001:25) for Iranian oak species plants in relation to Cu, zinc, and Cu metals from soil to leaves, it acts as an accumulating plant. In accordance with the results of this research, in the study of Khodakarmi et al. (2009:15), Iranian oak was included in the category of superabsorbent plants in relation to the accumulation of Cu pollutants, which has a high capacity in terms of root absorption. Also, Madejón et al. (2006:25) stated that oak leaves are more resistant than olive leaves. The concentrations of elements in leaves and fruits decrease with time and the risk of toxicity in the food web is reduced. The review and comparison of five algorithms showed that (ANN) the highest explanatory coefficient values (0.85, 0.88, and 0.97) were obtained for three metals, Cu, Zn, and Cu, respectively. Considering the importance of the PSRI synthetic band in increasing the accuracy of modeling with satellite images and the influence of the visible and near-infrared bands, the amount of reflection measured by the spectroscopic method showed that with the increase in the concentration of heavy elements, the amount of reflection in the visible and infrared range decreases (Liu et al., 2011:24).

The results showed that Sentinel-2 images along with artificial intelligence techniques have a relatively good ability to model the level of biological pollution index in the region. In line with the obtained results, it is suggested that the Iranian oak species is used to reduce pollution on highways because it accumulates heavy metals.

Cold and frost are one of the climatic hazards that cause damage to various activities every year. Climate change, on the other hand, causes spatial and temporal changes in glaciation. The purpose of this study is to analyze the temporal-spatial changes and predict the future of glaciers in Hamadan province. CanESM2 model was used to predict the minimum daily temperature in the province. Data mining of general circulation models was Downscaling using LARS-WG model. The above parameters were simulated for a period of 30 years (2050-2021) under three scenarios RCP2.6, RCP4.5 and RCP8.5 for selected stations. The results of the monthly minimum temperature survey in the study stations of the province showed that the minimum temperature in the period (2050-2021) in all studied stations according to all three scenarios will increase in all months of the year compared to the base period. The average minimum temperature of the province is equal to 2.5 degrees Celsius, which in the coming decades based on the scenarios of RCP2.6, RCP4.5 and RCP8.5 will reach 6, 6.2 and 6.3 degrees Celsius, respectively, which is the highest The changes are related to Nojeh station and the lowest is related to Hamedan. The spatial distribution of the beginning and end of freezing in the future period indicates that freezing in the northeastern and northern parts of the province starts earlier and ends later than in other parts of the province, while in the southern parts of the province it starts later and ends earlier. The results of examining the changes in the onset of frost in the next decade compared to the base period showed that in all stations studied the onset of frost will decrease between 3 to 11 days.

Monitoring the changes and fluctuations of precipitation in geographical areas can give a better view of the behavior of this phenomenon in the coming years. The purpose of this research is to investigate the precipitation situation in Ardabil Plain (Ardabil, Bileh-Daragh, and Kolour stations) and forecast it in the coming years based on the output of CMIP6 models by the CMhyd downscaling model. Then, using R2, MAE, MSE, RMSE, and Taylor diagram, the observational data of the base period were compared with the historical data of 5 GCM models from CMIP6, and the best model was selected for each studied station. The output of the top models was corrected for skewness by linear scaling method and based on SSP126, SSP245, and SSP585 scenarios, the precipitation of 2050-2023 for each station, forecast, and its trend were drawn with the Mann-Kendall statistic. The results showed that in the eastern and western areas of Ardabil Plain (leading to the heights of Talesh and Sablan mountains), the rainfall changes were increasing (2.80 mm). In the Ardabil station, the MIROC6 model with a correlation coefficient of 0.94%, and in Bileh-Daragh and Kolour stations, the MPI-ESM1-2-HR model with a correlation coefficient of 0.88% and 0.92%, respectively, have the highest accuracy in simulating the precipitation. Also, the results of the scenarios showed that the precipitation changes in Ardabil station in the future period compared to the base period under the SSP126, SSP245, and SSP585 scenarios will be 0.24, -6.36, and -2%, respectively.

In this research, in order to reveal possible climate changes, the time series of annual average temperature of Urmia synoptic station during the statistical period of 1951-2017 was studied. Box-Jenkins prediction model (integrated auto-regressive and moving average model) was used to find the change model and predict the behavior of the time series. After fitting different models, R2, Akaike information criterion (AIC), regression standard error (SEE) and the Schwartz-Bayesin criterion (BIC) were measured to select the optimal model. The results showed that the time series model ARIMA (2,2) (1,0) has better results compared to other models and the trend of time series changes of this model has less error. After choosing the best model, the average annual temperature values for the next 13 years were predicted using it. The temperature prediction was done using this model with a good fit and the correlation between the actual and fitted values was around 82%. After ensuring the correctness of the forecast, the time series until 2030 was estimated. The forecast of the model indicates a mild temperature increase in the coming years with an upward linear trend. The study of the general circulation of the atmosphere of the region by drawing and analyzing the difference maps for the parameters of geopotential height of 500 hpa, relative rotation of 500 hpa, vertical velocity of the atmosphere (Omega) and air temperature on the surface of the earth indicates the strengthening of the stability of the atmosphere as well as the increase in temperature. The air of Urmia city is 0.4 degrees Celsius compared to the past, which confirms the results of the Box-Jenkins model.

Sinkholes are depressions in the ground which have no natural external surface drainage. They may be occurred in karstic landforms through dissolution process with accompanying of other karstic features (Parise, 2019). Jafari and Mohammadi (2018), stated that understanding geographical condion and causative factors and related processes are vital in sinkhole hazard zonation in Kabudrahang and Famenin plain. North of Alamut at border of Gilan and Mazandaran provinces is one of the areas that dominantly sinkholes have been taken place. More than 200 dissolution based sinkhole have been observed and mapped in this area (Armani and Taromi, 2022). In this study an attempt was made to map sinkholes in this area by understanding environmental condition, role of causative factors, data integration and modeling in a GIS.

The study field is located in North of Razmian, bordrs of Qazvin, Gilan and Mazandaran provinces. The study area is limited to latitudes between 36° 35΄ and 36° 42΄ North, and longitudes between 50° 15΄ and 50° 30΄ East. First, the required geographic data, such as a map indicating areas of hope to have access to shallow karst water, climate zones, mean temperature classes map, surface flow concentration, geology map including lithology and geological lineaments density maps at scale 1:100000 were prepared. Since areas of hope to have access to shallow karst water are potentially vulnerable to collapse of overburden materials over such areas, therefore this spatial data was used as a basis for detail investigation and identification of sinkholes. For doing this, the data layers were integrated by using of decision making critera.Then, cross operation was applied to the data layers called climate zones and zones with same mean temperature. The same operation also was applied to data layers named lineaments density and flow accumulation classes. These operaton led to have two maps and attribute tables. By overlaying the two output maps, a new map having information on possible combinations of all causative factors was produced. At the next step, proper weights (1 to 5) were given to the possible combination forms, based on characteristics and role of causative factors in dissolving carbonate rocks and creation of sinkholes, by using two dimentional tables in a GIS. The map representing potentials for sinkhole occurrence was created by classifying the final weight map. Consequently the generated map representing potentials for occurrence of sinkholes or susceptible areas for sinkhole occurrence was refined and precceised via considering information of areas of hope to have access shallow karst water resources. Accuracy of results then were assessed by cheking spatial overlaps and coincidence of geographic locations of more than 240 observed sinkholes and sinkhole vulnerability map and sink map generated through proccessing of digital elevaton model (DEM). Since results of model for mapping areas of hope to have access to shallow karst water is underestimated due to sensivity to vegetation cover, so a buffer around ground truths are used for accuracy assessment.

There are many sinkholes in the study area. More than 240 of them have been studied during a intensive field work. Most of sinkholes in Northwest of Alamut are Karrens and caves in type and variety, which have been formed through solution processes in bedrocks. About 28 sinkholes have been reported by Soldo et al., 2020, in Feiz_Abad plain, Abarkuh, that are taken place by means of the same processe. Although solution process in soluble materials like carbonate rocks is a main factor for generating such geomorphological features at highlands, but lowering groundwater level in plains plays a main role for land subsidene and also collapsing Earth materials ending to sinkholes. There are some methods like radar interferometery and direct field measurments that have been developed for recognition and characterizing occurred land subsidence and sinkholes, while there is no well known method for identifying and mappig points that are potentially vulnerable to sinkhole incidence. The method which has been developed for mapping areas of hope to have access to shallow karst water, in Azarshahr, by Jalali et, al 2009 and the same method applied by Armani et al., 2022, to North of Qazwin province, might be the most proper method and basis for seeking areas potentially vulnerable to sinkhole hazard. Therefore the areas of hope to have access to shallow kaerst water, provided by Armani et al., for this study area, were searched for allocating areas that are vulnerable for sinkhole occurrences, by applying above_mentioned methodology. as a result of application of this method, spatial distribution of potentials areas that are vulnerable to sinkhole occurrence were identified.The model used by Jalali et al., (2009) al. and Armani and Jalali, (2022) for mapping areas of hope to have access to shallow karst water excludes dense vegetation covers, so the final result becomes underestimated. Since the study area relatively have good vegetation cover, therefore the area and number of identified sinkholes were identified less than they are. In the other words if vegetation cover was not a limiting factor in the model, high regression would be expected between observed sinkholes and output of the model. Anyhow more than 66% of susceptible areas to sinkhole occurrence are coincide with areas less than 200 meter DEM-derived sinks buffers and about 40% of those susceptible areas are fallen in buffers less than 200 meter to observed sinkholes.

Preparing sinkhole hazard map by making use of remotely snsensed data and relational modeling in Alamut area is bearable and cost effective from time and cost points of vies. Therefore one may provide sinkhole hazard and their spatial distribution maps by indirect mapping procedure. Since sinkhole are generally being formed in soluble materials, like carbonate rocks, so some susceptible parts of this rocks that have been marked as areas of hope to have access to shallow karst water, could be selected as a reliable bassis for further spatial data achievement about sinkholes and their characteristics.

Increasing population and urban development, increasing use of cars, increasing the number of private cars, Also the narrow width of the streets and the lack of supply of marginal park space, especially in the central parts, have caused many problems for large and densely populated cities. Parking lots as one of the most important urban infrastructures play a major role in reducing these problems. Today, in large cities, with the correct location of public parking lots, optimally manage of urban traffic is possible by increasing the provision of services to a large number of vehicles. 

In this research, first, effective criteria were extracted according to the opinion of Babol Municipality experts. The information layers of each criterion were prepared in the GIS environment and to equalize the layers, each criterion was classified, Then, the identified criteria were weighted using ANP technique and with the help of Super Decision software, and then pairwise comparisons were done. Weighted layers were combined by ANP method, were placed on top of each other in the GIS environment based on the influence of each layer (relative weight) and the map of the optimal areas for the construction of public parking lots was obtained. 

In this research, the inconsistency coefficient obtained was 0.07. Criteria prioritization showed that, "Distance from the road", "Distance from offices use" and "Distance from business use" criteria with a significance coefficient of 0.25, 0.24 and 0.15 respectively had the highest weights. Arc GIS software was used to prepare the final maps. Finally, suitable places for creating public parking lots were determined by applying the final weight of the criteria and overlapping the layers. According to the final location map, areas with very high potential, areas with high capability and areas with medium capability each have 3.11, 55.75 and 36.56 percent of urban lands, respectively. Areas with very high and high potential are mostly located in the northwestern, northeastern, southwestern and central parts of the city.            

The results indicate that the spatial distribution of existing parking lots in the city is not related to the effective criteria in these parking lots. According to the residential use map and population density and due to the epidemic of private car use, there is no match between the number of parking spaces in the city and their spatial distribution and population density. The result of urban parking location zoning using the ANP model and comparing it with existing parking lots in the city shows that The class of areas with high capacity for parking lots is located in parts of the city where there are no parking areas and there is an urgent need to create these types of users. This factor indicates that the location of existing parking lots in Babol city has been done without considering effective factors and criteria. All parking lots are located in one part of the city and at a close distance from each other. There is a need to create many public parking lots in other parts of the city, according to the urban population, until the per capita is closer to the reality. Considering the population of Babol city, which is 250,217 people, and the number of public parking lots, which is 6, this amount per capita is very low.

The main aim of this research was to model the drivers of air pollution in Tehran using the Interpretive-Structural Modeling approach. For this, drivers causing air pollution in Tehran were determined by referring to experts' opinions and using the interpretative structural approach. Then, the influence and dependence of the drivers were assessed using the MICMAC Model. According to the results, the general policies of the government at seventh level located at the lowest level, followed by government interventions on the sixth level, the officials supporting the environment and research and development on the fifth level, innovations in urban management on the fourth level, monitoring the production of pollutants and population growth in the third level, reforming the consumption pattern on the second level, and finally, the number of vehicles, energy price, quality of industries, and clean energy investment were placed at the one level. This research used a structural-interpretive approach, a soft research method in operations, to understand and structure the problem and answer the research question. Furthermore, influential and dependent driving forces were identified so that any change in influential driving forces would lead to changes in dependent driving forces, and the tangible effects of changes on dependent driving forces would be demonstrated. These drivers were used to solve the air pollution problem and pave the way to reaching favorable air quality conditions in Tehran.

The physical development of cities is increasing day by day. Correct management of this development from various aspects is among the important issues that must be considered. There are many methods for predicting and determining the direction of urban development, one of these methods for determining suitable areas is the method based on neural networks.

The purpose of this research is to model the development of the city of Rasht in the last 20 years and predict the directions of development of this city until 2032.

By using ETM+ Landsat 7 and 8 satellite images of 2002, 2012 and 2021 of Rasht city and with GIS software, images with suitable band composition are prepared and then the images are classified using Multi Layer Perceptron(MLP) Artificial Neural Network  method. The indicators considered for the neighborhood model of urban areas are the distance from urban points, the distance to the central areas of the city, and the distance to the main streets and roads.

Studied Areas: 

Rasht city, the capital of Gilan province, is located at 49 degrees 35 minutes 45 seconds east longitude and 37 degrees 16 minutes 30 seconds north latitude from the Greenwich meridian, and its area is about 10,240 hectares.

Results:

 In this model, in the training mode of the first stage (input, applying 4 indexes on the images of 2002), the network performed 104 iterations, and the lowest error rate, which is evaluated by the crossentropy criterion, was equal to 0.058526 in the 98th iteration. In the second step, the input of the model was to apply 4 indicators on the images of 2012, and the lowest error rate was evaluated as 0.076657.

In total, the model has been able to predict the development of Rasht city in 2012, 95.9% and for 2021, 93.8%, which can be acceptable. The model error in this first part was 1.4% and in the second part was 2.6%. By examining the 20-year period of physical development, the development directions of Rasht city in 2032 were predicted.

Projection of summer monsoon rains in Southeast Iran based on Ensemble model the precipitation factor has a variable and random nature and has a different behavior in terms of space and time. Therefore, the prediction of precipitation has more uncertainty compared to other meteorological variables. In the current study, the data output of Cordex database and CMIP5 models were used using the neural network method to reduce the uncertainty and estimate precipitation properly. The results showed that due to the high correlation of temperature, humidity and air pressure with precipitation, the use of these variables is beneficial in reducing the uncertainty of precipitation forecast. In addition, the non-linear method of artificial neural networks can be used to bias the rainfall data of Cordex database and CMIP5 to forecast the rainfall in the southeast of the country. Another result of this research is the increasing trend of rainfall in the southeast of Iran, especially in the coastal areas. This can be considered as a result of the increase in the level under the influence of rains affected or simultaneous with the southwest monsoon of India. The increasing trend of precipitation in the southern coasts is also related to the increase in the storage capacity of moisture content. The interannual variability of India's monsoon rainfall also shows a steady positive trend under continued global warming. Since both the increase in the duration of monsoon rains and the increase in interannual variability in the future are seen in most models, we can be confident in these predicted trends. Indian summer monsoon rainfall is also predicted to be higher under global warming in the 2050s compared to the baseline.

Cancer is one of the most common causes of death worldwide. Always the role of natural and geographical factors in the manner and manner of distribution and its effects on disease centers and the role of natural processes in fundamental changes and humans as well as human-related diseases, even in places where these effects are clearly evident in the death or destruction of habitats and humans themselves; It has a pale appearance.

This research is based on field studies in terms of the nature of the applied goal and in terms of the descriptive-analytical research method. The statistical population of this research includes all patients with gastrointestinal cancer who were diagnosed between 2014-2017 and were registered in the Sima Cancer System (Electronic Management Integration System) and were permanently residing in Lorestan province. In order to achieve the objectives of the research, indicators related to the role of geographical factors in the spread of digestive tract cancer were extracted (average annual rainfall, vegetation cover, average annual temperature, average sunny hours, and climatic zones).In order to investigate the role of geographic factors in the classification and distribution of these indicators, one-sample t-tests, Pearson's correlation, and Friedman's test were used. In the following, ArcGIS software was used to explain the model through geographic weighted regression of use and the level and status of these effects.

 The results showed that the most important factor influencing the variable of cancer distribution was the vegetation component with a coefficient of 0.91%, which explains the influence situation well. Also, the results of the effect of geographical factors were such that Khorramabad and Borujerd cities had the highest effect, Kouhdasht, Delfan, Aliguderz, and Durood cities had a moderate effect, and Selah, Poldekhtar, and Azna cities had the least effect from geographical factors.

Soil erosion is the process by which soil particles and components are separated from their main bed by an erosive agent and transported to another location. In the soil erosion process, there are three distinct phases: 1- separation of soil particles, 2- particle transfer and 3- sedimentation of transported materials. In water erosion, the erosive factors are rainfall and runoff. Erosion and the consequent reduction of soil fertility are among the issues that make it difficult to achieve sustainable agricultural development and environmental protection. It is important to study the quantity and quality of erosion in the country's watersheds and to prevent the loss of one of the richest and most valuable natural resources of the country, namely soil, and to fight against this process. (Tabatabai, 1392). Therefore, to calculate the rate of erosion and sediment production in most watersheds of the country that lack statistics or lack of statistics, the use of experimental models to estimate erosion and sediment is required. According to what has been said, the present study was conducted based on the following two main objectives 1- Estimation of erosion and sediment in Adineh Masjed watershed, which is one of the main sub-basins of Kamal Saleh Dam, using EPM and MPSIAC experimental models and 2- Investigation and comparing two models and choosing a better model for similar regions and climates.

Adineh Masjid watershed is one of the sub-basins of Dez and the main sub-basin of Kamal Saleh dam. Temperature, isotherm, geology of the area, slope and available information were performed and finally, by interpreting the photos, types, land units, current land use were determined and updated with field control. For a more detailed study, first, according to the condition of the main waterway and changes in the appearance of the land and vegetation and new land material, the ridges separating the basin were divided into 15 sub-basins. In EPM model, four watershed erosion coefficient (Ψ), land use coefficient (Xa), rock and soil susceptibility coefficient to erosion (Y) and average basin slope (I) and in MPSIAC model, nine geological, soil, climate factor (Climate), runoff, slope, vegetation, land use, current erosion status and waterway erosion are examined. Each model was scored according to data analysis and digital images and then placed in the relevant formula. Finally, the amount of erosion and sediment in the basin was estimated and the sedimentation class of the area was determined.

To determine the score of nine factors affecting soil erosion using MPSIAC method and the four factors of EPM model, each of the factors affecting erosion in units were analyzed. Finally, by weighting, the points of each factor in the models were calculated. The degree of R deposition from the sum of the nine factors of MPSIAC model and the degree of Z erosion was obtained by combining the four EPM factors. Then, the amount of sediment production and erosion in the field of relationships related to each model was calculated and compared and analyzed. In MPSIAC model, the amount of specific sediment (M3 / Km2 / year) was calculated as 112.713 and the specific erosion (M3 / Km2 / year) was calculated as 375.71. In the EPM model, the amount of specific sediment (M3 / Km2 / year) was calculated as 213.95 and Specific erosion (M3 / Km2 / year) was calculated to be 395.86.

The results of sediment and erosion estimation were estimated separately for each sub-area using two models and it was found that the two models are somewhat relatively compatible with each other. The results of MPSIAC model, have more accuracy and reliability, and therefore the results of the MPSIAC model can be used to estimate the amount of sediment entering the Kamal Saleh Dam. However, due to the small distance between the results of the two models, if we do not have access to MPSIAC model data in similar areas, the EPM model can be used with less data and more easily accessible. It was also observed that in the upper and entrance parts of the basin, where the slope is higher and the vegetation is less, the amount of sediment production and erosion is higher in these areas. So that the upper parts of the basin are in the medium erosion class and the rest of the basin is in the low erosion class.

In Iran, Hadi plan is the most comprehensive, local and most practical rural development plan that It is increasingly running throughout the country. Evaluate the effects and identify the functional damage of these plans It can provide a cognitive and scientific basis for the implementation problems of these projects, Optimization of financial-executive costs of responsible institutions and as a result It will accelerate the process of achieving the development of the country's villages. Nevertheless, studies show Despite the widespread implementation of these projects in rural areas of the country and Spend large financial costs in this area, a coherent study of the functional impairments of these designs has not been performed. Therefore, Is the main purpose of the present quantitative and applied research Evaluate the effects and identify the functional damage of the conductor design that It has been done on a case-by-case basis in the villages of Kermanshah province. The statistical population includes 856 rural points that A Hadi plan has been implemented in them and Using Sample Power Software as a statistical sample, 244 villages were estimated. The main research tool for collecting field data, was a researcher-made questionnaire that Has reached final approval Its validity by referring to university professors and relevant experts and Its reliability by pre-testing and calculating Cronbach's alpha coefficient. To analyse the collected data SPSS and Amos software are used. Wilcoxon test results showed The average rank for the stage before and after the implementation of the project was respectively 19.77 and 125.77 and The implementation of the pilot project has been effective on rural development. The results showed heuristic factor analysis Laws restricting service departments and natural resource acquisition agreements, Weak content and implementation basis of the project, Weakness of the participatory system, Poor location and physical development, Socio-economic instability, Undermining the identity and landscape of the village, Impracticability and Environmental-physical instability, Are respectively the most important damage to the conductor design which together explain about 64% of the variance of the dependent variable. The final model designed, with a good fit, Confirmed the research results.