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Simulation and continuous review of dynamic processes and urban growth patterns with regard to past development and its prediction in the future, for planners and proponents of natural resource conservation in setting sustainable development strategies, achieving sustainable urban development as well as better decision making It is vital to guide future development. In this regard, the city of Karaj with the approach of being the center of the province as being industrial and migrating has had an impact on all the internal structure of the surrounding cities and villages. As a result, the use of hybrid modeling with a deeper and local perspective for codified planning for the sustainable development of the city of Karaj is inevitable. The aim of this study was to model the growth patterns of Karaj city using heuristic statistical preprocessing (ER), ordinary least squares regression (OLS) and spatial weighted regression model (GWR) and also to predict its development using the model. CA-Markov considering the 20-year period 2002-2021.

Methods and Material: 

For this purpose, first, effective criteria in this process were collected, analyzed and prepared from relevant organizations, and land use maps were extracted from Landsat satellite images. In the next step, the maps were validated and changes were detected. The results of change detection show that the largest increase in area occurred in the built-up areas (2893 hectares) and the largest decrease in area occurred in barren lands (808 hectares). Based on these changes and to avoid the trial and error method in selecting the best combination of input criteria to the GWR model, pre-processing was performed on the criteria using the ER and OLS methods. In the next step, considering the output of ER and OLS methods, 8 independent variables were selected as inputs to the models. Then, modeling of urban growth patterns was performed using the GWR model.

results showed that out of 8 variables, two variables had the same direction of impact (negative or positive) in the studied space and the other variables change their impact in the whole region. Finally, using the CA-Markov model, the land use map for 2041 was predicted. The final results showed that the CA-Markov model predicts that the highest rate of development will occur in 2041 in the eastern and northeastern parts of Karaj.

The performance of broiler chickens is directly influenced by temperature changes and the occurrence of heat stress, whether it is cold or hot. The present study aims to assess the cooling and heating degree days in different stages of broiler chicken production in Khorasan Razavi province. To achieve this objective, daily average temperature data were collected from 13 synoptic stations during the statistical period of 1988-2018. Cooling and heating degree days were calculated for each week of production using specific thresholds, and their spatial distribution was analyzed. Furthermore, the relationship between cooling and heating degree days and geographical features was evaluated. The findings indicate a decrease in cooling degree days and an increase in heating degree days as latitude increases. The northern and western regions of the province exhibited a greater need for heating throughout all stages of broiler chicken production, whereas the eastern and southern regions had higher cooling requirements at different production stages. Overall, the northeastern, southern, and western marginal areas of the province, including Khaf, Gonabad, Kashmar, Sarakhs, and Sabzevar, exhibited the lowest cooling and heating needs during the 6-week period of broiler chicken production, making them suitable climates for this economic activity.

Visiting Mazandaran province could be a fascinating and memorable trip due to its amazing natural touristic attractions such as Caspian Sea and mount Damavand. The three main roads naming Kandovan, Haraz and Firoozkooh can be used to access Mazandaran province. Among them, passing through Kandovan road is fascinating with its beautiful natural landscapes. At the same time, this road is also known as one of the most dangerous roads of Iran due to its mountainous location and the potential occurrence of different types of climatic and geomorphologic hazards. Apart from these dangers, the occurrence of accidents in Kandovan road is one of the main concerns of tourists visiting west parts of Mazandaran province and also the local governments providing relief and rescue services and facilities to injured people. Therefore, it is crucial to identifying the dangerous sections of this road in order to minimize fatalities and socio-economic losses. The purpose of this research is to investigate the spatio-temporal density pattern of road accidents and also to identify accidents clusters along Kandovan road. 

To this end, we used road accidents information along Kandovan road, collected by the relief and rescue bases of Red Crescent organization of Mazandaran province in the period of 2016 to 2022. Information like location, date, and the number of death and injuries in the road accidents along this road were used in this research. First, we used GIS, spatial and statistical analyses in order to get insight from road accidents distribution and statistics. In the next step, Kernel Density Estimation – a Geostatitical measure – was used to investigate the general spatial density pattern of road accidents in the period of 2016-2022 and also the spatio-temporal density pattern of road accidents in every year from 2016 to 2022. Furthermore, the hot spot analysis was implemented to the distribution of road accidents in this period in order to find out whether accidents are clustered, dispersed or randomly distributed. Both general spatial pattern and annual spatio-temporal patterns of accidents were investigated using hot spot analysis. With this, accidents clusters reflected as hot spots were identified based on the Getis-Ord Gi*index and the associated Z-score, P-value and Gi-bin statistics. In this context, the number of accident clusters, the length of road in the accident clusters and the percentage of observed accidents in the clusters were computed from 2016 to 2022.  

Results show that 2084 accidents were occurred in the period of 2016-2022 with 9076 injuries and 52 deaths. The most number of accidents was occurred in 2022 following the end of Corona lockdown in 2021. Also, several parts of Kandovan road indicated to contain the highest number of accidents density. Besides, the accident density pattern changes spatially and temporarily with an increasing trend in the number of accidents density from the end year of Corona disease epidemic in 2020. Results from hot spot analysis also identified several accidents clusters along this road in the period of 2016-2022. In this context, road accidents clusters were identified in Zangouleh Bridge, Majlar, Siah bisheh, Knadovan tunnel and Ushen Bridge with average Z-score value of 3.12, average P-value smaller than 0.05 and confidence interval of 90 to 99%. The total length of road in these clusters was more than 14 kilometer which contains around 60 % of the total accidents. The spatio-temporal distribution pattern of accidents clusters and also road lengths in the identified clusters change decreasingly in the period of 2016-2022. The results of this research can be used to investigate the reasons behind the occurrence of road accidents in the high accidents density sections and also in accidents clusters identified along the road. Taking proper preparation and mitigation strategies can be beneficial in proper crisis management of road accidents in order to avoid human causalities and socio-economic losses.

We conclude that kernel density estimation and hot spot analysis are effective geostatistical approaches to investigate the density pattern of road accidents and also to identify accidents clusters. In order to increase the safety of Kandovan road, the factors contributing to accidents occurrence in highly dense accidents sections of road and also in accidents clusters need to be identified, and with implementing proper measures, their effects can be minimized.

This research was conducted to simulate flood flow in the Shahrchai River in Urmia County, Iran. The Shahrchai River, which passes through the city of Urmia, experiences a flooding state during the spring season, causing damage to buildings and agricultural lands in its vicinity.

 The hydraulic model HEC-RAS was used to generate floodplain maps for three sections located downstream of the Shahrchai Dam. Floodplain maps were prepared for return periods of 2, 5, 10, 25, 50, and 100 years based on different flow rates from two hydrometric stations. Satellite imagery from the Landsat 8 OLI sensor was utilized to create land use maps, which were classified using supervised classification in ENVI software.

The results showed that due to the presence of the Shahrchai Dam, the inflow of water to the river channel had a regulated state, resulting in a lower probability of flooding in the 2- and 5-year return period floods. However, in return periods of 25 years and above, due to the increase in river discharge, the lands along the river and the floodplain are flooded.

The final maps revealed that in the first interval, agricultural lands and orchards suffered the most damage during return periods of 25 years and above. In the second interval, residential areas and urban facilities are at risk of flooding during return periods of 25 years and above. In the third interval, agricultural lands are most susceptible to flooding. 

Few studies have been conducted to investigate the hydrological behavior of the Shahrchai River in Urmia, especially the urban area, using the HEC-RAS model. Therefore, in this research, the HEC-RAS model was employed to simulate flood hazards along this river, and the obtained results significantly contribute to managing this risk.

One of the most important effective factors in better efficiency in providing timely and reliable firefighting services in cities is the issue of locating stations to reduce the time to reach the scene of the accident. In this research, first, the layering of the road network of Ardabil city was downloaded from the OSM database, and the topology of the layer was created using topology rules in the ArcGIS software environment. Then, to identify urban cores deprived of fire services in Ardabil city, network analysis in the context of geographic information system has been used in terms of distance and also driving time. The service area of each of the stations was determined by analyzing the service area, and for this purpose, the distance of two kilometers from Manhattan and the time of three minutes to reach the accident site were used. To perform the analysis, the information fields of the maximum speed of vehicles on roads, the length of roads, the time taken by vehicles to travel the road, and the operating speed in the road network layer of Ardabil city have been used. The result also shows that 79% of the city is within the service range of fire stations, and areas such as Azadi and Azadeghan in the center of the city, Kalkhoran and Seyedabad neighborhoods in the north of the city, Niyar in the east, and the newly built settlements in the south of the city lack service coverage. In order to provide more coverage and increase safety in areas outside the service area, three new locations have been proposed for the construction of fire stations.

The Quetta sub-basin is a part of the Pishin River basin, situated in the southwestern region of Pakistan. This study aimed to determine the spatial distribution of annual soil erosion through the utilization of the Revised Universal Soil Loss Equation (RUSLE) model. To accomplish this, numerous data mining techniques were employed, along with machine learning algorithms, to produce thematic layers (K, R, LS, C, and P) that served as input parameters for the RUSLE model. According to the resultant model, soil erosion in the study area ranged from 0.00 to 866 tons per hectare per year. The estimated values for rainfall-runoff erosivity (R), soil. erodibility (K), topography (LS), and cover management (C), factors ranged from 147 to 191 (MJ.mm.ha⁻¹.h⁻¹year⁻¹), 0.0229 to 0.0259 (t.ha.MJ⁻¹mm⁻¹), 0.002 to 360.77, and 0.001 to 1, respectively. The statistics revealed that 58% of the land in the study area experiences a very low degree of soil erosion, at an erosion rate less than 13.58 t/ha/year. About 24% of the study area faces low erosion, with an erosion rate spanning from 13.58-44.16 t/ha/year. 13% of the area is demarcated as moderate soil erosion severity, at an erosion rate ranging from 44.16-81.53.14 t/ha/year. On the other hand, 5% of the study area experienced high to very high soil erosion, with an erosion rate of 81.53-866.34 t/ha/year.

Land use planning encompasses the rational organization of economic, social, cultural, and environmental development aspects. Spatial organization of settlement systems within the framework of land use planning is closely related to the spatial-physical patterns of rural settlements. Achieving a balanced development in rural areas depends on finding suitable spatial patterns in settlement systems generally and rural settlements specifically. Analyzing rural settlements in terms of economic, social, and environmental aspects without considering ecological, spatial, and vulnerability approaches is ineffective. Rural settlements face challenges such as poverty, income inequality, rural migration, village abandonment, neglect of spatial-physical management, and high vulnerability. Factors such as altitude, slope, geological structure, faults, water resources, soil, vegetation, and land use serve as natural bases that significantly influence the identification of suitable and unsuitable areas for rural settlement risk assessment.This applied-developmental study employs library and survey methods to evaluate the ecological and environmental capabilities of the Aq Su region in Kalaleh County for organizing settlement systems. To measure the impact of vulnerability factors on the spatial distribution of rural settlements, multiple regression analysis was utilized. Subsequently, spatial database preparation in a GIS environment (ArcGIS) was performed. After standardizing the criteria using fuzzy logic and AHP methods, weights were assigned to each criterion in the software environment. By integrating these criteria based on the AHP model and fuzzy logic, a final map indicating suitable and unsuitable areas was generated. The study area in the resulting map was classified into highly suitable, suitable, and unsuitable categories for planning various settlement activities.

Landslide is one of the most important dangerous geomorphological processes of a range, it plays a significant role in the evolution of ranges, Sa'in pass, in the Ardabil-Sarab communication axis, has been affected by landslides for a long time due to its special geological, climatic, geomorphological features and human activities. In line with the zoning of landslides Sa'in Pass in the Nair-Sarab communication axis, nine important variables affecting the occurrence of landslides were used, including: height, slope, slope direction, geological formations, distance from the fault, rainfall and distance from the waterway, land use and distance from the communication road. The weighting of the investigated factors was done using the ANP method and in the Super Decision software environment. Finally, the thematic layers affecting the landslide event according to their weight or coefficient (resulting from the ANP model) in the ArcGIS software environment using the weighted combination method, were combined with each other and the final map of landslide hazard zoning was obtained in the Nair-Sarab communication axis. . According to the obtained results, the factors of slope, height, lithology and distance from the fault had the highest weight coefficients with values of 0.209, 0.139, 0.132 and 0.124, respectively. The result of this study indicates the high risk of the studied area in terms of landslide occurrence. High-risk areas are mainly located in 10-40% slope, in areas with 300-450 mm rainfall and in close distances from communication road, river and fault. Also, very resistant, non-resistant and semi-resistant formations and agricultural and pasture uses, slopes with north, west and northwest directions, are more sensitive to the occurrence of landslid.

The present study is a model for locating and resettling the families of prisoners before and after imprisonment; It has dealt with the prisoners of the Ghezel Hesar complex and the Karaj penitentiary, in order to examine and assess the level of compliance of the families of the prisoners present in these prisons in relation to the area around the prison.

This research, which is applied in terms of purpose and survey in terms of method, a researcher-made questionnaire was used to collect data. The statistical population includes prisoners in Ghezel hesar prisons, including Ghezel hesar penitentiary and Karaj central penitentiary. Among them, prisoners whose families lived in Alborz province were selected as a statistical sample. For data analysis, Wilcoxon test in SPSS software and spatial analysis commands in GIS software were used.

The output of Wilcoxon test showed that out of 259 families surveyed, 202 families of prisoners were accommodated in the pre-prison and post-prison period and only in 4 cases we saw a change of residence.

In general, the results show that there is no evidence of the impact of the residential environment around the prison on the location of Ghezel Hesar prisons.

Earthquake is one of the inevitable natural disasters that, if it occurs, causes countless damages and problems for the economy, environment and human life. Therefore, earthquake crisis management is essential. Experience has shown that preventing the occurrence of a crisis is better than organizing it after it occurs. Therefore, the phases before the crisis in the crisis management cycle are of particular importance.Iran's strategic geographical location positions it susceptible to substantial seismic activity, establishing its standing as one of the most earthquake-prone nations globally. The convergence of the Alborz and Zagros mountain ranges has increased this susceptibility, notably due to the interaction of the Saudi plate with the Zagros range, thereby causing seismic hazards for various urban centers located in close proximity to fault lines and mountainous regions. Identifying areas prone to these environmental hazards is fundamental as a primary measure in implementing effective risk mitigation strategies, urban planning initiatives, and construction endeavors. Therefore, the present investigation was conducted to evaluate and map the seismic vulnerability of Hormozgan province, with the objective of pinpointing and categorizing high-risk zones within the province.

Hormozgan Province is situated in the southern region of Iran, positioned to the north of the Strait of Hormuz. Geospatially, the province spans from approximately 25 degrees and 25 minutes to 27 degrees and 18 minutes north latitude, and 52 degrees and 39 minutes to 59 degrees and 14 minutes east longitude from the Prime Meridian. With a land area of around 71,193 square kilometers, Hormozgan Province encompasses about 3.4% of Iran's total land area and comprises 13 cities, 39 districts, 88 villages, and 50 townships.This study utilized ArcMap software to analyze earthquake data from the past 20 years. They created maps for factors like earthquake magnitude, depth, and proximity to faults. Additionally, density maps for both faults and historical earthquake epicenters were generated. After processing the data and assigning weights using expert opinions through Fuzzy AHP, the software combined these layers to produce a final map that zones earthquake hazard levels across the region.As aforementioned, the research methodology employed in this study involved the integration of fuzzy logic models and hierarchical analysis within a Geographic Information System (GIS) framework to assess the seismic vulnerability of Hormozgan province to earthquake risks.The Fuzzy Hierarchy Analysis Method (FAHP) incorporates fuzzy logic concepts into hierarchical frameworks to accommodate subjectivity in complex decision-making. Through the hierarchical arrangement of decision-making criteria and the use of fuzzy sets with logical operations, this method enables visualization of ambiguous and inaccurate data and provides a versatile and user-friendly strategy for decision analysis and problem solving.To assess seismic risk levels across the province, this study considered key earthquake vulnerability indicators: slope, elevation, proximity and density of fault lines, earthquake depth and magnitude, distance from epicenters, and density of seismic points. By integrating these factors, we were able to create a robust assessment that identified areas with varying degrees of earthquake vulnerability.

Our analysis revealed that a significant portion (around 22%) of Hormozgan province, encompassing 15,807.64 square kilometers, faces very high earthquake risk. Additionally, 8,133.15 square kilometers (11.50%) were identified as areas with very low seismic risk. By combining fuzzy logic models and hierarchical analysis, this study effectively identified specific zones within the province that require targeted earthquake preparedness and mitigation measures. These findings demonstrated the nuanced distribution of seismic risk levels across Hormozgan province, highlighting the need for tailored interventions to improve disaster resilience.This research highlights the importance of proactive earthquake risk assessment and zoning. By identifying areas with varying levels of seismic risk, this approach provides a crucial foundation for strategic decision-making. This allows for targeted risk management strategies and informed urban development planning in earthquake-prone regions like Hormozgan province, ultimately safeguarding communities and infrastructure from the potential impacts of seismic events.

Ultimately, the primary objective of this study is to evaluate and zone earthquake hazard levels in Hormozgan province using a hybrid Fuzzy AHP model. The application of Fuzzy AHP facilitates the analysis of various spatial parameters based on theirimportance weights to generate a vulnerability map. This approach proved instrumental in effectively assessing and zoning the vulnerability of Hormozgan province to seismic hazards.By leveraging integrated methodologies, we were able to comprehensively assess seismic risk and identify areas requiring targeted interventions. These insights provide valuable resources for policymakers, urban planners, and disastermanagementstakeholders, which emphasize the importance of informed decision-making to bolster earthquake resilience in vulnerable regions.Moving forward, this research lays the foundation for informed strategies to enhance disaster preparedness and mitigate the impact of seismic events in Hormozgan province and similar earthquake-prone areas.

The consequences of climate change are increasingly threatening cities and villages in various ways. Due to their location at the intersection of land and sea and the presence of significant human and economic resources, the coastal cities face greater threats from such hazards, especially floods. The existence of deteriorated fabrics also increases this vulnerability. This research aimed to evaluate and analyze the physical resilience of the deteriorated urban fabrics in the coastal city of Dayyer against urban floods using a descriptive-analytical approach. For data analysis, the AHP analytical model was used to weigh the criteria and assess their importance, the SAW fuzzy method was employed to evaluate the final physical resilience, and GIS software was utilized for map plotting. According to the results, among the examined criteria, "elevation above sea level" and "distance from the shoreline and waterways" are the most important ones, with weights of 0.271 and 0.227, respectively. Additionally, based on the findings of this research, the deteriorated fabrics in the coastal city of Dayyer has different levels of physical resilience. The areas in the "Bāzār," "Kheniyā," and "Arabs" neighborhoods have the lowest physical resilience, while the "Bāgh" neighborhood, due to its distance from the sea, higher elevation above sea level, and newer buildings, has shown greater physical resilience. Ultimately, based on the results, recommendations for improving the physical resilience of the deteriorated fabrics of the coastal city of Dayyer include, preventing urban expansion in low-lying and coastal areas and accelerating the renovation and reconstruction of these areas.

Considering that there are different forms of mass movements in the ChamGardlan watershed, especially along communication routes, agricultural and residential areas, it is necessary to create refugee maps Therefore, it is impossible to examine the factors influencing its situation in order to prevent and control this phenomenon. Therefore, during the field visits, geographical, physiography, land use, vegetation cover, soil, climatology, geography and geomorphology maps were produced in the GIS environment. The method of this research has been accomplished base of distinction of the geomorphological units while using aerial photos and crossing  basis maps. Then, the effective factors on the occuration of mass movements were studied using logistic regression equations. So that, the factors such as slope, geological formation type, pedologic, climatic, etc. were taked into consideration as independant variables, and mass movements occurance frequency as function of mentioned factors.The result indicated that the effective factors related to frequency of land sliding happening in the area in arrangement, are slope, geological formation type and mass  movements  type (both kind and amount of salts in soil) and also landuse.

Landslides are one of the natural phenomena that cause a lot of financial and human losses in the country every year. Therefore, identifying landslide-prone areas to use methods to prevent or deal with slope instability is very important to reduce their hazard and risk. Landslides have always been a serious threat to human habitation. The aim of this study is to use the fuzzy hierarchical process method for landslide risk zoning in Savadkuh through information layers and factors affecting landslides. In the present study, using the landslide points taken from the city, landslide zones were identified in the region. Factors such as altitude, slope, aspect, geology, soil layer, land-use, distance from the fault, and distance from the road and the river were studied as influential variables in landslides. In order to prepare the layers and classify each of them for each variable, the method of combining the landslide layer and the desired variable was used, and in fact, the same method was used to determine the fuzzy membership using the frequency ratio model. After calculating the frequency ratio and fuzzy membership of the classes, the fuzzy set operators, including addition, multiplication, and gamma of 0.7, 0.8 and 0.9, were used as methods to overlap the classified variables with the fuzzy membership values to Landslide zoning maps should be prepared in the study area. In order to select the optimal method from fuzzy overlap operators, two methods of quality summation (Qs) and precision method (P) were used to determine which operator or fuzzy method has better accuracy for landslide risk zoning in Savadkuh. The value of the quality summation index, which shows the comparison and evaluation of methods in comparison with each other, indicates that the 0.8 gamma fuzzy operator has the highest value of Qs among other fuzzy operators

Fuel stations are always considered as one of the most sensitive and effective urban uses. Therefore, the placement of this use among other uses in the city is of great importance and the incorrect placement of this use can cause disruptions in the access to environmental health and neighboring uses in addition to having a negative impact on the urban environment. As a result, the correct location of fuel stations in the city can bring acceptable results in the mentioned fields. In this research, the fuel stations of Semnan city have been studied and investigated by field sampling method and using GIS software. The purpose of this research is to identify the problems of the neighborhood of fuel stations and discuss the accessibility of these stations in the city of Semnan and to present the existing solutions in order to improve these problems. The results of the field investigations show that 20% of the stations in Semnan city are not in a good condition in terms of indicators such as standards, equipment safety, and most importantly, proximity to other uses. By comparing the rules and standards with the map of the current status of fuel stations in the city, it was found that a number of stations are not located in suitable areas for establishment.

The purpose of the current research was to investigate and compare the performance of environmental health based on Elmeri index and Geographical Information System (GIS) in the large-scale open spaces of the Tehran Revolution Sports Complex.

The present study was descriptive, cross-sectional, quantitative and qualitative, which was conducted in order to evaluate environmental health performance using the ELMERI questionnaire method and Geographical Information System (GIS) in Tehran's Engleab sports complex. In Elmeri's method, two components of environmental health, including: cleanliness, order, order and industrial hygiene, were examined and evaluated by HSE experts and researchers in the mentioned spaces. In order to analyze the data collected through GPS device and land use maps of Tehran, GIS 10 tool was used.

In the northern areas of the Revolution sports complex, the concentration of PM10, No. 2 pollutants was higher than other areas. The distribution of air pollution with O3 pollutant was more in the eastern part of the Revolution complex than in other stations, and it was the lowest in the west of the stadium where the golf and tennis courts are located. In Al-Mari's method, the component of cleanliness, order and order of tennis courts was in a good condition with a total index of 83.5% and in the component of industrial hygiene with a total index of 78.8%. In the component of cleanliness, order and order of golf courses, the total index was 82.5%, and in the component of industrial hygiene, the total index of golf courses was 77.6% and it was in good condition.

The health level and air pollution index of the large-scale spaces of the Revolution Complex, including tennis and golf courts, were found to be suitable for personnel and people who do sports in these spaces.

Soil erosion is one of the important issues in the watersheds of Iran and can be considered as one of the most important barriers to achieving sustainable agriculture and natural resources. This study was conducted to compare the MPSYAK, EPM and BLM models using kappa statistical coefficient to assess soil erosion and sediment production in the Seymareh-e-Charnar catchment area. For this purpose, the position of 90 points of erosion points was determined in a field survey by a GPS device and these points were adapted to the final erosion maps.The evaluation of the results obtained from the models used by the Kappa statistical coefficient shows that the MPSYAK model with Kappa statistical coefficient is 0.91 compared to the APM and BLM models with a kappa statistical coefficient of 0.76 and 0.71 of greater accuracy In assessing the risk of erosion in the Seymareh Chenar catchment area. Also, the results of the overlaying of the final erosion mapwith erosion points showed that in the AP model, 81% of the points in the medium-risk zone, the BBL model had 37% of these points in the medium-risk zone and in the M-PSYAK model 90% of the specified points In the middle danger area.
Therefore, it can be said that the studied area is in the middle erosion class and the M-PSIAC model shows more accurate results for erosion evaluation in this basin. Based on the zoning done using the M-PSYAK model, 7.93, 14.45, 77.62% of the area of the area is located in very low, medium and low risk classes. Also, based on the APM model, 27.44%, 32.16%, 40.40% of the area of the area were in low, moderate, high risk classes, respectively. The results of this model estimated the coefficient of erosion intensity of 0.58 and the total sediment produced during one year was 1921183.6 cubic meters.

 Statement of the Problem: 

Landslides are among the most important geomorphological hazards in mountainous areas. Large-scale landslides often have significant social and economic impacts, making them one of the costliest natural disasters worldwide, causing considerable damage to individuals and infrastructure each year. Nowadays, due to climate change and human activities, the frequency, intensity, and impact of landslides have increased, posing significant threats to life and property. In recent years, with rapid socio-economic development, the spatial extent of human activities has also gradually expanded. The occurrence of heavy rainfall has increased the frequency of landslides in mountainous areas and the resulting economic losses have gradually increased, turning landslides into barriers to human environment development. Given the complex physics and diverse nature of triggering mechanisms (such as rainfall and earthquakes), dynamic landslide monitoring is vital for risk assessment and management. While small landslides constitute the majority of landslide events annually, large landslides are usually responsible for a significant portion of casualties and damages. In most parts of the world, identifying their locations and effects still faces many challenges due to the diversity of landslide types and morphologies, as well as the difficulty in collecting and updating survey forms. Therefore, the development of tools and techniques for identifying and monitoring these widespread gravitational processes is of great importance. Spatial assessment and preparation of hazard maps are fundamental strategies in landslide risk management. In the present study, spatial assessment and zoning of landslide risk in the Zemkan watershed in Kermanshah have been addressed. This watershed drains parts of the western slopes of the Zagros Mountainous area and has a high potential for landslides.

In order to assess the spatial risk of landslides in the watershed, studies of 13 factors affecting landslide occurrence were conducted, including elevation, slope, aspect, the Melton ruggedness number, surface convexity, length of slope, valley depth, TWI, precipitation, geological formations, distance from streams, distance from roads, and vegetation cover. In line with the research objectives, the necessary data were obtained from 1:25,000 and 1:50,000 topographic maps; 1:100,000 and 1:250,000 geological maps; Aster satellite images with a resolution of 27 meters; Sentinel satellite images (with a resolution of 10 meters) and Google Earth (GeoEye with an approximate resolution of 1 meter); climate data; field studies; and library resources. ArcGIS, ENVI, and SAGA GIS software were used for the preparation and preparation of thematic layers and the execution of research models. A catastrophe theory-based approach was employed for zoning and spatial prediction of landslide occurrence risk in the Zemkan watershed area. Functions of catastrophe theory were used in GIS environment to combine and overlay these factors. The model employed was used to address uncertainties associated with decision-making and data classification. In this model, the weight of criteria is determined by the internal mechanism of the system, which has a mathematical nature.

The results of the research demonstrate the satisfactory performance of catastrophe theory functions in zoning the risk of landslides. The model accuracy, calculated using field mapping of landslide zones and receiver operating characteristic (ROC) curves, was approximately 90%. Catastrophe theory-based modeling showed that slope factors with a coefficient of 1.3, precipitation with a coefficient of 1.2, elevation with a coefficient of 1.1, and geological formations with a coefficient of 1 are the most important variables affecting landslide occurrence in the Zemkan watershed. Over 32.4% of the study area fell into high and very high susceptibility classes. Several conditions have led to significant portions of the central and southern parts of the Zemkan watershed having a high landslide potential. In this regard, factors such as high elevation and slope, significant precipitation, the presence of landslide-sensitive geological formations such as marl, clayey limestone, and shale (Kazhomi formation), westward orientation perpendicular to westward winds, long slopes, high drainage density, and human interventions are noteworthy.

In the present study, a model based on catastrophe theory was utilized to mitigate uncertainties associated with decision-making and data classification. In this model, the weights of criteria are determined by the internal mechanism of the system, which has a mathematical nature. The results of the model are repeatable and generalizable, thereby reducing decision-making uncertainties and enabling the integration of multiple quantitative and qualitative data. The research findings indicate the effectiveness of catastrophe theory functions based on GIS in spatial assessment and zoning of landslide risk in the study area. The alignment of landslide field mapping with landslide risk zoning maps and receiver operating characteristic (ROC) curves indicates a model accuracy of approximately 90%. The model results show that slope, precipitation, elevation, and geology are the most important factors influencing landslide occurrence in the Zemkan watershed. A significant portion of the study area falls into high and very high susceptibility classes of landslides, indicating a considerable potential for landslides in the Zemkan watershed and the need for planning to mitigate the risks associated with landslide occurrence.

Urban green spaces are generally available for free to city dwellers which have a vital and key role in people's mental and physical health. Despite the fact that many cities in the country have urban green space, it differs in terms of the distribution and other spatial parameters, both at the level of the cities in Iran and at the level of the regions within each city. This study evaluates the different characteristics of the green space of the holy city of Mashhad by applying the satellite image processing and analyzing data provided by the city municipality. In this research, utilizing the spatial data of the parks of the thirteen districts of Mashhad municipality and the land cover maps generated by Google Earth Engine system, eight landscape metrics of the land surface were calculated in GIS software for each of the districts. The results show the difference between the parks of each one of the thirteen districts of the city of Mashhad in terms of various landscape metrics. Also, the analysis of the results of this study showed that the 10th district of Mashhad municipality has a more favorable situation than other regions, both in terms of the number of parks and the ease of access to green space for citizens. The findings can be used as a ideal model for the development and improvement the spatial characteristics of other parks within thirteen regions of Mashhad.

The geographic information system, by combining decision-making models, can be effective in various areas of spatial development, including tourism capacities. Due to their characteristics and spatial differences, peri-urban tourism villages operate differently from other rural areas in the service sector. Due to these conditions, the required tourism services of these villages are also different. Izeh city has various suburban villages, some of which have tourist attractions. Due to these capacities and the geographical location of the villages in relation to the city of Izeh, these villages have become very important over time. As such, today we are witnessing the growth of the population, as well as the increase in the price of land and the change of land use in suburban villages. The touristic nature of some of these villages is another important factor that shows the importance of paying attention to the management, planning and development of services in them; Because the spatial distribution of services and the level of accessibility at the level of suburban villages should be done according to their capacities and geographical location, based on logical principles and criteria. The geographic information system and spatial decision-making models can be effective in this field and provide a prioritization of tourism services needed in peri-urban villages and determine the spatial distribution of services. Therefore, in this research, the aim is to evaluate the services needed for tourism development in peri-urban villages through the VIKOR model and analyzing their spatial distribution in the GIS environment.

The research method is descriptive-analytical and based on the applied goal. Two methods of library-document studies and survey studies are used to collect information. Field studies are based on common techniques, namely questionnaires. The number of 5 Pirasheri villages with tourism capabilities, including Kohbad, Kolfarah, Abrak, Noorabad, and Kell Infern, have been emphasized in this study. The statistical population of the research is made up of visitors who entered the villages. The sample size for each village was determined as 20 people and a total of 100 visitors were questioned. Further, after collecting the data, through the VIKOR model, villages were analyzed and prioritized, as well as the required services. Also, AHP method and algorithms available in GIS including central location, hot-cold spots and clustering of spatial statistics were used.

The results showed that, in general, the most important needed and important services were accommodation services with an importance coefficient of 0.389. In addition, transportation services are known with an importance factor of 0.186. Two types of health services with a weight of 0.146 and catering services with a score of 0.099 are also recognized in the third and fourth ranks. The lowest weights of criteria in the field of services required for tourism development in Urban-Peripheral villages are related to two technology services with a weight of 0.052 and shopping services with a weight of 0.055. The rate of compatibility of values and pairwise comparison of data is also equal to 0.05, which is less than 0.1 and therefore acceptable.Based on the results of Vikor model, Noorabad village has received the first rank in the field of required tourism services with a weight of 0.857. In fact, this village has more weaknesses in the field of tourism services compared to other villages, and it is necessary to create and expand various services, including accommodation and hospitality services in this village. After that, the village of Kolfarah with a value of 0.813 is recognized as the second most needed tourist service. Kohbad village is ranked third with a weight of 0.767 and this village also needs to plan and create various tourism services.Based on the results of the central location algorithm in GIS and applying the calculated price weight, Kolfarah village is known as the central village in terms of services required by tourism; Because this village has had an acceptable weight in calculations, and secondly, compared to other villages, it needs more promotion and attention in terms of tourism resources and existing attractions.Examining the spatial autocorrelation index shows that this index is equal to -0.367787. Since this value is close to negative (-1), it can be concluded that the data do not have spatial autocorrelation and are scattered. Also, by referring to the standard value of z, which is equal to -0.822, the hypothesis of autocorrelation in spatial distribution can be rejected, and as a result, the random pattern in the field of tourism services can be confirmed. In fact, Urban-Peripheral villages have had a random pattern in terms of tourism services. Therefore, the randomness of services and the existence of spatial differences between urban tourism villages are confirmed and based on this situation, planning and prioritization of services in villages should be done.

In general, according to the results, it can be concluded that the Urban-Peripheral villages are not at the same level in terms of tourism services. Another point is that despite the geographical location and proximity to cities, many weaknesses in terms of services can be seen in them. This is the context. In addition, the result of the research indicates the lack of concentration of services in a single village. In other words, the services are scattered in all the villages and this issue has made it difficult for tourists to access all kinds of services in the shortest time and at the lowest cost. The innovation of the research, firstly, in terms of methodology, is the integration of Vikor model and spatial algorithms in the GIS environment, and secondly, the use of spatial statistics algorithms in the survey of rural tourism services, which has received less attention.