جستجوی مقالات مرتبط با کلیدواژه « cluster analysis » در نشریات گروه « جغرافیا »

Environmental changes The environmental environment of any environment can be changed. In case of achieving this goal, first the average daily statistics (2021-2009) were received from the General Meteorological Organization for Nair city. The maximum limit is determined by using 99% of Frein's threshold limit, then for Frein's days, the sea level pressure value was extracted from the Nova site, and on this model, patterning was done with Ward's hierarchical clustering method based on Euclidean distance. As a result, two major patterns were identified and one representative day of each pattern was included in the synoptic analysis. For this, NCEP-NCAR data were used to draw synoptic maps in the software environment. The results showed that the thermal low pressure systems that entered Iran from the south-east and south-west sides covered the entire geographical area of Iran and especially the studied area and brought an unstable atmosphere. At this time, the warm air from the southern latitudes that flowed through the Naveh channel in the west of Iran towards the northwest of Iran was blocked by the blocking barrier located in the western half of Iran. The anomalous state of air temperature showed that on the investigated day, temperature changes increased by 4 degrees Celsius compared to the length of the week. Geodetic maps of temperature and temperature advection at the level of 500 hectopascals also show that the origin of heat movement is from the north-east of Africa and has been drawn towards the study area, and heat convergence has occurred in the study area and has added to the temperature.

For this purpose, the data of 13 climatic variables in 14 synoptic stations in a period of 44 years (from 1977 to 2020) used and a 13x14 matrix (rows; climatic elements and columns; number of stations) was created. In order to generalize the station data to the area, a grid with 15x15 km pixel was formed in central Iran and a matrix with dimensions of 446x15 (rows; digital pixel and columns; number of stations) It was found that the basis of the calculations will be factor analysis with varimax rotation and cluster analysis with Ward integration. The results of measuring the relationship between altitude and climatic variables indicate that in Central Iran, there is a direct and significant relationship between these two factors. However, due to the influence of local and macro-scale climatic factors, this relationship is not the same throughout the area and sometimes creates climatic nesting. In addition, the results showed that the 4 main and effective factors that make the climate of central Iran are: precipitation, temperature, humidity and dust storm. These factors explain 86.2 percent of the climatic behavior of this area. So that the rainfall with 35 percent is the most important climatic element in this area, which often dominates in cold mountainous regions and high altitudes. The temperature is 27.3 percent in the central deserts and the sides of Lut desert in Kashan, Khourbiabanak, Lar and Bam. Humidity is effective with 15.3 percent in parts of hot and humid southern areas in Baft, Abadeh and even cold and humid northern areas in Daran, Isfahan. Dust storms with 8.8 percent are the least effective factor in the climate of central Iran, which are scattered in Khourbiabanak, Bafaq, Yazd, and Kashan

Aerosol optical depth (AOD) is a dimensionless quantity that shows the amount of light passing through the atmosphere and expresses the amount of absorption and scattering caused by aerosols in the path of light passage. Knowing AOD is necessary to understand its effects on air quality and provide a strategy of confrontation with it. South Baluchistan basin is affected by dust and high concentrations of aerosol due to its geographical location. Therefore, in this study, the tempo-spatial changes of AOD in this basin have been analyzed. In this research, the data of the AOD product (MOD 04 L2) and, the Deep Blue algorithm of MODIS sensor of Terra satellite during the period of 2002-2019 were used. Principal component analysis (PCA) and cluster analysis were used for data processing. The results showed that the first component alone explains 84% of the variance of the data. The pattern of temporal changes shows that this component exists throughout the year, but it decreases in the cold period and increases in the warm period of the year. Based on the temporal changes of the AOD, the basin can be divided into four temporal periods: winter, spring-autumn, transitional, and summer. The mean AOD reaches 0.69 in the summer pattern. This means that the basin has relatively dusty weather during the summer. Based on spatial distribution, the basin can be divided into three areas: mountainous, piedmont, and plains. The average AOD in the basin is 0.38, which reaches 0.62 in the plain zone. The AOD regime is the same in all three zones, but the plain zone is significantly different from the other two zones in terms of quantity. The high deal of AOD in this basin is related to regional factors that are active in the warm period of the year (Indian monsoon) in addition to local factors.

The purpose of this study was to investigate the changes in Iran's climate zones during the periods 1965-1975, 1976-1985, 1986 -1955, 1996-2005, 2006-2015. For this purpose, the weather data (minimum, maximum, average), humidity (minimum, maximum, average), rainfall, wind and sunshine for 411 synoptic stations during the period 1965 to 2015 were collected and analyzed by the Iran’s Meteorological Organization. Moreover, the Asafzari database was also used in two sections. The first section was formed with the help of 1434 stations from the beginning of 1961 to 2004 and the second section from 2004 to 2015 with the help of 960 stations. At first, factors influencing the climate of Iran were analyzed using factor analysis and then clustered using cluster analysis. In order to validate the identified areas, Silhouette Index (SI) was used. The results showed that most of the spatial variations during the five periods studied were very hot and dry (very low rainfall and high temperature), warm and dry (low rainfall and high temperatures), and cold and dry (low rainfall and low temperature) so that each of these three areas, for example, the cold and dry (low rainfall and low temperature) areas, reduces. On the contrary, the size of the two other areas increased. This dimension of change in the first and second period has been quite evident. The results of the silhouette analysis also showed that more than 92 percent of the Iran’s zones were located right in their group, which indicates the high validity of the identified areas.

Shamal wind is one of the local winds with high continuity and diversity in the Middle East and the Persian Gulf region, which often causes dust storms during the summer. In this research, the hourly data of sea level pressure, geopotential height, U and V winds were collected for a period of 44 years from the Copernicus database. First, these data were arranged as a long-term mean, secondly. In order to process the data, principal component analysis and cluster analysis were used. Applying the PCA showed that more than 97% of the variation of the data is explained by three components. The score map of the first component revealed the spatial mechanism of the Shamal summer wind and the eigenvector diagram of the first component of the time period of the Shamal summer wind activity. In addition, the hierarchical cluster analysis on the time-space matrix of SLP showed three-time clusters that represent the time period of the north wind in summer and winter. The analysis of the maps of the monthly pressure distribution pattern showed that the most important active and influential system in the region is the low pressure of the Persian Gulf in the summer season, and the low pressure of the Red Sea in the winter season. The results suggest that the changes in the patterns of the earth's surface at the levels of 500 and 700 hPa are not much significant while it shows a better existence in the 850 and 1000 hPa maps.

Precipitation anomalies, especially drought and its changes are among the most important topics in climatology. The current study was carried out to regionalize drought events and evaluate the changes in their extent in annual, seasonal and monthly time scales. For this purpose, EAR5 monthly rainfall data and the RAI drought index were used. Hierarchical cluster analysis based on Ward's correlation-integration distance Mann-Kendall's test and the slope of the regression line were used to extract spatial clusters and their changes. The number of spatial clusters (areas) of co-occurrence of drought in the rainy season and months is wider and more homogeneous than in the less rainy months such as the summer season. Certain geographical-climatic areas such as Southeast, Center, Northwest and West-Southwest are seen most of the time. The annual drought changes in none of the areas show a significant trend, which could be due to intra-seasonal and monthly contrasts in drought changes. So in winter and spring (the main rainfall period of the country), an increasing trend was observed, and on the other hand, in autumn, a decreasing trend of drought was observed. On a monthly scale, the most obvious increase trend has occurred in the two main months of rainfall in the country, namely January and March, and a decrease in November. The results of the research can indicate the temporal shift of rainfall or the change in the country's rainfall regime

Historical contexts serve as significant carriers of ancient heritage, conveying cultural and civilizational messages across generations. The surroundings of the holy shrine in Mashhad boast valuable historical and religious landmarks such as historic houses, mosques, gardens, and caravanserais. However, due to their integration within aging urban fabric, these sites face challenges including visual degradation, structural integrity issues, accessibility constraints, and deficiencies in urban infrastructure. Despite the establishment of regeneration offices, efforts to preserve and maintain these sites have not been entirely successful. This research aims to assess the operational pathology of facilitation offices, particularly focusing on tourism, within the central fabric surrounding the holy shrine. The study employs a mixed-method approach, combining qualitative interviews conducted between 1401-1402 with 28 managers of facilitation offices. Findings highlight critical factors contributing to operational pathology, including the knowledge of urban regeneration experts and related entities (coefficient of importance = 0.184), urban management's perspective on tourism (coefficient = 0.110), financial resource inadequacies within regeneration organizations (coefficient = 0.099), expertise deficiencies among regeneration experts (coefficient = 0.095), reluctance to collaborate with other entities (coefficient = 0.086), and weaknesses in the evaluation system of regeneration organizations. These results prioritize key areas requiring intervention for enhancing the performance of neighborhood development offices in the vicinity of the holy shrine.

Domestic tourism plays a key role in the tourism industry. With the global boom and expansion of the tourism industry, an increasing number of regions in developing countries have recognized the importance of tourism as an important factor in the development of the regional economy. As a bridge between the West and the East, Iran has a special place in the field of tourism in terms of special geographical conditions in the region and the Middle East, in terms of special geographical conditions in the region and the Middle East. Indeed, the expansion of economic, health, security and communication infrastructure in the 21st century has made tourism an inevitable reality in human life. Ardabil is one of the cities of Iran and the capital of Ardabil province in northwestern Iran. Ardabil province, due to its unique historical and geographical conditions, has many tourist attractions and in different seasons of the year, it receives many tourists from different parts of the country. The climatic attractions of Ardabil province are richer in spring and summer than in winter; Also, in terms of topography, Ardabil province has very strong potentials in the mountainous part. The province has many attractions. Sarein and Meshkinshahr are also two tourist cities in Ardabil province that attract many tourists to this province every year due to their pristine and eye-catching nature and warm waters. Tourism market segmentation is one of the important measures that can help marketers and planners of tourism destinations in identifying the needs and wants of tourists. The basis of tourism market segmentation is based on the concept that tourism markets are composed of different and diverse groups of tourists that members of each of these groups needs, wants, interests, personality, travel behavior, shopping style and have the same reactions to the variables of a tourism product or service offered. Segmentation serves as an important strategic tool for tourism marketers and provides practical insights into targeting, positioning and competitive analysis. Customer segmentation into different groups and identifying the characteristics of each group helps us to adopt better marketing approaches and on the other hand creates creative ideas.

The current research is a descriptive survey in terms of data collection. Also, considering that the purpose of this research is to segment the tourism market based on the travel motives of tourists, it is practical in terms of the purpose. The statistical population of this study consists of domestic tourists visiting the cities of Ardabil, Sarein and Meshkinshahr between the first of May and the end of July 2017.Sampling was done using available sampling method and the required sample size was calculated based on Cochran's formula for an unlimited population, 384 people, and the number of samples were equally divided between three cities of Ardabil, Sarein, Meshkinshahr. In order to distribute the questionnaires, the prominent tourist areas of these three cities were visited in person during the specified time period.

Chi-square test was used to examine the differences between clusters based on demographic characteristics. The results show that there is a significant difference between all clusters based on demographic characteristics at the 95% confidence level. alsoIn this research, only the travel satisfaction variable has been used as a psychological characteristic. The results indicate that there is a significant difference between the clusters in terms of travel satisfaction at the 95% confidence level. The selected behavioral variables in this research included visit experience, travel companions, length of stay and source of information. The results indicate that at the 95% confidence level, there is a significant difference between all clusters in terms of behavioral characteristics. Except for cluster 4, in the rest of the clusters, more than half of the people have experienced revisiting.

As a general conclusion, it can be said that in general, the cities of Ardabil, Sarein and Meshkinshahr have many tourist attractions in most areas. Offered. For example, due to the importance of the family cluster compared to other clusters, it is necessary to create safe, comfortable and suitable environments for families, or due to the fact that the second cluster was emotional in importance, creating exciting environments or at least creating safe and clear paths. Equipping them for mountaineering will help attract more travelers to these areas. In any case, it should be noted that the most important step in the development of the tourism market is the development and improvement of urban infrastructure, attracting capital and increasing the culture of tourism among the general public. The existence of differences in motivations and goals and in general demographic factors and psychological characteristics of tourists and their behavioral patterns, clarifies the need for knowledge and knowledge of planners and trustees of tourism affairs of these characteristics. This knowledge provides a better understanding of tourism and is a valuable guide for designing more effective development plans. The main reason for the study of the motivations of tourists in choosing a tourist destination is that measuring the motivations of tourists allows us to understand the preferences and needs of tourists. Understanding what motivates tourists to choose a destination and what they tend to experience is in fact a set of vital information very important for tourism planners to improve the quality of visitor experiences and their satisfaction. If a careful study of the motives and desires of tourists in choosing different tourist destinations is not done, the desires and needs of tourists will always remain unknown and tourists will lose their satisfaction from traveling to these destinations. The results of this study show that one of the appropriate methods of market segmentation is to base the motivational factors of visitors; But this variable alone does not provide the marketer with complete information about the obtained sections.

Having sufficient information about the operation area is one of the most important and key success factors in planning, directing and successfully implementing operations, and this issue is of double importance, especially regarding the weather conditions of the area, in water and soil operations. In order to conduct research and identify the weather types of Abu Musa Island, in order to plan and implement hydrological operations, the data related to 18 weather variables in a period of 30 years (1991-2021) as well as the average and maximum strength of the sea in one day have been used. In order to statistically analyze the data and obtain the statistical characteristics of each weather type, MATLAB software was used and to identify the weather types, weather elements were subjected to cluster analysis by integration method. After conducting trial and error operations to select the number of air brigade groups, four air brigades were finally identified for this island. Hierarchical analysis has been used to determine the most suitable and worst type of weather. The results showed that based on the pairwise comparison of weather elements to determine the priority of the air force to carry out soil dredging operations, the elements of wind speed and horizontal visibility were assigned the highest weight and the most effective weather elements in soil dredging operations were identified. After forming the decision matrix, the weight of each of the specific weather types and the moderate weather type with the maximum sea power with a weight of 0.343 with the activity period in the late winter and early spring season was estimated as the worst weather type for carrying out dredging operations in Abu Musi Island

IntroductionNomadic tourism destinations are considered as an important part of the tourism system and a result of the transformation and development of a spatial-spatial phenomenon in space; Due to the balance in the spatial distribution of growth and development factors, a large number of host communities located in the geographical territory of the destination are also affected by the developments and benefits of tourism development and can play an important role in the formation of the image of the destination.Methodology The purpose of this research is to analyze the clusters of nomadic rural tourism attractions in the Papi Sepid part of the Lorestan Plain; Finally, the optimal model of the spatial organization of rural tourism destinations in this area was designed. The research method was descriptive-analytical and applied. The statistical population of this research consisted of 315 villagers living in 14 selected villages of the region (using stratified random sampling). To collect data, field methods and a questionnaire were used, the reliability of which was calculated using Cronbach's alpha test, which indicated the appropriateness of the research tool. To analyze the data, cluster analysis was used in the SPSS20 software environment, and ArcGIS software was used to draw maps and patterns of spatial organization suitable for rural tourism.Geographical area of researchtourism destinations in the rural areas of Sepid Dasht Lorestan (Papi sector) which mainly relied on ecotourism.Results and discussionThe findings showed that spatial organization with the first degree (spatial development with a high degree) was related to Cham-Sanger and Tang-Heft dehistans. Spatial organization with degree 2 (spatial development with moderate degree) was related to Bisheh and Garit dehistans and spatial organization with degree 3 (spatial development with weak degree) was related to Dehistan of Iran.ConclusionFor the spatial development and organization of tourism in the Papi sector, a concept (an intervening view of factors) is needed for spatial development, in other words, for spatial organization in this region, having a systematic and integrated view of all resources and factors in space (resources) human and natural resources) is necessary and requires a comprehensive regional planning.

Soil surface sealing is mostly influenced by the specific prevailing conditions during its formation, and the variables affecting soil surface sealing are the physical characteristics of the soil, the chemical conditions of the soil-water system, the characteristics of rain, and the initial and boundary conditions of the flow (Mualem et al, 1990). It is a common phenomenon in most soils of Iran due to arid and semi-arid climate, weak vegetation and loose soil aggregates. In Kowar plain, as an important Agricultural pole of Fars province, it is very important to determine the factors affecting the formation of surface sealing, to identify the most important characteristics of the soil in controlling the surface sealing formation, and to provide a suitable index to determine the sensitivity of the soil to this formation based on the characteristics of soil erosion, which are very important issues and have been addressed in this research study.

To carry out this research, 80 samples (0-20 cm) were selected from Kowar plain with a variety of physical and chemical characteristics, and after sampling, the samples were air dried and passed through a 2 mm sieve. Then, the parameters of particle size distribution, humidity, organic matter, electrical conductivity and pH of saturated soil extract were measured. In addition, the average weight and geometric mean diameter of soil aggregates, calcium carbonate equivalent, fractal dimensions of one-centimeter soil particles (Bartoli, et al, 1991), percentage of moisture saturation, sodium, calcium and magnesium were determined. The saturated hydraulic conductivity of the samples were measured and the evaluation of soil sensitivity to the surface sealing with seven different indices of SI, RSI, CI, WAS, PR (Permeability Resistance), CSI,   C5-C10 had been performed. Also multivariate statistical methods (cluster analysis, discriminant analysis and canonical correlation) were used for conducting the required analyses.

 After conducting the multivariate statistical method investigations, the results of cluster analysis led to the creation of a discriminant function with a chi-score of 12.73 reaching significance at the probability level of 0.001. This function completely showed the power (ability) to create separation between the two cluster analysis result groups. The organic matter was the most important primary variable that separated these two groups from each other and was significant at the probability level of 0.001. Based on the structure matrix, it was determined that CI, SI and CSI indexes with coefficients of 0.85, 0.58 and 0.30, respectively, are among the most important indices in the separation of these two groups. The performed canonical correlation provided a canonical function with a correlation of 0.99 and a chi score of 626.2. The highest canonical correlation belongs to primarily organic matter and then to clay. Two indices of Soil Stability Index (SI) and Crusting index (CI) were the most important indices having the highest correlation level among the indices. The most important variables influencing the evaluation indices of the sealing surface in the two group’s separation were organic matter and clay, which provided a function with high capability and the highest canonical correlation, respectively.

  The highest coefficient of variation is related to the mass of soil particles with a length of one centimeter (Bartoli model) and the highest canonical correlation in the first degree belongs to the organic matter and clay, it also shows the most important variables, with the highest correlation between these two variables with the mentioned indicators (CI,SI). In addition, two indices of SI and CI were the most important indices having the highest correlation among the indices. The results of cluster analysis, the discriminant function analysis and canonical correlation showed that the most important variables affecting the sealing surface evaluation indices in separating two groups and providing a function with high capability and the highest canonical correlation are organic matter and clay, respectively.  Also based on the structure matrix, the crusting index and aggregate stability are the most important indices that separate the two groups. In fact, the main samples differentiating factors in terms of the sealing surface are the above named indices. Organic matter and soil stability indexes have become significant with a very high correlation and showing a better justification of this indicator (SI) with the characteristics of the soil in determining the sensitivity of the soil to the seal structural formation layer.

The favorable situation of the housing sector is one of the important indicators of social and economic development. Planning in the housing sector in order to achieve the desired situation requires identifying and analyzing the broad dimensions of this sector. One of the most important steps in housing planning is awareness and review of the current housing situation. One of the important ways to be aware of the current housing situation in order to plan housing is to use housing indicators. These indicators, on the one hand, indicate the quantitative and qualitative status of housing in each period of time, and on the other hand, are an effective guide for improving housing planning for the future (a key tool for charting the future of housing).

Objective of the research: 

The present study is the ranking and leveling of the cities of the province using housing indicators.

The approach of the present study is applied and the research method used is descriptive-analytical. In order to collect information from the documentary and library methods used and the required information of housing sector indicators, has been extracted from the results of the general population and housing census of 2016 in Golestan province. In order to analyze the data, TOPSIS technique and cluster analysis and in order to show the spatial levels of the studied cities, Arc Gis software has been used.Geographical area of ​​the research: The geographical area of ​​the present study is the cities of Golestan province, which includes 14 cities of Gorgan, Gonbad, Aq Qala, Bandar-e Turkmen, Minoodasht, Kalaleh, Azadshahr, Ramian, Aliabad, Kordkoy, Bandar-e-Gaz, Gomishan, Galikesh and Maraveh Tappeh.

The research findings show that among the cities of the province, the cities of Gorgan, Ramyan, Aliabad and Gonbad are among the most enjoyable and Maraveh Tappeh, Galikesh, Minoodasht and Turkmen are among the most deprived cities of the province in terms of indicators. Are housing.

The general conclusion of this study indicates that the distribution of housing indicators in the province is unequal and cities that are far from the center of the province have more inequality.

Today, the concept of cultural tourism has drawn upon the factor of culture to facilitate development. The most important prerequisite to stress culture and culture-based industries necessitates a solid background.  Tehran, as the capital of Iranian civilization, has this advantage which can help the cultural tourism industry to contribute to urban development. However, the concept of cultural tourism is neglected in urban development plans. Therefore, the questions that arise include: a) what are the indicators of cultural tourism for the development of Tehran? b) How is the development in the 22 districts of Tehran ranked based on cultural tourism? This research is descriptive-analytical nature using a mixed approach to explain the framework of cultural tourism’s effectiveness on the development of Iranian cities. To this end, ranking the development status of the 22 districts of Tehran was carried out based on a road map to benefit from the hidden cultural treasures of Tehran by attaching cultural tourism to urban development plans.  This study employed documentary, and field study methods as data collection methods while content analysis, swing weighting, taxonomy-numerical, and cluster analysis were used as analytical methods. The results show that the 12th district of Tehran, with the most recorded places, and historical sites, Oud Lajan Bazaar, and Tehran Bazaar, have been given a higher priority compared to the rest districts of Tehran. Districts 6 and 1 of Tehran have had a better rank compared to other districts because of hotels and exhibitions of painting, photography, and sculpture and they have been ranked second and third respectively.

Cemetery is one of the effective elements in arranging the spatial structure of human settlement and especially Iranian cities. The social-cultural development of cemeteries along with the increase of social interactions and presence of citizens will bring vitality to urban spaces. The current research is applied in terms of purpose and descriptive-analytical in terms of method. The method of data collection is documentary and survey, and ArcGIS software and models such as cluster analysis (Group Analysis) and interpolation (IDW) were used for quantitative data analysis. In order to identify and verify the cultural areas of cemeteries, accessibility indicators such as Imam Reza shrine, typical tourist attractions, historical monuments, residential centers and other citizen facilities and services were used. The results showed that the shrine complexes of Imam Reza, Gonbad Kheshti, Gonbad Sabz and Khwaja Rabi as the first cultural area, Yasir and Nasser as the second cultural area, Khwaja Murad and Khwaja Abbasalt as the third cultural area and Miami as the fourth culture area can be identified. In order to increase the role of the cultural areas of cemeteries in the urban vitality of Mashhad metropolis, the indigenous model of the garden-cemetery to promote the Iranian identity in historical cemeteries and the planning of tourism facilities and equipment through the spatial-functional connection of cemeteries with the shrine of Imam Reza in socio-cultural development of urban cemeteries is effective.

Identifying homogeneous climatic zones plays an important role in the success of regional development programs. The climate system is composed of various elements, factors, and variables that together form the climatic components of a region. Multi-characteristic and multivariate methods can combine and overlap the types of elements and variables effective in constructing the climate with appropriate weights in the climatic zoning area. In the present study, climatic zoning of the Caspian region was performed using factor analysis and cluster analysis. For this purpose, a 30*30 matrix consisting of 30 meteorological stations and 30 climatic and environmental variables was formed. The results of factor analysis showed that the climate of the region is affected by 5 factors including precipitation-humidity, temperature, wind, sunlight, and environmental factors. These factors explained a total of 92.5% of the variance of the data. Then, cluster analysis was performed by the hierarchical integration method of Ward on the five mentioned factors. The results showed four climatic zones including humid, semi-humid, semi-arid, and arid in the study area.

One of the important branches of synoptic climatology is identifying the extreme states of environmental features, such as severe storms and especially heavy rains and floods (Alijani et al., 2008, 107). Flood is the most common environmental damage. Every year, floods kill more than 2000 people and unfortunately affect 75 million of the world's population (Mohammadi and Masoudian, 2008, 70). Flood is considered as one of the most important natural disasters in our country, and what makes this natural disaster a disaster is the lack of awareness to deal with its consequences and prevent the adverse effects of natural events on the pillars of economic and environmental well-being. Therefore, since heavy and torrential rains are dangerous and damaging environmental phenomena that occur in most places, especially in areas with little rain, and cause a lot of damage, identifying the synoptic conditions that cause these rains can help in predicting the time of occurrence and implementing the necessary preparations.

In this study, two categories of ground and upper atmosphere data are used as follows:A) Use of daily rainfall data from October to December for 22 stations located in Kurdistan, Kermanshah, Hamedan, Lorestan and Ilam provinces, which were obtained from the National Meteorological Organization during the statistical period of 1991 to 2019.B) Using high-level data. Includes reprocessed data for components of geopotential height, sea level pressure, zonal wind, meridional wind, specific humidity, and omega obtained from the US Environmental Prediction Database. The spatial resolution of this data is 2.5 by 2.5 arc degrees. TRMM satellite data with a spatial resolution of 1 x 1 degree was also used to analyze rainfall and runoff. To perform synoptic analysis, the environmental to circulation method has been used; In this way, first, the days of heavy rains were identified with the 98% percentile method, and then their synoptic dimensions in the space between 10 to 70 degrees north latitude and 0 to 80 degrees east longitude were investigated. By considering and applying the two conditions of rainfall threshold greater than 98 percent and covering more than 50 percent on the daily rainfall data of the autumn season (September 23 to December 21) during the period from 1991 to 2019 at selected stations in the western provinces of Iran, 20 days super heavy rain was extracted. The amount of precipitation on the mentioned days ranges from 22 to 81 mm; which shows the lower intensity of heavy rains in the autumn season compared to the winter season of the region. In this research, using the obtained data, maps of sea level pressure, combination of geopotential height and Omega, humidity advection, jet stream, precipitation rate, runoff and profile have been drawn and analyzed using Grads software. In the next step, in order to classify the patterns of sea level pressure on the days of heavy rain, the s-mode cluster analysis method was carried out using Euclidean distance and Ward technique.

Figure 2 shows the clustering tree of sea level pressure data during the days of heavy and pervasive rainfall in the western half of Iran. In this research, s-state cluster analysis method with Ward integration technique was used to classify pressure patterns during days of heavy rain. The obtained patterns were also checked by visual method and trial and error in order to select the best classes with the least intra-group difference and the most extra-group differences and changes. Finally, after the investigations, 4 pressure patterns were identified. But in this research, due to the similarity of patterns and the large number of maps, 3 final patterns were selected for analysis. The identified patterns are the first pattern of multi-core low pressures (Sudanese, Mediterranean and Saudi) with 8 days, the second pattern of Sudanese low pressure with 8 days and the third pattern of North European-Atlas, Mediterranean and Sudanese low pressures with 4 days (Table 1). In terms of time, the months of November, December and October have the highest number of rainy days. The slope of the heavy rainfall trend in all stations except Ilam shows a slight increasing trend. Only Ilam station has experienced a weak negative trend of heavy rainfall. This behavior of the trend of heavy rain actually indicates the increase of flood rains in this region of the country in the autumn season. Based on the frequency of days of heavy rain, the selected stations of Sanandaj and Hamedan are equal to each other with 26 days of heavy rain, Kermanshah and Khorramabad stations with 24 days and Ilam with 15 days. It can be seen that there is a slight difference between the stations in terms of the occurrence of this extreme and risky phenomenon, which can be an indication of the effects of circulation patterns on a synoptic scale that have created these conditions.

The statistical analysis of the days of heavy rain in the western part of Iran in the autumn season showed that the months of November, December and October have the most frequent days of heavy rain. Most of the stations in the region experience a weak positive trend of heavy rainfall on an annual scale, which indicates an increase in the occurrence of such extreme events in the autumn season of the last few years. Based on the 98% percentile threshold, the frequency of rainy days in the selected stations ranges from 15 to 26 days, and there is a slight difference between the stations in this regard. For the synoptic section, after classifying the sea level pressure patterns by cluster analysis method, a visual inspection of the pressure maps from a few days before the peak of rainfall was done to ensure the type of pressure systems and their main origin. Finally, after the investigations, 3 final patterns of super heavy rainfall in the west of the country during the autumn season were identified. The results of the analysis of sea level pressure patterns showed that in the first pattern, multi-core low pressure centers are located over the Middle East. In the second pattern, we see extensive changes in the pressure values in the Northern Hemisphere, in such a way that the Siberian high pressure with an east-west movement covers all of Russia, East and Central Europe, and North-East Africa, It has not allowed the penetration of low pressure systems from the Mediterranean and Europe, and in this case, only the Sudanese low pressure entered the studied area after passing through the Red Sea and Arabia from the south-west and south of Iran. But in the third pattern, the pressure changes in the Northern Hemisphere are the opposite of the other patterns, so that since the days before the peak of rainfall, the closed low pressure center from the north of the Atlantic Ocean has started to advance eastward and with the extension of its tongues on the southern latitudes, created the secondary Mediterranean low pressure in the west of this sea, and on the day of peak rainfall, it is located in the east of the sea, or it merges with the low pressure tongue of the North Atlantic, and it covers the western region of the country in a unified manner with the closed low pressure of Sudan and Arabia.

In order to identify effective sea level circulation patterns in creating atmospheric rivers associated with heavy rainfall in Iran, sea level pressure data in 940 days of the occurrence of this phenomenon were analyzed by principal components analysis(PCA) and reduced to 13 principal components, and by applying Ward Hierarchical clustering analysis on them, 5 main patterns or circulation types with subtypes were obtained.The results showed that the establishment and expansion of eastern and western high pressures in the mid latitudes and strong low pressures of high latitudes with weak to strong low pressures of low latitudes, especially Sudanese low pressure in the study area, in all circulation types, highlights the role of moisture transfer from two sources of the northern Atlantic and the northern parts of the Indian Ocean moisture which Through the strengthening resources of the Mediterranean and Red Seas, they supplied atmospheric rivers moisture and mainly caused heavy rains on the western slopes of the Zagros and southwestern Iran.

Atmospheric circulation has a variety of patterns in terms of time and space, However, drastic changes in atmospheric factors and elements have caused anomalies in these patterns, which result in changes in temperature, humidity, pressure and precipitation in different parts of the world, one of which can be the snowfall in snow-covered areas. Snow cover has significant effects on climate, such as the effect of radiant energy in the region and atmospheric and thermal circulation, and any changes in climate may have long-term environmental and economic consequences for the time, amount and distribution of snow. Cold, rainy and snowy winters are a feature of the mountainous climate of the Central Zagros region of Iran, which is the gateway for various humid air masses to enter Iran from the Mediterranean and Eastern Europe. With this feature and being mountainous, the region is witnessing low temperatures and snowfall in the mountainous areas of this region. In this research, snowfall in the Middle Zagros, which is the source, the most important catchment area of the country and the source of the most important and largest rivers in Iran to the south and southwest of the country is investigated. This is especially necessary in the mountainous areas of the Zagros, where water from snowmelt plays an important role in runoff, which can be considered a pivotal operation in the field of water resources management and flood control in the Zagros. Therefore, the present study tries to investigate the relationship between changes in snow cover in the Middle Zagros region and changes in atmospheric circulation patterns using synoptic methods. The purpose of this study is to analyze the synoptic characteristics of the Middle Zagros snow cover in relation to atmospheric circulation patterns and to explain the spatial and temporal characteristics of this phenomenon using the statistics of synoptic stations in the study area. The results can help in forecasting and planning surface and groundwater resources as well as drought and prevent damage due to flooding of rivers in this region, most of which is due to snowmelt in the highlands of this region. The data required for the study include hourly and daily meteorological statistics of snowy days at synoptic stations in the three provinces of Ilam, Kermanshah and Lorestan, which were obtained from the Meteorological Organization. Geopotential altitude data of 500 and 850 and sea level were also obtained from the website of the National Center for Environmental Prediction and the National Meteorological Research Center (NCEP / NCAR). These statistics cover the long-term period (2018-1989). After extracting the snow day codes (including codes 70, 71, 72, 73, 74, 75), it was found that among the stations in the region, 14 stations had days with snow to be checked, which in terms of time distribution. And have a statistical period of 30 years and cover the entire Middle Zagros. In this study, after collecting statistics and data on snow-related days during the statistical period (1989-2018) in synonymous stations located in three provinces of Kermanshah, Ilam and Lorestan, as well as data on different atmospheric levels from the site of NCEP/NCAR center in Middle Zagros, they were processed using factor analysis and hierarchical clustering techniques and The results were analyzed and finally different snow-generating companion patterns in the study area were studied in detail. The results of studying circulatory coping patterns after analyzing the data at the levels of 500 and 850 hpa were entered using factor analysis technique and hierarchical clustering method, four models of companionship governing the snowy days of middle Zagros were identified and determined. These results showed that four distinct patterns for snowfall in middle Zagros can be identified. Accordingly, the first and third patterns with a total of 64.5% of the dominant pattern of snowfall in middle Zagros are mainly due to the establishment of high pressure center in the Mediterranean and Black Sea and the study area in the front of the deep landing at a high level Also, in most cases of heavy snowfall, a cold hole is formed at the level of 850 hpe which covers the study area and In most cases, a strong carrier is located in Eastern Europe or stretched diagonally from the west of the Caspian Sea to the south of the Red Sea. The study of patterns shows that the high-elevated center of the western Mediterranean and tibetan plateau is strengthened and by moving to higher latitudes, it helps to create strong graphs with north-south axis in Europe and Asia. The creation of these crypts and the existence of low-lying or cold centers in western Iran strengthens the eastern Mediterranean frigate and stretches to low latitudes and causes cold escape in the study area. On such days, the polar vortex fold extends to low latitudes such as the north of the Caspian and western Iran with the north-south or northeast-southwest axis, causing cold air to fall in the region. In the study of patterns and days of heavy snowfall, it is necessary to penetrate the polar vertex fold into low latitudes for heavy snowfall.

This research aims to identify the synoptic patterns of dust generation in Kohgiluyeh and Boyer Ahmad provinces. Therefore, two sets of data including the daily data of dust code 06 from Hamdid stations in the statistical years 2007 to 2017 and the variables of air temperature, geopotential height, sea level pressure, orbital wind, meridian wind, specific humidity, and omega were used as upper atmosphere data. To check the synergism of the dust-generating patterns in the given years, the uneven circulation patterns of the geopotential height of 500 hectopascals in the dusty days of the province were drawn. After determining the days of dust using cluster analysis and integration by the Ward method, 5 patterns were extracted and drawn on the roughness data of peninsular height of 500 hectopascals. The results of this research showed that there is the most significant relationship between the synoptic patterns of the Middle East region and dust events in the province by circulation patterns number 2 and 5 at the level of 500 hectopascals. For a better conclusion of the conditions and factors causing the dust phenomenon in Kohgiluyeh and Boyer Ahmad provinces, maps of average sea level pressure, specific humidity at levels of 1000, 850, and 700 hectopascals, omega (vertical air velocity in the atmosphere) at levels of 1000 and 400 hectopascals, Tavai ( Convergence and divergence of wind) at 500, 700 and 1000 hPa levels and drawing of a jet (river of wind) at 200 hPa level during the rule of each of the models were drawn and analyzed.

Optimal allocation between different economic sectors requires a correct understanding of the efficiency of resources in each sector. When there is a scarcity of one or more resources that play a more vital role in the production of a sector, the optimal allocation of that scarce resource between different sectors is critical. In this study, different provinces of the country in terms of spatial dispersion and levels of development of horticultural indicators have been measured by different methods of factor analysis and cluster analysis as well as HDI method. Cluster analysis and HDI in geographical studies In this study, an attempt has been made to study the spatial distribution of horticultural indicators in 30 provinces of the country in terms of development. For this purpose, 22 normalized variables were studied. They selected 4 factors that contain 87% of the information of primary variables and then based on these four factors, different provinces of the country were classified into 5 homogeneous clusters and to measure its development by Horticultural development index method, agricultural development index. It has been used that the most developed province in terms of horticulture is Isfahan with HDI 0.37% and the most deprived provinces of Bushehr and Qom with HDI is 0.94%.