JOURNAL OF GEOGRAPHICAL SCIENCES
Year:2018 | Volume:17 | Issue:47 |Papers Count:19

The aim of this study is modeling spatiotemporal variations of albedo. This study was conducted using simultaneous effects of several components, such as wetness of surface layer of soil, cloudiness, topography and vegetation density (NDVI), using MEERA2 model with a resolution of 50 in 50 km during 2000-2010 in Iran. The results of spatial analysis of albedo values in Iran showed that the highest value is in 44 to 45 degrees of east longitude about 2.8 to 3.3 and the lowest value of albedo is also in 52 to 53 degrees of east longitude, that is, the eastern slopes of the Zagros Mountains, have been recorded at 1 to 1.5 units. In terms of provincial rank, the largest albedo is about 0.25 units in Ilam province and the Fars province is ranked next about 0.24 units. The lowest amount of albedo also in the Gilan provinces and in next Mazandaran province are about 0.19 and 0.18 respectively. In addition, the results of temporal analysis in seasonal scale showed that the highest albedo in Iran in winter was 0.26 and its lowest amount was recorded in spring with 0.23 units. In general, according to the factors used, it can be said that the western and central parts of the country have a highest albedo, and the north and northwest regions of the country have a lowest albedo.

In recent decades, developing urban tourism as one of major economic activities in different countries has caused many managers and planners to consider increased quality of tourism experience and protecting interests of host communities to expand the activities of this industry, knowing potentials, existing problems, decision making and planning. To do so, strategic planning can be propounded as a response to difficulties occurred due to lack of appropriate planning in tourism. In core tourism like all other commercial activities, strategic tourism should be depicted. So, one of strategic planning models used to develop tourism particularly urban tourism is a traditional model called SWOT. Therefore, in present study, it has been endeavored of Shahr-e-kord located in Chaharmahal-e-Bakhtiari as well as to analyze difficulties and problems existing in respect of Shahr-e-kord tourism. His study is a descriptive-analytic one and was done using filed studies and data gathered through evidence and libraries, questionnaires (considering the attitude of 70 officials and tourists) and Internet. Then, data was analyzed using excel software and strategic model of SWOT. Results suggested that due to having high capacities for tourism, Shahr-e-kord suffers from lack of enough infrastructure problems. On the other hand, it encompasses opportunities for educated young people to be employed and for investing. Some of major solutions to develop tourism are to increase advertisement, provide welfare and accommodation facilities, attract investment and be protected by government.

Suspended particles management is one of the important issues in controlling the air pollution of cities. These particles cause and develop heart and respiratory diseases in people. Mashhad is considered as one of the main and populous cities of Iran. Because of its climatic conditions and its tourism, the city is at the highest risk of this type of pollution. We attempted to use the multi-layer perceptron (MLP) artificial neural network and a Markov chain model to predict PM10 concentrations the city. We applied hourly data of CO, SO2 , PM2.5 and temperature in late March and April 2015. Out of 1488 data series, 1300 data were used for network training and 188 data were used for validation. The results indicated the optimal performance of these methods in predicting of the amount of pollutants and also the probability of occurrence of hours with different quality of contamination. The best MLP artificial neural network model predicted the amount of pollutant particles with a coefficient of determination (R2 ) 0.88, index of agreement of 0.91 and a mean square error of 2.26. Also, the Markov model with average absolute error predicted about 0.1 percent of the probability of transferring the condition and the continuation of different states of air pollution caused by suspended particles.

Identify water resources management and proper application of relevant officials and managers are the main concern. Groundwater as a most important natural resources of Iran needs to planning and management of all aspects. In this regard, a study done of the Shaharchay river basin in the west of the Urmia Lake and the northern structural, sedimentary zone of Sanandaj - Sirjan. The aim of the study is to identify areas where the water table is higher in groundwater. To achieve this, an interpolation of (IDW) water level underground of Shaharchay by using the data of piezometeric well, then matching results with the position of faults and available tectonic seismic data. fractures were checked and the role of basin natural characteristics such as slope, lithology, soil type, ages of Geological, precipitation and landuse on groundwater level fluctuations were checked as well. Investigations show 4 different patterns of movement of groundwater in the basin area. Except of fault, other criteria alone are not much of a water table. The results show that the the western part of the water table is located in a very low of zoning, which has very high mountains with high slopes, high rainfall, no fracture Quaternary and pasture. Eastern part of the basin is located in the area of medium and high underground water level only a part of the shores of Urmia Lake in this zoning has a very high water table. With very little gradient, local average precipitation, high permeability, active Quaternary faults, the garden and the city landuse. But the center of the basin zoning was very high with very low permeability, high slope, average precipitation and mixture of garden, forest and grassland usages. basin center located on high seismic intensity zone and density Quaternary faults. only because of the high level in the basin center of Silvaneh are active faults and a high intensity tectonic seismic.

The purpose of this research is the simulation of the maize function to scenario of climate change to the present and future. So to survey the region climate, daily data, maximum and minimum temperature, precipitation and radiation have been utilized during the period of (1987-2016). In order to simulating of climate in future, firstly the date of IPCM4 model under scenario and 30’s and 50’s with downscaling LARS-WG model. Before the simulation yield of maize, APSIM model was evaluated and validated. To calculate the maize yield the output of LARS model, plant date and were utilized as the cropping input model of APSIM. By variance analysis maize yield was compared in present and future. The results showed that the APSIM model validation can simulate acceptable accuracy and climate parameters change effect on the yield rate of maize. And on the basis of the highest yield in Fasa the lowest in the city Abade in base line. In future under different scenarios of climate change, maze grain yield in Fars province except Abade, other cities are decreasing than base line.

According to its historical background, natural conditions and political geography, Caucasus is made up of a variety of races, followers and cultures of different rituals and religions. Historical links of Caucasus residents with Iranian civilization and culture resulted in their adherence to Iranian governments in equilibrium with Roman, Ottoman and Russian policies. Following the collapse of Safavids, which was simultaneous s’ with Tsarist Russia being at the height of its power and hundred years an away from the wars of iran & Russia. Political instability of Iran, continual installation and downfall of several governments’ absence, of power in the region, insecurity and internal pressures as well as foreign interventions, all and all paved the ground for the separation of Caucasus from Iran.

The attempt to recognize phenomena and affairs has always been a concern of the human mind and has constantly sought to complete this knowledge. The correct recognition is also achieved when the real nature of phenomena is clear to man. The phenomena are based on their own philosophical foundations and, therefore, their understanding requires perception these philosophical foundations and using proper methods of recognition. The map is also a phenomenon that has its own philosophical foundations and by understanding these philosophical foundations, the true meaning and the components that influence its meaning are clarified. Recognizing it correctly requires understanding many of the elements and other factors. To real understanding this phenomenon, one needs to understand beyond what is usually said about it. In this research, we tried to clarify the philosophical foundations of the map and the factors influencing its meaning by using of hermeneutical methodology. The results of this research showed that the map of the ontology aspect is of an objective-subjective nature. Therefore, it should be understood by methodology such as hermeneutics and not explanation. Also, using this method, it is determined that the mapping factors are divided into two categories. Internal factors, such as the choice of the type of projection and cartographic deviations and external factors such as, the mental purpose of the cartographer and the banners, understand map reader from map, and the spaces of thought, power, and so on make up the actual meaning of the map.

Air pollution is one of the most important natural hazards in cities that is one of the priorities of climate research. In this research, synoptic situation of days polluted by ozone in Tehran have been studied and by environmental to circulation approach and cluster analysis. At first, was formed a matrix in 2417*41. Rows are indicated days and columns represent the number of stations. by cluster analysis and Ward method eight different clusters were identified. The results showed that the frequency of the ozone days have a seasonal trend and more can be seen in the first half of year in these cases the establishment subtropical high pressure in Iran. Therefore, cause the persistency of pollution in Tehran.

Due to the complexity of air pollution action, artificial intelligence models specifically, neural networks are utilized to simulate air pollution. So far, numerous artificial neural network models have been used to estimate the concentration of atmospheric PMs. These models have had different accuracies that scholars are constantly exceed their efficiency using numerous parameters. The current research aims to compare Elman and Jordan recurrent networks for error distribution and validation to estimate atmospheric particular matters concentration in Ahvaz city. The used parameters are relative humidity, air pressure, and temperature and aerosol optical depth. The latter one is extracted from MODIS sensor images and air pollution monitoring stations. The results show that Jordan model with RMSE of 219.9 milligram per cubic meter has more accuracy rather than Elman model with RMSE of 228.5. The value of R2 index that shows the linear relation between the estimated from the model and observed values for Jordan is equal to 0.5 that implies 50% estimation accuracy. The value is because of MODIS spatial resolution, inadequacy in numbers as well as spatial distribution of meteorological station inside the study area. According to the results of the current research, it seems that air pollution monitoring stations have to increase in terms of numbers and suitable spatial distribution. Also, other ancillary data like volunteer geographic air pollution data entry using mobile connected cheap sensors as portable stations may be used to implement more accurate simulation for air pollution.

Urbanization bubble is a new concept in urban planning issues for examining sustainability at various levels of social, economic, environmental, and management. So far, no common definition provided for urbanization bubble that indicate a lack of research in this field. This research aimed at assessing futures studies of urbanization bubble in Tehran metropolitan with focus on scenario planning. Research method in term of purpose is applied and in term of method is exploratory descriptive analytic one. Required data gathered through field study and document review. In field studies, Delphi technique performed in the form of a group of 30 people. For data analyzing, cross impact analyzes used in MICMAC software. Results indicate that 56 factors identified as key factors in five institutional, managerial, economic, social and environmental dimensions affecting future condition of urbanization bubble. Then, based on experts’ comments, 25 agents identified. Dispersion of the variables indicates the instability of Tehran's metropolitan system. Five categories of influential, dual, regulatory, influential and independent factors identified. Final scores and ranking of key factors carried out and finally, three scenarios presented for the future status of urbanization bubble in Tehran metropolitan.

In this study, precipitation simulated annual and seasonal in East and North-East of Iran, in 1987-2011, by using RegCM4 dynamic model in two case; with and without using post-processing technique. The required data for RegCM4 model with NetCDf format, received from ICTP center. For the implementation of the main dynamic model, Convective precipitation test scheme and the horizontal resolution, performed for 2007. According to the test, Kuo Schema had less error than Emmanuel and Gurl schemes in Precipitation and region temperature modeling. Horizontal resolution selected 30 Km. After model implementation with Gurl schema and 30 Km horizontal resolution, Precipitation and temperature output post- processed using MA model. According to results, in the study area, during 2006-2011 verification period, average annual rainfall raw bias of RegCM4 model was calculated and post-processed equal to 8.3 millimeter and 61.04 respectively. Briefly in the annual time scale, in 75% of studied stations, post-processing is effective and MA model is more efficient. In seasonal scale, bias error of average precipitation is equal to 54.99 millimeter in the winter, 27011 millimeters in the spring, -3.6 millimeter in the summer and 7.21 millimeter in the fall. Simulation of the temperature data in the stations using RegCM4 and MA model in north-east of Iran, revealed high performance. Bias error of average temperature is equal to -2.78 for RegCM4 model and post-processed equal to -0.05. In all stations, modeled Annual temperature and observational data has difference less than 0/1 ° C. In seasonal scale, the mean bias error range according ° C is equal to -4.1 in the winter, -4.09 in the spring, -1.8 in the summer and -1.5 in the fall.

In recent years, the severe fluctuations in precipitation have affected various parts of the country. On the southern coasts of the Caspian Sea, precipitation as one of the important climatic parameters has undergone changes due to global climate change. In the present study, we tried to evaluate the effect of climate change on rainfall in this region by applying a suitable model. In this study, observational period rainfall (1961-2001) was analyzed. the output of the HadCM3 model was used. At first, seven synoptic stations were selected and their data were analyzed in terms of accuracy, and length of statistical period, and lost data was restored. The AOGCM data were simulated using the SDSM model and the rainfall values were simulated for the observation period. After confirming the matching of the simulated data with observational data, the values of the Future (2039-2011) is estimated. The estimation errors of the SDSM model were calculated monthly by MBE and MAE criteria, and then compared. The output of the SDSM model was used to study the total annual precipitation in days with rainfall of more than 1 mm in the observation period and the upcoming period (2011-2039) by the R-Climdex model and the values of the PRCPTOT index Became zoning in the Future. The results showed that the model error in season with high rainfall is more than seasons with low rainfall. On a monthly scale, the maximum error occurred in the months of September, October, November and December. The maximum error in the fall and the minimum error was calculated in the spring and April and May months. According to the results, the total annual rainfall in the period of 2039-2011 will decrease in Anzali, Babolsar, Gorgan and Noshahr stations and rainfall will increase in stations of Astara, Ramsar and Rasht. Geographical distribution of selected were 5 sites in the Khuzestan, 20 sites in Bushehr, 24 sites in Hormozghan and 12 sites in Sistan and Baluchistan provinces. In total, 9000 sites were selected with a 2 km2 were suitable for large scale microalgae cultivation. The total area of these sites were estimated to be 18000 km2. The highest number of proper sites were found in Hormozghan province and lowest numbers of sites were found in Khuzestan province. The availability of technical service, carbon dioxide point resources from oil and gas units are an advantages for microalgae related activities in the Bushehr and Khuzestan provinces. The higher quality of water in the Sistan and Baluchistan province is an advantages for development of microalgae biomass production in the area.

Providing enough microalgae biomass is required for various applications in sectors such as food, medicine and energy. The biomass resources such as land, water, nutrient and carbon dioxide are essential in cultivation feasibility study for biomass production as well as cost benefits. The aims of this research is therefore, site assessment and prioritization of potential site locations, carbon dioxide and water requirement for microalgae biomass production in the Persian Gulf and Oman Sea coastal areas. This analysis was undertaken to provide a preliminary assessment of the demands that may be expected on land, water, and CO2 resources in the Persian Gulf and Oman Sea coastal areas required for the large volume of biomass feedstock production by autotrophic microalgae. Emphasize was placed on the finding proper sites to achieve higher biomass productivity. The areas were selected to provide examples where geographical differences in water evaporation and solar resources, land availability profiles, water demand profiles and stationary CO2 sources would be possible alternatives for large scale production.

Thunderstorms are major climatic events due to the significant effects and catastrophic consequences on humans and the natural environment. The researches have shown that the elevation and latitude factors are two variables that can affect the occurrence of this phenomenon. Therefore, the main aim of this study is to investigate the spatial analysis of the effects of lightning and its effects on the components such as elevation and geographic extent in Iran. Apart from this fact, firstly, the monthly data of thunderstorms occurrence in 118 synoptic stations of Iran, from 1991 to 2010 on a basis from the country's meteorological organization were obtained and GIS software was produced by the annual and seasonal maps of Iran. Then, for the spatial analysis of this climatic phenomenon, the method of landing statistics of the Kriging (Universal) method was to examine its seasonal and annual status. In order to better understand the effect of Thunder hurricanes from altitude and latitude using Curve Expert software, seasonal and annual charts, along with the correlation of each production, were analyzed. The results show that the highest annual thunderstorms occur in the northwest of Iran, and the least amount is consistent with the central and eastern parts of the country. In addition, according to seasonal analysis, although the station has the highest rate at 800 to 1, 300 meters, the maximum occurrence of this phenomenon varies from 0 to 2200 meters in different seasons of the stations. The overall result shows that the factor of height is slightly correlated with the occurrence of the Thunder storm phenomenon and the highest correlation is due to the latitude factor.