JOURNAL OF GEOGRAPHICAL SCIENCES
Year:2018 | Volume:18 | Issue:48 |Papers Count:15

Wheat is the main focus of the economy of Kurdistan province in which the annual fluctuation of wheat yield is 4/11 times as affected by the climatic elements of the site. This study investigated the role of agro-climatic variables and indices on rainfed wheat yield in Kurdistan province. The data of planting area, amount of production, damages and yield of wheat of 31-year in 10 regions of Kurdistan along with the hourly, daily, decade, monthly, seasonal and yearly levels data of 22 synoptic stations were collected. The correlation between wheat yield and 128 independent variables was calculated. The effect of variables on yield evaluated by multivariate regression. The spatial analysis of variables was performed and the spatial model of wheat yield was introduced for province and regions. The results showed that climatic elements in various regions are different, in a 99% confidence. Most of the independent variables alone have a significant effect on wheat yield, but in the stepwise model, 7 variables such as: the number of rainy days of the year, the sum of the degree hours (of temperature less than -11 ° C) in germination and tilling stage, annual precipitation and the precipitation of November are determinants of the yield. Yield and effective independent variables have significant spatial differences even in a cluster climate type. The highest and lowest coefficient of variation of wheat yield is related to Bijar and Kamyaran areas, respectively. Kamyaran and Sanandaj regions have the highest and lowest yield, respectively. Bijar is the highest risk region of the province for wheat production.The results of this study showed that with a 99 percent confidence, climatic elements (variables) vary in different regions. Most of the independent variables have a significant effect on wheat yield in simple linear regression, but in Stepwise method, due to the internal correlation between variables, just variables entered that have insignificant correlation with each other and have more effects than other variables. The variables affecting the performance are differentin various regions, and from the point of view of effectiveness, the arrangement of the variables in different areas vary too. In other words, even in two regions with a climatic type (based on the Modified De Martonne method), both agro-climatic indices and wheat yield are significantly different. The impact of effective variables on yield at any time and place depends on the time of year and the phonological stage of wheat. At one time the environmental conditions of different regions in terms of temperature, humidity and precipitation differ, based on phonological stages of the regions. The time of the vulnerability of wheat varies from place to place. Wheat vulnerability at flowering stage is more than other stages. The effect of independent variables on yield at different times of year is proportional to the phonological stage in years Different and different in different regions. In Kurdistan province, the number of rainy days of the year, total degree hours the temperature reaches below -11 °C (sum of hours with below -11 °C temperature) from germination to tillering stage, the annual precipitation, the rainfall in the fifth decade of the water year (the precipitation of 11-20 of November), annual relative humidity and total degree hours the temperature reaches above 30°Ctemperature (sum of hours with above 30 °C temperature) in milky and dough stage is the determinants of the production of rainfed wheat. In Baneh and Marivan areas, the coefficient of variation (CV) is lower and in Bijar and Divandareh regions CV is more than other regions. Kamyaran region has the highest yield, Baneh and Marivan were ranked secondjointly. Sanandaj and then Bijarhave the lowest yield. Each region has a model for wheat yield and determinant factors vary from region to region. Although the annual production of Bijar is higher than other areas, wheat production in the Bijar region has a higher risk than other areas.

In the current disorderly world, securing benefits and achieving optimal security for countries alone is very difficult and unavoidable. Uniting with other countries and powers is a way to advance national goals and provide benefits, and bring more guarantees for countries to survive, advance, develop and peace. The factors and conditions that lead to the unification of the countries have been a lot of controversy and debate and have been analyzed from a variety of perspectives. Although geographic proximity and geographical similarity seem to be the prelude to creating unity between countries, the Iranian-Iraqi model in the Middle East is challenging this claim. Except for a few days in the early 20th century, the two countries were in conflict with the majority of the century, even an eight-year-old war between them. So the main question of this research is how geopolitical factors contribute to the unification of countries, and what are these factors and components in the strategic relationship between Iran and Iraq? This research is descriptive and based on library and document data. The results of the study show that the components of the internal environment (economic, socio-cultural components, geographic and political components, security and geopolitics), the regional external environment and, ultimately, the global environment have affected the quality and quantity of the strategic linkage of Baghdad-Tehran. The strategic link between the two countries is a function of the accompaniment and positive function of the triangle, which itself is based on more complex components.

This study was performed to evaluate the extent of leaf area in Iran from (2002) to (2016) using Remote sensing. For this purpose, we extracted data collection and leaf area index for the Iranian territory from MODIS website. The database was established with programming in MATLAB software to perform mathematical and Statistical calculations repeated. After the analysis of the data in this software a monthly average long-term map was developed. The maps show that the central, East and South-East are almost empty of leaf area or seen very sparse in some areas. In contrast areas of leaves in the northern and western parts of Iran, are good, which generally includes fields, except forest Arasbaran and Hirkany. Precipitation and the temperature, is the main factors for the growth and development of plants, that these two conditions are enumerated in the west due to being on the way of westerly winds. Lowest leaf area index is for January and February and the highest average of leaf area is for May and June. Next, study of 15 years of leaf area index data by cluster analysis based on the calculation of Euclidean distance and Ward method, showed that all 12 months fit in the two main groups and, in fact, divided for two periods of strong and weak vegetation. In this analysis, , April during the cold period and October in the warm period of the year as the transition months and they are located on a separate cluster.

The present research about the spatial changes of precipitation is mainly focused on western areas of Iran. Precipitation data for three seasons of fall, winter, and spring have been obtained from Esafzari Database, with 15*15 km spatial resolution in the form of a Lambert Cone Image System for the period from 1986 to 2015. To examine the prevailing pattern of precipitation in west of Iran, we have used geostatistical methods of spatial autocorrelation. The changes in precipitation trends have been analyzed using parametric and non-parametric analyses of regression and Mann Kendal. We have used MATLAB for analysis of the data. We have also used ArcGIS and Surfer for drawing maps. The results of inter-decade changes of positive spatial autocorrelation of precipitation in west of Iran have indicated that there has been a decline in spatial extent of the positive spatial autocorrelation pattern in spring and fall, except for winter with a negligible increasing trend. Nevertheless, except for the second period, no considerable spatial changes were observed in the spatial pattern of precipitation in the region. However, there was a decreasing trend in the negative spatial autocorrelation of precipitation in annual and seasonal scales. The results of trend analysis have indicated that there was a decreasing trend in a vast area of the west parts of the country in annual scale and also in winter. Although there was an increasing trend in precipitation in fall and spring, but the trend was not significant in 95 % of confidence interval. The results of Man Kendal test have confirmed the results obtained from linear regression.

Increasing CO2 emissions and consequently, air temperature causes climate anomalies which affects all the aspects of human life. The purpose of this study was to assess the temperature changes and also to predict the extreme temperatures in Gilan and Mazandaran Provinces. To do this, the SDSM statistical and dynamical model was used. As well, it was applied the Mann-Kendal graphical and statistical technique to analyze the temperature changes and its trend. In this regard, the daily temperature was obtained from Rasht, Ramsar and Babolsar synoptic stations during 1961 – 2010, and also the general circulation models data of HadCM3 and NCEP were collected from related databases. The results revealed a significant positive trend in monthly and annual minimum and maximum temperature in all three stations in the first (1961-2010) and third (1961-2040) periods. There is not a significant trend in extreme temperatures in Ramsar and maximum temperature in Rasht in the second period (2011-2040). The Mann-Kendal graphical test was used for the yearly extreme temperatures in all periods. The results showed that it was occurred both increasing trend and suddenly changes or shifts at the 95% confidence level in all stations. It is occurred the highest of changes in monthly and annual of the minimum temperature at forecasted period (2011-2040). It was predicted extreme temperature to increase about 0.1 to 1.7° C. The short time oscillations and significant positive trend occurred in both the maximum and minimum temperature shows the temperature increase and climate changes in the future. Thus it is obvious the decrease in temperature difference in warm and cold seasons.

The current study was conducted to investigate and explain poverty in Saravan village in Rasht city. In this research, survey method and structural equation modeling were used to present a model of based on results of the census in 2011, the number of villages in this district was 7 villages and the number of households was 4283 households. Morgan table was used to determine the sample size of the family heads living in rural areas of Saravan. Finally, 351 questionnaires were selected for family heads, which it was increased to 370 to obtain better results of the questionnaires. The results of a single sample T test indicate that the social and political indices are at good status. However, the T-value of the economic dimension is at the poverty status. The main reason for the poor status of this index is adequate consumption of fruits and vegetables in the household food plan, the inadequacy of housing space for children and the vulnerability of residential against earthquakes and accidents, and the sale of products indirectly through middlemen. It has caused respondents to consider lower scores for this index. According to the findings, the factor load of all items is confirmed in the social, economic and political dimensions.

Landslide, due to its dangerous nature in mountainous areas, usually causes morphology to suddenly collapse and causes major damage to residential areas, roads, agricultural lands, and so on. In this study, using the AHP model and fuzzy logic operators, we evaluated and zoned the landslide sensitivity in the Pseudogene basin in Razavi Khorasan province. The eight main criteria of elevation, slope, tilt direction, distance from the waterway, distance from the road, distance from the fault, geology and land use associated with the occurrence of landslide phenomena were examined in total. The sub-criteria were weighted and fuzzy using the Frequency Ratio Model. The weight of the criteria was also determined using the AHP model. Then the landslide susceptibility map was prepared using fuzzy operators 9 / 0.8 / 0 and 0.7 and verified using the ROC curve. The results showed that the gradient factor had the most effect and land use factor had the least effect on the occurrence of slip in the basin. Validation results of the model showed a 90% accuracy of the landslide sensitivity map with a 0.7% operator in the basin. Therefore, the fuzzy gamma model with the 7th operator provides the best form of landslide susceptibility map in the Pseudogene basin.

This study is aimed at estimating monthly mean air temperature (Ta) using the MODIS Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), latitude, altitude, slope gradient and land use data during 2001-2015. The results showed that despite some spatial similarities between annual spatial patterns of Ta and LST, their variations are significantly different, so that the Ta variation coefficient is four times the one of the LST. Our analysis indicated that while in winter latitude is the key factor in explaining the distribution of the differences LST-Ta, in other seasons the role of slope and vegetation become more prominent. After obtaining the spatial patterns of LST and Ta, we estimated Ta using regression models in spatial resolution of 0.125˚. The lowest estimation error was found in the months of November and December with a high explanatory coefficient (R2) of 70% and a standard error of 1 ° C. On the other hand, the maximum error was obtained from May to August with R2 between 59 to 63% and a standard error of 1.6 ° C which is significant at the 0.05 level. In addition, result of evaluation of individual months showed that estimation of Ta is more accurate at the cold months of the year (November, December, January, February, and March). With considering different land uses, the highest R2 was related to waters and urban areas (96 to 99%) in warm months, and the lowest R2 was for mixed forest and grassland (between 15 and 36%) in cold months.

Landforms and geomorphological processes is the most important factors that affecting dispersion and quality of building materials. Case study, consisting of both new and old alluvial fans is located in the West of the city of Sabzevar. The aim of this study was to investigate the process of freezing and thawing in the durability and quality of materials taken from the alluvial fans old and new. To achieve this goal, we dug four wells in different parts of new and old of fans. The examples of large and small stones from the depths of one meter, two meters, three meters and four, wells were removed. Then to measure resistance of material, against freezing and thawing, freezing and thawing tests were performed on all samples. According to the test on three outcomes for this study was obtained. First: weight loss of samples of the new fans of head is greater, compared with other samples are taken because of the waters. Second, samples of the new fans head because the waters have greater weight loss compared with other samples are taken. Therefore, samples of new fans is fine-grained as possible. Thirdly, if the target is high-quality materials, best materials is made of metamorphic minerals, such as andesite and pyroxene.

Modeling provides the studying of groundwater managers as an efficient method with the lowest cost. The purpose of this study was comparison of the numerical model, neural intelligent and geostatistical in groundwater table changes modeling. The information of Hamedan – Bahar aquifer was studied as one of the most important water sources in Hamedan province. In this study, MODFLOW numerical code in GMS software, artificial neural network (ANN) and neural – fuzzy (CANFIS) method in NeuroSolution software, wavelet-neural method in MATLAB software and geostatistical method in ArcGIS software were used. The results showed that the accuracy of methods in estimation of the groundwater table with the lowest Normal Root Mean Square Error (NRMSE) include Wavelet-ANN, CANFIS, geostatistical, ANN and numerical model, respectively. The NRMSE value in Wavelet-ANN method as optimization method was 0.11 % and in numerical model was 2.2 %. Also the correlation coefficients were 0.998 and 0.904, respectively. So application of neural combination models, specially, wavelet theory in estimated the groundwater table is most suitable than geostatistical and numerical model. Moreover, in the neural intelligent models were applied latitude, longitude and altitude as available variables in input models. The zoning results of groundwater table indicated that the decreased trend of groundwater table was from the west to the east of aquifer which was in line with the hydraulic gradient.

The management of land development in the compilation of urban development documents is a very important topic. Failure to pay attention to this necessity, and the course of physical development foreseen for urban areas, make the main goal of the development plan, which improves the quality of housing in urban areas, not being realized. The purpose of this study is to introduce a functional model for land development management in order to guide and manage the urban development flow. To this end, the Land Readjustment Plan (LR) as the selected method of land management in urban areas is introduced and it is possible to perform it in a range of Yazd city. The general research method used in this descriptive-analytic study. The data used in this article collected by the library method as well as the field survey were used and analyzed using ArcGIS software. In this regard, a proposal for the scope of the study was compiled and evaluated before and after the implementation of the plan. The calculation of the distributional index showed that the proposed scheme would give 20% of the profits to the owners in the scope of the study. The conclusion from this study shows that using the Land Readjustment Program as an economic and design tool, planning and redevelopment of undeveloped lands can be done in accordance with urban needs. This planning involves modifying the layout of parts, modifying the network of roads, supplying services and infrastructure of the facility. Thus, the field of realization of urban development plans in these areas was provided. It also provided the basis for the participation of all stakeholder groups through creating the necessary attractions for the groups influencing the implementation of the project.

Remote sensing technology is one of the most efficient and innovative technologies for agricultural land use/cover mapping. In this regard, the object-based Image Analysis (OBIA) is known as a new method of satellite image processing which integrates spatial and spectral information for satellite image process. This approach make use of spectral, environmental, physical and geometrical characteristics (e.g. texture, shape) together images contexts for modeling of land use/cover classes. The main objective of this study is to classify micro land use/cover of Meyandoab County by applying appropriate and effective algorithms and parameters in the object based approach. For this goal, Quick Bird and Aster satellite images were used within the integrated approach for processing and land use modeling. Accordingly, the land use map was classified in 9 class based on spectral and spatial characteristics. In order to perform OBIA, the segmentation was applied in the scale of 10, shape parameter of 0.7 as well as the compactness of 0.3. In terms of the classification task, fuzzy based algorithm and operators (AND, OR) was applied to detriment the membership functionality of segments for each class as well as classifying the related objects. We also applied textures, geometric, NDVI, GLCM, brightness algorithms based on fuzzy operators and assign class algorithm. In order to applying the validation of results, the accuracy assessment step was performed and the finally overall accuracy of 93.6 was obtained for the derived map. The Kappa coefficient was also detriment to be 0.92. The area under cultivation included respectively for lands of wheat and barley, prunes and plums, apples, vineyards and alfalfa hay2622.42, 4505, 4354.55, 4457.85, 14110.58 hectares.

Study how to relax and leisure from the work of citizens it is located in the field of leisure geography studies. The current study is practical in an aim and descriptive– analytical in method and practical– theoretical in nature. In this study, the first path analysis model was used in order to express logical correlations between environmental and demographics variables, on leisure geography and providing structural analysis.the results of study path analysis model shows that the impacts of the physical environment outside the home with standardized coefficients0.461 into other variables have the greatest impact and demographic variables with standard coefficients 0.025 has least impact on leisure geography of metropolis. In the following, the number of 383 questionnaires was distributed in order to study comparatively the spatial pattern leisure geography among citizen's zones 2, 4 and 7 of the city of Ahvaz that they were at different levels of enjoyment. The results of the questionnaire of citizens indicate that leisure pattern in Region2 is different from other areas; However, the pattern of citizens leisure of district4 and7 has not a significant difference together. In this context, assigning a specific type of planning is approved in order to improve the quality of community health and welfare of the citizens;; with regard to natural and human environment conditions of the city and leisure facilities available.

Livability approach is defined as the healthy, safe, suitable and economically accessible urban system that brings about high life quality and is considered as a subset of sustainable development. Although investigating urban livability can be advantageous in identifying deficiencies and taking actions in order to improve livability of the living environment of residents, but unfortunately there has been inadequate considerations about livability theory in Iran. the result, in this study, the livability of Urumia city has been investigated. Firstly, after devising 24 factors in 4 aspects (Physical-Environmental, Economic, Social and Health) this index was evaluated in urban areas by using newly invented model RALSPI with descriptive-analytical approach. Finally, based on this model, the areas were placed within the range of very livable to intolerable, so that District #1 was determined as the best area with livability score of 0.31 and District #2 was determined as the most unlivable area with the score of 0.007. This issue revealed a huge gap between the areas of the city.