فصلنامه فضای جغرافیایی
پیاپی 63 (پاییز 1397)

Human impact on the environment are increasingly of urban life arises that this is due to human population growth is partly a result of technological progress. Cities as the center of attraction of population with multiple and various environmental problems such as air pollution, noise, waste, and water pollution this leads to increasing pressure on the environment and therefore the incidence of environmental pollution. The study aimed to measure and evaluating the quality of the urban residential environment with cross-sectional approach in urban settlements Ardabil province. To achieve the goal of is evaluated 5 environmental factors (environment, energy, environment, social, cultural, recreational and employment) in the form 30 Index. Rate the importance of each of the variables were determined using the Shannon entropy. Models used to analyze the data is Visual PROMETHEE PROMETHEE and GAIA software. The results show that urban settlements Kosar city with a score of 2,674 / 0 has favorable conditions, Bilesuar, Namin, Sareyn, as well as the privileges 1281/0, 1147/0, 0994/0, 0924/0 has favorable conditions, Meshkin with a score of 0369/0 in relatively good condition, Warmth, anklets and Ardebil with 0704 votes / 0-, 1359 / 0- and 2098 / 0- of adverse conditions And Pars Abad city with 3228 negative rating / -0 in last place and the situation is quite unsatisfactory. Based on the analysis of the 30 indicators used PARSABAD Gaia city status this research indicates that only in the ratio of active branches of sewage into the urban population in the state is ideal. Overall results show that environmental situation in cities far worse that the urban population is more urban counties that have less.

Knowledge of groundwater quality and quantity changes is needed for an appropriate management and optimum utilization of groundwater resources. Many different statistical methods are available for detecting and estimating trends present in water quality parameters. These methods range from the simple correlation and regression analyses to time-series analyses and nonparametric approaches. Analysis of the time series is the most common technique used to detect changes in climate and hydrologic phenomena. Trend analysis can be defined as the use of an experimental approach to determine and explain the changes in a system over a period of time in statistical terms. In nonparametric methods, unlike parametric approaches, fewer assumptions about the data frequency distribution (e.g. normality of the data distribution) need to be made. Besides, the knowledge about spatial distribution pattern of groundwater quality is required for a sustainable and appropriate groundwater management. The nonparametric tests of Mann-Kendall (MK) and Spearman’s rho (SR) are commonly used to evaluate the trend of changes in climate and hydrology data. The aim of this study is to use Mann-Kendall and Spearman methods for investigating the changes in groundwater quality in Khash region during 2004-2013, according to the data of 17 stations. The slope of the trend line for all variables is calculated using Sen's estimator. Moreover, ordinary kriging is used to predict the spatial distribution pattern of groundwater quality parameters. Matherials and Methods: The study area is Khash region located in Sistan and Baluchestan Province. The study area is located between 61-00 to 61-45 latitudes and 27-45 to 28-40 longitudes. Groundwater quality parameters studied include acidity (pH), electrical conductivity (EC), sodium (Na+), sodium percentage (Na%), sodium adsorption ratio (SAR), sulfate (SO42-), the bicarbonate ion (HCO3-), chlorine (Cl-) , magnesium (Mg2+), calcium (Ca2+), potassium (K+), total cations, total anions, total hardness (TH) and dissolved solids (TDS). The data were collected from 17 stations during 1383-1392. The Spearman's rho, Mann-Kendall and Sen's estimator tests were used for detecting trend in quality parameters of groundwater. A brief representation of the methods used is provided as following: In this study Mann-Kendall (MK) and Spearman’s rho (SR) tests are used to analysis the trend of changes in groundwater quality data over Khash plain. The slopes of the trend lines can be estimated by using a simple non- parametric procedure called the sen’s slope estimator. To better investigate the groundwater quality changes over 2004 to 2013 across the whole area, the spatial distribution patterns of quality parameters are mapped using ordinary kriging (OK) interpolation method. OK estimator estimates the unknown values of a groundwater quality parameter through a linear weighted moving average of surrounding data values. Discussion of Results: In this study, the annual changes in groundwater quality in Khash region during the period 2004-2013 with the Mann-Kendall and Spearman nonparametric methods were studied. Sen's estimator slope was used to estimate the slope of the trend line for qualitative variables. The results showed that the majority of water quality variables have positive trend at most stations. The strongest positive trend (Mann-Kendall ’Z=3.93 and Spearman ’Z=3) was seen for EC at station number 4. Based on the results of the Mann-Kendall test, stations numbers 4, 10, 16 and 17 had the most significant positive collections. Also EC, TDS, K+ and Cl- had the most significant collections are among other variables. The results of Spearman method showed that the stations 4, 10, 15 and 16 have more significant positive trends. Ca2+ and SO42- had more negative trends at most stations. The most significant positive trends have seen for EC and TDS, followed by K+, Na%, Cl-, TH and HCO3- in the majority of the stations. According to this method, SO42- tends to decrease in the most of the stations. Sen's estimator results showed that the stations 10, 8, 1, 14, 15 and 16 had more positive slopes. According to these results, EC, TDS, Na%, Na+, SAR, HCO3-, Cl-, pH and total cations have increased in most stations. According to the results of all three methods (Mann-Kendall, Spearman and Sen's estimator), stations 10 and 16 are critical situation. The results of the Mann-Kendall and Spearman showed that EC and TDS have increased at most stations. Also, the slope of these two variables is positive at most stations. The results of all three methods showed that SO42- tends to decrease in the most of stations. According to the maps generated using ordinary kriging, the amounts of %Na, SAR, pH and HCO3- increased from 2005 to 2013. To investigate the factors affecting the quality of groundwater in the area, trend analysis of rainfall was also performed. Mann-Kendall and Sen's estimator test results showed that both stations had negative trends of annual rainfall. The results showed a decrease in rainfall, which reduces the volume of water entering the aquifer. Excessive groundwater withdrawals, population growth and development of industrial life are among the factors decrease the water quality in the study area. Conclusions: The results of this study showed that the Mann-Kendall and Spearman methods have similar performance in detecting stations with degrading water quality. According to the results, EC and TDS tend to increase and SO42- tends to decrease in most stations. Groundwater quality in stations No. 10 and 16 showed the most meaningful positive trends among others. Middle slope of the trend line was positive for 70% of the plotted curves. In general, the results showed a positive trend of groundwater quality parameters in most stations meaning that groundwater quality tends to decrease in this region over time. Low amounts of rainfall, excessive groundwater withdrawal, population growth and development of industrial life are the main factors threaten groundwater quality in the area. To prevent further groundwater quality degradation and protect the water resources for future generation, appropriate management strategies should be considered.

In order to compete in the international arena, cities attempt to enhance their infrastructures to encourage innovation. In all successful and innovative cities, there are three effective levels including creative people, urban organizations (which act as mediator), and national and international companies. In fact, these intermediate organizations play the role of an interconnector between creative people with new ideas and national and international companies (for commercializing new and creative ideas and having economic development). The purpose of this research is to predict the future of Mashhad and propound related scenarios about the relation between the three above-mentioned levels in vision 1404, and finally develop the strategies required for achieving the desirable scenario of innovative city formation in Mashhad. This is a fundamental applied research in terms of purpose and descriptive-analytical (consecutive mixed method) in terms of nature and methodology, which has used scenario-planning in six steps. Data were extracted using questionnaire and semi-structured interview. After analyzing the data, four scenarios were planned, and finally the scenario of the golden city was selected as the desirable scenario and several strategies were suggested for achieving such a scenario.

In this paper the prediction of heat waves have been done using Markov Chain. In order to identify heat waves the max temperature of 1437 stations have been applied. The data covers the period of 1962/1/1 to 2004/12/31. Then these stations have been interpolated on 15 km × 15 km grids and has consisted a matrix in 15695 × 7187. The rows represent days and columns represent the pixels. This index was applied on 15695 and on all the pixels. So a matrix in 15695 × 7187 was consisted. Because the Z above 2 indicates the positive abnormality, this value was chosen as the heat wave. Then the values of P and Q that represent the occurrence and nonoccurrence of heat waves were utilized to predict heat waves over Iran. In general the mean annul distribution of heat waves show that southern parts of the country experience more heat waves than northern parts. The investigation of heat waves in spring with two days of return showed that in many parts of the country the value is 100 days but in regions around Kerman this value is around 2000 days with a significant gradient. The time for the occurrence of heat waves with two days of return in fall is reduced to 50 days in comparison to spring.

Urban management is a comprehensive concept and It aims to strengthen government agencies and And various NGOs to identify programs and policies They are implemented with optimum results and No it is not possible to run a city. But today, Cities, especially in large cities due to the problems of excessive Makes the traditional urban management lose their effectiveness And in this regard, Integrated urban management as a learning management entity and Engaged with the issues and phenomena very broad and diverse cities and urbanization is essential To eventually achieve sustainable development in the city can be attained. Type of this research is descriptive-analytic study. And collect data from field studies and library use. Also for analysis Multi-criteria decision-making models (DEMATEL fuzzy TOPSIS) is used. The findings show that among the main criteria for research, Communication structure with the highest weight factor and direct impact in first place with 19.17 points, Legal terms policymakers with a score (19.11) in second place And eventually attitude with a score (19.00) in third with And these factors are the most important factors in the implementation of integrated urban management in metropolitan Tehran. The following criteria are also based on TOPSIS reflects the fact that Organizational tasks overlap in various organs related to urban management, Weak information infrastructure for integrated urban management and Anonymous integrated approach in the management of different spatial levels First to third positions respectively in terms of experts, business professionals and Have a greater impact on the implementation of integrated urban management in the metropolis.

Evaporation is one of most important parameters which are affected by many variables such as rainfall, wind velocity, sunny hours, and relative humidity etc. Evaporation estimation is important for any area with surface water resources because of its effect on dam lakes, precipitation-runoff modelling, river area performance, water management – calculating amount of water that plants need and planning for watering and so on. Evaporation can have significant effect on water balance of a river or a reservoir and it may be cause water level to decrease. Due to hydraulic system complications caused by statistical information imperfection and determining all parameters involved, complete hydraulic system modelling is impossible. At such circumstances using al mathematical modelling system will be considered. Matherials & Method: In this study we tried to estimate pan evaporation using two models including Artificial Neural Network (ANN) and Support Vector Machine (SVM) with data preprocessing (gamma test and principal component analysis) to determine affective inputs into two models. For this matter data gatherd from three synoptic stations at Astara, Kiashahr and Talesh at Guilan province has been used. Synoptic stations data includes evaporation, wind velocity at two meter altitude, temperature (minimum, average and maximum), humidity (minimum, average and maximum), sunny and rainy hours. Statistical period of data for Astara and Talesh synoptic stations were 1384 to 1393 and for Kiashahr were 1385 to 1393. 80 percent of meteorology data were used for calibration and other 20 percent were used for model validation. In this study we used multilayer perceptron artificial neural network with sigmoid tangent function and 1 to 20 neurons for hidden layer and support vector machine with radial based kernel function. Calculations has been made in to section with two data preprocess methods. At first section input variable has been selected by gamma test and pan evaporation estimation was made by both models. At second section modelling has been pulled out by input variables selected by principal component analysis. Discussion of results: At gamma test section pan evaporation estimation parameters were as follows: minimum temperature, maximum humidity, minimum humidity, rainfall and sunny hours for Astara station; maximum temperature, minimum temperature, minimum humidity, rainfall and sunny hours for Kiashahr station and maximum temperature, minimum temperature, maximum humidity, average humidity, rainfall and sunny hours for Talesh station. According to principal component analysis results on Astara, Kiashahr and Talesh stations, five, five and four principal component were used in modeling these stations respectively. At first section input compound determined by gamma test to estimate Pan evaporation of the selected stations were used. Pan Evaporation estimation results shows that at Astara station GT-ANN model has less root mean square error than GT-SVM model and beter performance. Pan Evaporation estimation at Kiashahr station was done suitably with both models. At this station GT-SVM had a better performance with root mean square error of 1.295 compared to GT-ANN model with 1.356. At Talesh station both models had close results but results for GT-SVM were more accurate compared to GT-ANN. Nash Sutcliffe coefficient attained for Astara and talesh stations acknowledges their excellent results and for Kiashahr station shows the satisfactory results. At second section modelling were done by using selected inputs by PCA preprocess method. Accordint to results, PCA-ANN model had better performance estimating pan evaporation at Astara and talesh stations than PCA-SVM model as its root mean square error was lower. Value of Nash Sutcliffe coefficient shows the suitable performance of both models at both stations. PCA-SVM model had better performance estimation pan evaporation than PCA-ANN with lower root mean square error at Kiashahr station. Nash Sutcliffe coefficient of PCA-SVM model was 0.666 and for PCA-ANN model was 0.634 which shows the satisfactory performance of both models. Conclusions: Results shows the good performance of preprocessing methods (principal component analysis and gamma test). Actually performance of GT-ANN, PCA-ANN, GT-SVM and PCA-SVM models performance estimating pan evaporation of each one of the stations are very close to each other. This similarity is caused by performance of gamma test and principal component analysis preprocessing methods. Principal component analysis converts input variables to independent principal component using linear relation between input variables. Actually this method reduces the effect of the variables with similar information by giving them lower factor. But in gamma test method consider to gamma factor attained from various input compounds, variable that has a negative effect on output will be determined and eliminated from final input compound. As we said before, nature of none linear Gamma and linear PCA methods are different but when PCA method decreases the factor that is eliminated in gamma test to a small value, inputs determined by both methods will be close to each other. This can be one of the reasons that close the estimating models results to each other. So we cannot recommend one preprocessing methods better than the other. We can conclude that for estimating pan evaporation at these stations both preprocessing methods are suitable. According to results PCA-ANN for Astara and Talesh and GT-SVM model for Kiashahr station had better performance than others. Although both models had acceptable performance estimating pan evaporation of stations but SVM model results were better than ANN model.

Shopping is one of the things that has always been of interest to tourists and pilgrims and malls and shopping centers varied tourists and pilgrims from around the world that illustrate the importance of this issue. Mashhad, the second largest religious metropolis in the world, annually receives more than 25 million pilgrims and tourists from around the world, is a market and various shopping centers that can meet the needs of tourists and pilgrims. In this study, the factors affecting the choice of shopping centers by tourists and pilgrims in Mashhad were studied and analyzed. For this purpose, 396 questionnaires were collected using multinomial logit to estimate these factors were discussed. Shopping in Mashhad them into three groups based on their geographic location. The first group more frequently than other groups, including: Markets around the holly shrine, Reza market, central market, Ferdowsi market and 17 Shahrivar that Geographical position is around the shrine. The second group includes Janet, Zist khavar, Proma, Alton, and the third group includes Almas shargh, Kian center, Padidieh hypermarket and Torghabeh bazar. The results showed that the variables of income, education and transport index (below average) have a significant positive impact on the tourists in the second group than the first group and variables of survival, province, family members, transportation (personal means) and transportation (less than average) have positive and significant impact and variables of job, cost effectiveness (more than average) and infrastructure (below average) have a significant negative impact on the tourists in the third group compared with the first group.

Nowadays, groundwater contamination is considered as one of the most important environmental issues. Because of its land use diversity, the Piranshahr Watershed (23385 ha) in East Azarbaijan Province was chosen as the study area for this research. Water quality samples were collected from 145 wells across the watershed. After variogram analyses and determination of spatial variations of the water quality parameters, different interpolation methods were applied to map the spatial distribution of the parameters. The methods with lowest RMSE were selected as the best interpolators. The results showed that, for pH, Ca, Mg and TH, radial-basis functions; for Na, inverse distance weighting (IDW); for TDS, exponential kriging; and for No3, ordinary kriging have the lowest RMSE values. The resulting maps indicated that, all parameters except Na and TH, have no limitation for drinking purpose. Spatial distribution of nitrate in groundwater indicated that highest concentrations of nitrate occur in the areas with high permeability and barren and agriculture land uses (east and south of the watershed). Results showed that water quality in the region has a degrading trend that is due to overexploitation of water for agriculture uses.

Introduction: Evaluation of Uvala as one of the typical karstic landforms is important in environmental management. Compared with other karstic holes such as doline and polje that have perennially been studied, uvalas have been less investigated, or have been addressed enigmatically. The Uvala is a combination of some dolines and in terms of size and dimension is larger than doline and smaller than polje. Distinguishing uvala from other karstic sinkholes should not based on one or two factors, but usage of various parameters such as topography, structural conditions, active tectonics, morphoclimatic heritage, present hydrology and geomorphological features should be considered. In this research, with the help of studying the various factors such as topography, lithology, active tectonics, hydrological processes, environmental activities, and geomorphological parameters affective in kastification (i.e. weathering), it has been tried to study the formation and development of uvala as a surface karstic. The aim of this research is to analyze the morphometry of uvala and to recognize this surface karstic feature. Some field observations were carried out for gathering some quantitative parameters of holes. Materials and methods: Topographic data of study area were extracted from 1:25,000 topographic maps and geological data derived from 1:100,000 geological maps. In this study, based on field observations, topographic maps, Digital Elevation Model, quantitative and statistical methods, 23 Uvalas were identified in Parav-Biston block. Also aerial photographs, satellite imagery and Google Earth software were used for exact delineation of holes border. In order to extract morphometric characteristics of holes, and to identify and distinguish uvalas, 20 meters Digital Elevation Models were used. Morphometric parameters calculated in this study include perimeter, area, depth, volume, main orientation, elongation ratio, sinuosity, ratio of section area and Pitting index. Statistical correlations between variables were used in order to find the relations between quantitative parameters of Uvala metrics and the affective factors on the formations and development of Uvalas in Parav-Biston block. Results and discussion: Result of this study reveals that all studied uvalas are developed in elevations higher than 2000 m asl. and most uvalas are located in elevations between 2600 and 3000 m asl. About 74 percent of uvalas have topographic gradient of 0 to 2 percent, and there is no any uvala in gradients higher than 14%. This demonstrates that the probability of Uvala formation in low gradient slopes is higher than steep slopes. Evaluation of regression analysis between parameters reveals that the pitting index is inversely correlated to uvala area so that pitting index decreases as the uvala area increases. There is also inverse relationship between uvala volume and pitting index as well as between uvala depth and pitting index. The uvala volume is positively correlated to area and depth. The assessment of relation between uvala elongation ratio and maximum diameter of uvala reveals that elongation ratio increases as maximum diameter increases. Results show that 86% of uvala orientation is parallel to overall trend of faults. In contrast to Polje, the bottom of all uvalas is pitted and a little sedimentation takes place in uvalas bed. 95 percent of uvalas are developed in Biston Limeston. Results show that lithology has an important effect on the formation and development of uvalas. In study area, extension and favorable condition of Bisetun Massive Limestone has resulted in the development of 95% of Uvalas in this unit. Analyzing the rose diagram of 200 main faults and fractures in Parav-Biston block reveals that main elongation of most uvalas is parallel to main faults of study area. Conclusions: Various karstic features especially uvala have been developed in calcareous lithology and under the profound effect of tectonic in Parav-Biston block. Result of this study shows that most of uvalas have elongated parallel to main faults of Zagros. This implies that uvala differs in origin from other karstic features such as polje that are often originated from dissolution activity and also from sedimentation in the surface karst. The bad pitting is characteristic of uvala and this is its main difference with polje. In deeper uvalas, the value of pitting index is lower, implying the smoother bed of uvala. This can be due the development of underground drainages in deep uvalas. Evaluation of uvala shape indicates the tectonic controls on the formation and development of this feature in Parav-Biston block.

Dalahoo mass located in Folded Zagros structural unit. The purpose of this investigation is mapping the surface karst development is in the Zagros folded. Nine elements of lithology, faults, elevation, rainfall, temperature, use land (vegetation), slope and aspect as independent variables in the process of karst formation and development and also geomorphology karst formation are involved in the study area. Mapping of surface karst development and the effects of different factors in permeability formations, Is necessary. The fuzzy logic model (gamma function) In order to achieve this goal, is used. Based on the results, Dalahoo mass in terms of zoning surface karst development were divided four four non Karst region, Karst with the development of low, medium developed and developed regions. Evaluation zoning map with sinkholes and karst Polje, showed high precision and high efficiency of this model to evaluate the development of karst surface.

Introduction: Developing tourism in the areas that have the required capabilities can be a useful way for the host communities to comprehensively grow and develop. Attractions are necessary but insufficient elements to develop tourism in an area since developing tourism requires accurate identification of the area and providing services to tourists. More importantly, lack of careful planning to recognize the appropriate tourism may lead to undesirable consequences for the environment. Currently, most countries in the world are competing to take more advantages of their capabilities and obtain a larger share of revenue from tourism. However, unlike having a variety of attractions, the cities in Iran have so far failed to make use of this advantage well. Gorgan city with plains in north and mountains in south has special natural and tourism features so that there is a temperate climate and many water resources that can create an area rich in ecotourism attractions. In this regard, this paper aims at evaluating the ecological capability in order to organize sustainable ecotourism by using MCE in Gorgan city, contributing to planning and managing tourism in this area to maximize positive capabilities and minimize the negative ones. Materials and Methods: This paper is going to evaluating the ecological indices to organize sustainable ecotourism in Gorgan by using MCE (Multi Criteria Evaluation). Since identifying and evaluating tourism capabilities is a multi-criteria decision- making issue, this study uses fuzzy multi-criteria decision-making model and WLC method (Weighted Linear Combination) in GIS environment. This paper is an applied-developmental study and the methodology used in this study is analytical-descriptive. The collecting data tool is library research method (using articles, reports, and other written available documents), interview, and case-studies. Discussion of Results: This paper studied 31 sub-criteria under 6 main criteria. The criteria used in this paper include continuous and discrete data whose standardization and weighting vary in the nature and value attributes of each criterion. At this point, the data layers developed to be used in fuzzy analysis were converted to appropriate formats of IDRISI 17 and ARC GIS10.1. Moreover, we used fuzzy logic for combing layers and determining the degree of membership fuzzy logic. Each layer in fuzzy logic is between 0 and 1 (0 < μ(x) <1) (Lin, 1996). Regarding this fact that it is possible to show the values between 0-255 in computer systems, we may show them between 0- 255 rather than 0- 1. At this scale, larger numbers have more utility. That is, the closer are values to 255, the more utility they will have. Creating layers and fuzzy sets in terms of their nature and types of applications, we used different functions and finally standardized each spatial layer. Standardizing and weighting the criteria, WLC method was used to do phase modulation and overlapping operations, and the final maps were extracted. Generally, the Weighted Linear Combination (WLC) was used based on the following relation: S= ∑ i=1 to nWiXi∏Ci Conclusions: According to the evaluations in the studied area, the results indicate that the identified areas on the map as appropriate areas for the development of sustainable ecotourism are more located in the southern and central parts of the area. The northern parts that are mostly plains are not much potential in terms of sustainable ecotourism development. The results show that 129.8 km2 (8%), 355.52 km2 (22%), 371.68 km2 (23%), 533.28 km2 (33%), 226.24 km2 (14%) of the total 1616 km2 of the Gorgan city have very weak, weak, average, high, and very high capabilities for ecotourism development, respectively. the regions with high density of vegetation and water resources good climate (southern and central parts) have the most capabilities for ecotourism activities. Analyzing the utility map, the northern regions are not potential for ecotourism development.

Introduction: Special and sensitive place of plants as the basis of ecosystems and role of them in moderating hazards such as floods, erosion and pollution of water resources make us to understand the environmental variables affecting the growth and development of vegetation cover. In light of this understanding and maintaining the interweaving relations between environmental variables and vegetation cover, we will be able to maintain and support the live coverage of vegetation. In this context, geomorphic variables as special appearance of other environmental elements and factors have closely related to vegetation cover in mountainous catchments. Awareness of the role of geomorphic variables in distribution of vegetation cover requires analysis the spatial relationships and scientifically accurate spatial modeling. In this regard, the emergence and development of remote sensing (RS) and Geographic Information System (GIS) and access to digital maps of geomorphic variables have provided the development and implementation of predictive models in investiagting the spatial variations of vegetation cover. This study aimed to assess and determine the spatial geomorphic-vegetation relationships using the pixel-based spatial approach in Arasbaran catchments (3 catchments: Naposhtehchhay, Ilginehchay and Mardanqumchay). Arasbaran mountainous catchments, NW Iran, include worthwhile forest and range ecosystems maintaining the great storage of biodiversity and particular uncommon species. Materials and Methods: Our approach is based on spatial multiple regression analysis between geomorphological parameters and abundance of vegetation cover. In this regard, 27 geomorphomety parameters as independent variables and NDVI as the dependent variable were computed from Landsat imagery (ETM sensor) and SRTM digital elevation model (DEM). First, preprocessing operations including atmospheric correction (noise reduction) and geometric correction was performed on the sattellite image. DEM is preprocessed by removal of sinks in GIS environment. After radiometric and geometric corrections, raster layers of geomorphic parameters computed and prepared using GIS and SAGA softwares and NDVI layer computed using IDRISI software. It is necessary to normalize the scale of data (-1 - +1) because of various scales of the variables using the following formula: Xnormalize= x- x(min)/x(max) - x(min) In the formula, x: raw value of the variable; min (x): minimum of the variable; max (x): maximum of the variable. We use the SAGA for performing the multiple regression (stepwise method) with 0/01 signisicance level. Results and Discussion: Preliminary results of the regression analysis showed that many of geomorphological parameters had significant relations with vegetation cover in spite of low correlation coefficients. Independent variables that positively correlated to the dependent variable were as follows: slope, transformed aspect, slope position, earth surface convexity, plan curvature, profile curvature, convergence index, flow path length, flow accumulation, Melton ruggedness number. Independent variables were negatively correlated to the dependent variable were as follows: valley depth, elevation, topography position index, slope length, flow width. The results of rgression steps indicated that 8 parameters including valley depth, topography position index, elevation, slope, slope position, transformed aspect, earth surface convexity and general curvature were the most important inependent variables explained most of variance of the dependent variable. Final results of regression analysis showed that the best linear regression model abtained in Mardanqumchay catchment with 0/32 R2 value. In contrast, the weakest regression model is abtained in Naposhtehcay with 0/11 R2 value. It appears that Ilghinehcay catchment have moderate phytogeomorphic conditions having rgression model with 0/21 R2 value. It is found that there is a correspondence between ruggedness of catchments and prediction power and efficiency of the regression models. Conclusion: This study attempts to analyze the relationships between geomorphology and vegetation cover using a geographic information system (GIS) and remote sensing (RS) approach in Arasbaran catchments, NW Iran. Identification of the most important independent geomorphic variables and comparison of the regression models in order to select the best regression model provided from the spatial regression analysis. Geomorphic parameters including valley depth, topography position index, elevation, slope, slope position, transformed aspect, earth surface convexity and general curvature valley are the most effective independent variables for explaining the spatial variations of vegetation cover abundance. The selected geomorphic variables, in the Whole, are enough reflection of geomorphology of a site, having not only the relation between form and process in them, being the special representative of other environmental factors. Comparison of the ruggedness of catchments with prediction power and efficiency of the regression models is interesting result of the research stressed the close and interweaved relationships between geomorphology and vegetation cover in the study area. Overall, although significant portion of the spatial variations of the vegetation cover abundance could not be explained by final regression models, but the predictive models can discover and determine important variables that affect the spatial patterns of vegetation cover and processes underlined in the patterns, leading to inhance understanding the geomorphic-vegetation relationships, considering the comprehensive spatial approach in regression analysis in one hand and complex non-linear relationships between vegetation cover and geomorphology in other hand.

To doing this research, daily precipitation data from 188 synoptic, climatology and rain gauges stations in and out of Kurdistan province during 21/3/1961 to 19/1/2011 have been used. Daily precipitation interpolated on 6*6 km pixels by Kriging spatial statistic over Kurdistan province. One matrix with dimension 18203*811 has been created that located time (days) on the rows and column were pixels. For each pixels total monthly precipitation has been calculated. Data of ten teleconnection patterns extracted from NCEP/NCAR. Linear regression has been used to detection correlation between precipitation and teleconnection patterns. The correlation tested in 95% confidence level. The results showed that correlation between precipitation and teleconnection patterns is significant in 95% confidence level. The extent and intensity of significant correlation go to head in autumn season. The impact of South Oscillation Index (SOI), North Sea Caspian Pattern (NCP) and East Atlantic and West Russia (EAWR) is high in autumn. In cold seasons, SOI has negative correlation while NCP and EAWR have positive correlation with precipitation. In warm seasons two recent indices have negative correlation with precipitation. In total, increase sea level pressure and geopotential height in 500 hPa over Western European parts and decrease over eastern Mediterranean, Caspian Sea and north Caspian result in increase precipitation in Kurdistan province during cold seasons. In contrast, increase sea level pressure and geopotential height in 500 hPa over northern part of Caspian Sea result in increase precipitation during warm seasons.

Nowadays the discussion on Physical- Spatial Expansion of cities is one of the problems of developing countries, especially Iran. The growth causes and pattern of a city is the most critical matters of the recent century. So, recognition of spatial growth causes and pattern of main cities of regions and countries such as Abdanan City is necessary for drawing up suitable policies and achieving sustainable development. In this regard, in the framework of sustainable development and urban smart growth theories, the causes and quality of spatial growth pattern of Abdanan City were evaluated in the framework of the analytical-descriptive research method. In this framework, for analyzing the population and employment distribution used Gini and Entropy's indexes. For analyzing the development pattern we used Moran and General G indexes, and Holdren model and Shanon Entropy's. The necessary data was collect by librarian method. The necessary data was collect by librarian method. The results showed that there are imbalance in population and employment distribution. The results also showed that the Abdanan City have had a random development pattern tending to Clustered pattern by forming a hot spot in its south part and a cold spot in its north part and because of low density, the results indicated in the ascendancy of the dispersed pattern. The results showed that Abdanan City despite dispersed growth in most periods, during 1385-1390, have had a sprawl growth of 97 percent and less than 3 percent of that is because of population growth and the real needs of the land. Finally, the results showed that management and economical parameters have high role in growth pattern of Abdanan city.

Sedimentation of landslides is a new threat to the watershed, whose analysis and evaluation of the necessity and importance of sustainable development is sustainable. The purpose of this study is to analyze the indicators of landslide affecting sediment load in the watershed. Assuming that the linear relationship between the landslide indexes is dominant over sediment load of the basin. Flood dewatering data of flowering mud and sub-basin of Chaviz were analyzed in two observational and annual methods using the deposition curve of the middle classes during the statistical period. The active lake landslides were analyzed using spatial correlation model of Moran, and this spatial analysis showed that landslides have cluster patterns and spatial correlation is effective on the indices of landslide and sediment load in the basin. The results showed that the cluster pattern of landslides was marl lithology of the Gourpi Formation and the best model was Moran spatial autocorrelation. The correlation in one and two-variable regression shows a linear relationship between the indices of landslide influence on sediment load of the basin, but the correlation in multivariate regression showed that nonlinear relationship between the indicators of landslide affecting sediment load in this sub-basin is dominant Among the indices, the mean slope of landslides with a coefficient of explanation of 0.997 and landslide area with a coefficient of explanation of 870.0 had the most effect on sediment load in the sub-basin of flower mud and the indexes of distance to main stream with a coefficient of explanation of 0.94 and length Landslide and rupture surface with a coefficient of 0.878 have the most effect on sediment load under the Chavez Basin. Therefore, it cannot be judged that, for example, the area variable has a direct relation with the increase or decrease of sediment, but it is necessary to analyze in the conditions of the catchment area and taking into account other variables affecting the landslide in the sedimentation of this process.