جستجوی مقالات مرتبط با کلیدواژه « ارسباران » در نشریات گروه « جغرافیا »

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.

Massive movements, especially landslides, are one of the most important natural disasters. Landslides endanger people's lives with environmental degradation, their resources and assets.
Existence of factors such as prerequisites for roughness, uncontrolled exploitation of forests, non-observance of technical principles for the construction and maintenance of forest and rural roads, lack of proper management and unconditional exploitation of existing resources have exacerbated it. Landslides cause significant damage financially and morally compared to natural hazards such as volcanoes and floods (GOSTI 2005: 408). The landslide every year causes many deaths and injuries in many parts of the world (Abedini et al., 2013), which necessitates the attention to this dangerous phenomenon. The research area in the area of about 9000 square kilometers of the Azerbaijani desert along the east and west to the north of the Aras and the west of the valley of Diz and its east is Qarshou and in the south of Ahar, and from Kasba to the Dare Dize valley along the northwestern slopes of the southern Karnatagh is.

Tourism is an important industry in almost every region of the planet. It touches the lives of most of the world’s population, employing numerous workers and contributing considerable percent of the global GDP. Tourism has long been identified as a powerful tool for development, spurring economic growth, increasing foreign exchange, smallholder investment, and local employment. As increasing the importance of developing the tourism sector to facilitate the achievement of economic development, attention to different attractions of tourism such as sports tourism has increased in recent decades. Sport tourism as main part of tourism sector has attracted growing concern from in relation to multiple aspects, such as sustainable development and diversification of the national economy. To address these concerns, it is necessary to investigate planning for sport tourism development. It is widely acknowledged that planning is crucial to successful sport tourism development and management; and planning has been a widely adopted principle in sport tourism development at both regional and national. As such, experts suggest strategic planning can be considered in the planning process; and a strategic plan be practically made for this purpose. Current research aimed to investigate the role of role of infrastructures of Arasbaran area, East-Azerbaijan in the development of sports tourism and formulate appropriate strategies for improvement and greater use of the region''''s tourist attractions.

Introduction Special and sensitive role of vegetation cover in ecosystem sustainability and moderating hazards such as floods, erosion and pollution of water resources persuades us to understand the environmental variables affecting the growth and development of it. This issue particularly is important for susceptible mountainous catchments. In these environments, geomorphic variables as special representative of environmental factors have close and interweaved relation to vegetation cover. So, knowledge of the relationships between geomorphology and vegetation can help us to better manage and maintain the mountainous ecosystems. The understanding 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) have widely improved modelling the spatial variations of vegetation cover. However, a few issues that are fundamental and important in geomorphic-vegetation relations must be noticed. Maybe, the scale is the most important issue in phytogeomorphic researches. This study aimed to assess and determine the relationships between geomorphology and vegetation cover using spatial regression approach in Arasbaran catchments (3 catchments: Naposhtehchhay, Ilginehchay and Mardanqumchay). We have particular stress for effect the scale on the relations and comparison of predictive regression models in multiple scales based on catchment and subcatchment divisions.
Materials and Methods Our approach is based on spatial multiple regression analysis between geomorphologic parameters and abundance of vegetation. In this regard, 27 geomorphomety parameters as independent variables and Normalized Difference Vegetation Index (NDVI) as the dependent variable were computed from Landsat imagery (ETM sensor) and digital elevation model (DEM) SRTM. First, preprocessing operations including atmospheric correction (noise reduction) and geometric correction were 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 extracted and prepared using GIS and SAGA softwares and NDVI layer computed using IDRISI software. Furthermore, determination and mapping the cathments and subcatchments performed by ArcHydro extension of GIS.Given the various scales of the variables, it was necessary to normalize the scale of data ( ) using the following formula: 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 spatial multiple regression (stepwise method) with 0/01 signisicance level. We examine the regression relations in two scales: 1- catchments 2- subcatchments. Finally, we compare different spatial multiple ression models at 2 scale for selection of best models.
Results and Discussion Initial results of showed that many of geomorphological parameters had significant relations with vegetation cover in spite of their low correlation coefficients. The results of rgression steps indicated that 8 parameters including valley depth, topographic position index, elevation, slope, slope position, transformed aspect, earth surface convexity and general curvature are the most important inependent variables in explaining the variance of dependent variable at catchment scale. The best linear regression model was abtained in Mardanqumchay catchment (R2= 0/32) in among regression models. In contrast, the weakest regression model is abtained in Naposhtehcay catchment (R2= 0/11) in among regression models. It appears that Ilghinehcay catchment have moderate phytogeomorphic conditions having moderate rgression model (R2= 0/21) in among regression models. It is found that there is a correspondence between ruggedness of catchments and prediction power and efficiency of the regression models. The results of regression analysis at subcatchment scale were significantly different. At this scale, best regression models observed with 0/42, 0/51 and 0/62 R2 values in Naposhtehchhay, Ilginehchay and Mardanqumchay, respectively. In contrast, weakest regression models observed with 0/08, 0/15 and 0/13 R2 values in Naposhtehchhay, Ilginehchay and Mardanqumchay, respectively. Hence, not only there are many differences among subcatchments, but there is considerable difference between catchments and subcatchments in the respect of intensity of relations between geomorphic parameters and vegetation cover.
Conclusion Results of the research showed the 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 variables in explaining the spatial variations of vegetation cover in Arasbaran catchments. The selected geomorphic variables, Wholly, are partly complete reflection of geomorphology of a site, not only keeping the relation between form and process, are the special representative of other environmental factors. Although significant portion of spatial variations of the vegetation cover could not be explained by final regression models at cathment scale, but the predictive models are valuable, considering the application of pixel-based spatial approach in regression analysis, in one hand and complex non-linear relationships between vegetation cover and geomorphology, in other hand. At subcatchment scale, some of these relations are stronger than catchment scale and regression models are more efficient, leading to inhance the understanding of relationships between geomorphology and vegetation. Furthermore, we can give preference to subcathments based on strength of regression relations (R2 rates), which determines the phytogeomorphic sensivity of them, in order to manage and support the mountainous ecosystems. It is concluded that important information about relationships between geomorphology and vegetation can be acquireed at multiple scales, simultaneously.

Development of tourism activities is one of the important topics in sustainable development and it has been introduced as a dynamic and growing industry. So, providing a suitable platform for identifying tourist attractions and planning for development them is an essential issue. Also, recognition of these attractions and natural talents in each region in order to make proper planning, leads to the formation of prone base of sustainable development and economic profit. In special natural and protected areas, assessment of tourism potential can be beneficial in order to reduce the damages and costs and minimize the negative impacts. Moreover, to achieve rural tourism in protected areas, applying rural cooperation approach can be helpful. Ecological potential assessment is assessment of inventory and potential of land by specific and pre-planned criteria. Ecological potential assessment studies are used as a basis for land use decision making and planning in all the world. For this purpose, determination of tourism areas in different classes according to natural ability, is important. Locating and planning based on natural condition can bring positive economic and social effects, and in the case of proper operation, it will have little negative environmental impact. For the development of tourism activities, selecting areas consistent with the ecological characteristic, on the one hand, reduces its negative effects on the environment and on the other hand, leads to boom tourism activity. Misheh Pareh village with cold and semi-arid climate is one of the villages of center part of the Kaleibar city in East Azarbaijan province. This village is in the Caspian catchment and the Aras river watershed and bordered by Khodaafryn city, Varzegan and Peyghanchay villages. Part of the largest mountain range of East Azarbaijan (Kharabakh Mountain) is in this area. Unique position of this village for tourism development is because of being in the Arasbaran conservation area and close to the border of Azerbaijan country and Aras commercial and free zone.

Firstly in this study, review of research, methods of evaluating and interpreting the contents recorded by other researchers have been discussed by library studies. More for potential assessment of this village to determine the most appropriate place to development tourism, multi criteria evaluation method analytic hierarchy process AHP was chosen based on the purposes of the analysis. One of the reasons for using this model compared to other models is in the ability of this model in quantification the qualitative indicators which is the most important reason for using this model in the present study. Since in this technique it is taken for granted that the study area is spatially homogeneous, these methods do not have the space dimension. Hence, a framework for multi criteria decision analysis based on GIS is necessary for using GIS capabilities in the acquisition, storage, retrieval, processing and analyzing data, integrated with the technical capabilities of multi criteria decision model. Combining GIS and AHP is a decision support method with powerful visualization and mapping capabilities, which in turn will facilitate proper use of land through creating a map. In this study, weighting and prioritization criteria were performed by using expert opinions. Then quantitative information of criteria entered into the GIS by using Marynouny help software and for each criteria a spatial layer was prepared. Selecting proper criteria, especially in optimal locating for different activities and organizing the structure of geographical spaces, creates the chance of comparing the alternatives and choosing the best of them. The important criteria to choose the best place to develop tourism in the area under study were identified and weighed through hierarchical analysis technique. Table 1 shows the final weight of the criteria. Totally, 10 criteria were selected and constructed as maps, as important criteria in potential rural tourism potential assessment based on research, data and expertise. Layers weight include: (Height: 0.0188), (slope: 0.0438), (aspect: 0.0171), (current land use: 0.691), (vegetation density: 0.2995), (distance from river: 0.1703), (distance from Water Fountains:. 0658), (close to the road: 0.0392), (close to the ancient site: 0.1482), (close to some villages: 0.1281). The four layers was considered as the limit and were deducted from the final output. Classification of layers in GIS by consideration of protected areas were divided into four categories. The valuation of areas in four category include Tourist prone areas)good), semi-prone areas for tourism (medium), areas with high tourism potential (voltage) and tourist areas without power (inappropriate) has been done. Criteria were evaluated according to SAATI method between 1 to 9. Then in the final step each of the layers were combined based on their weight, and the final tourism development potential map obtained in the region. In the studied area, important criteria for selecting a suitable place for tourism development were identified and weighted by using the AHP technique. After that restrictive layers include important habitats, ranging from the ancient site, the privacy safe of the river safe, the privacy safe Road were deducted from the final map.

Based on the Results Forested areas with dense vegetation 50-75 percent that is near the village centers, especially Osklu because of having more facilities and good access roads, has the highest potential for tourism development. Also due to the view point of safety in determining the potency of tourism development, privacy habitats and archaeological sites and forest areas with density of 75-100, have the lowest potential for rural tourism development. According to the comparison criteria and weights, vegetation, closeness to rivers, archaeological sites and central villages have the highest ratio of weight, and height and aspect have the lowest weighted coefficient. This coefficients indicate the importance of them.

Development of tourism activities is one of the important topics in sustainable development and it has been introduced as a dynamic and growing industry. So, providing a suitable platform for identifying tourist attractions and planning for their development i is an essential issue. Also, recognition of these attractions and natural talents in each region in order to make proper planning, leads to the formation of prone base of sustainable development and economic profit. Totally, 21.63 percent of the land of the region has good potential, 18.5 percent is mediocre, and 44.94 percent lacks the potential tourism development. Therefore, according to the good potential of the region, tourism development programs can be offered in this area in order to achieve sustainable development by a principle detailed plan.

Arasbaran is one of most important regions in terms of agriculture، economics and tourism in northwest of Iran that it usually receives the most yearly spring precipitation. To recognize the synoptic patterns of the 500 hpa، geopotential height data were driven for coordinates 00-70 ˚ E and 15- 65˚N in rainy springs (1972-1976-1979-1981-1986). To select the most important component using principal components analysis، a matrix S mode with dimensions 386×610 was used. The results showed that more than 92% of the total variance can be explained by 13 components. After clustering procedure on the 13 components، six circulation patterns were obtained. In 5 cases of the extracted patterns، there''s a really high center of east Mediterranean and south east Europe، the most important component was detected during the wet spring. Other major factors will be referred to the short-wave atmospheric middle level that at this time of year is usually active between the Caspian Sea and the Black Sea and cause wet periods in spring in this area. The systems accompanying low active centers of located in Central Asia and their short waves bring instability and precipitation in the spring to this area.