فصلنامه جغرافیا و پایداری محیط
پیاپی 20 (پاییز 1395)

In the current era, characterized by uncertainty, initiative, and complexity of issues, the traditional planning system faces various challenges. In fact, lack of identification, analysis, and implementation of key factors in regional development is considered as one of the weaknesses of regional planning systems. Therefore, the present research has been conducted with a foresight approach aiming to identify key factors in development of Northern Khorasan province. This study has applied the technique of analyzing cross-impacts. Besides, MICMAC software has been used to analyze the data. The results of analyzing the effectiveness of factors indicate an unsustainable situation in the regional system of northern Khorasan province. Applying the results obtained from this research and the initial factor analysis, 17 key factors were identified in the development of the region. Out of these factors, “development of new main roads for trans-provincial connections”, “existence of integrated rural territories”, “geopolitical situation of the province in relation to the Eastern Asia road”, “promotion of intra-provincial secondary roads in line with development of the settlement system”, “relative balance at the top of the urban system of the province”, “straightening border markets”, and “A variety of economic sectors with an average functionality” are the key factors which can be used as a base to outline scenarios and spatial allocation at provincial level. The result of these studies and identification of key factors are a basis for sustainable policymaking of spatial development in the future of the province that can integrate all the sectional and spatial measures and scenario makings at local levels into itself.

Slope instabilities are considered as one of the major dangers to human activities which occurred in natural slopes and the slopes made by humans. This study aimed to identify the factors affecting the occurrence of slope instability using logistic regression models and artificial neural network in Ahar Sattar khan dam basin. The results of statistical models to determine the potential areas of instability and ultimately create a hazard zonation map for the study area. In this regard, the most important factors in landslides such as slope, aspect, elevation, rainfall, distance from the road, fault and drainage, land use and exploration and peculiarities of each of them were identified. Standardization base of histogram model is by cutting the classes of each layer with occurred landslides. The models show that the very high-risk area in the neural network and logistic regression are 724 and 5/56 per cent respectively which cover the areas close to Sattar khan dam, mainly including the lithology of these areas located in the regions with lower resistance. Besides, Statistical methods Logistic prove that faults and lithology have an immense impact on the occurrence of landslide in this area. The ROC index value for neural network and logistic regression models are 0/85 and 0/81. So it can be said neural network model for zoning of landslides is more efficient, so any planning and construction must be compatible with the conditions of geomorphology and geology of the area leading to as least human and financial losses as possible.

Low productivity in agricultural sector, inappropriate use of production factors to enhance product performance during the last decade as a result of adverse environmental degradation and the need for sustainable production and food security prove the importance of the sustainability of the agricultural farming systems. This study is aimed to assess the sustainability of agricultural farming system, including smallholders, rural production cooperatives and Farm Corporation. The statistical population consisted of 17362 members of rural production cooperatives, 635 members of Farm Corporation and 85405 smallholders. The sample size is calculated by using Cochran formula and the appropriate assignment to each cooperatives and smallholders. The results showed that the standardized complex index of farm Corporations and rural production cooperatives are semi stable while smallholder system is unstable. Dimension farm Corporation is economically more stable than the other two systems, while less stable than the others with social dimension. Besides, social dimension of rural production cooperatives is more stable than other two farming systems. Moreover, environmental dimension is less stable to farm Corporation. Smallholder farming system in term of three dimensions especially economic dimension which is unstable. Economic strengthening small farmers system could be regared due to the fact that is a major percentage of farmers in Iran to increase the sector's degree of sustainability.

Ekbatan Dam and groundwater resources in Hamedan-Bahar plain are the main suppliers of drinking water in Hamedan city. The aim of this study is to evaluate drinking water supply in the medium-term time horizons (1410) and long term (1430). Therefore, resource system, consumption area of Ekbatan dam and underground provider are modeled by WEAP using 40-year-old statistics. calibrating the findings, the actual conditions of use and watershed resources in the current situation (in 1391) and both unauthorized and authorized the withdrawal of underground water source were modeled. The results showed that water shortage of Hamedan is around 2.8% annually. Having per capita expenditure per person as well as the urban population estimated in the aforesaid period, at first, the demand for drinking water is calculated. Then, considering water demand to be constant in other sectors, water demand was modeled. The results showed that about 19.6% and 34. 4% in 1410 and 1430 respectively face water shortage. The situation was almost the same in other sectors. Due to constant water resources and significant deficiencies in the research horizons, respectively, structural and non-structural solutions and their effects were tested. However, it was observed that structural measures alone are not helpful. That is why non-structural solutions on side structural solutions were proposed and examined.

The study of inequality and its Existence in different geographic areas has attracted the attention of programmers and politician in recent years. In our country suffering from space intra-regional and between-regional disparities in several cases, paying attention to spatial inequality in different aspects and indexes is necessary. In this regard, the aim of this research is the examination of the developmental level and spatial inequality and the analysis of developments of this spatial inequality of the agricultural sector among the cities of Kurdistan since 1996 to 2016. The research is a descriptive-analytic one which is performed in all cities of Kurdistan regarding political-administrative territory of this province in 1996 and 2016. Since the balanced development needs exact and comprehensive examination, there are 26 indices of agricultural sector in this study. Multi-criteria decision-making model “ELECTRE“ is used to examine the assumptions and analysis of data. The benchmark value of all indices is calculated by ANP method. Moreover, Williamson factor is used to examine the spatial inequality in all cities of Kurdistan, and Pearson Coefficient of Skewness is used to examine the distribution infrastructure. The findings show that the level of development has increased from 1996 to 2016 in the cities of Kurdistan, but relative convergence has not achieved. Besides, it is determined that core-periphery model has been the prevailing theory in distribution of agricultural infrastructure in this province. Therefore, Sanandaj has been considered as the most developed one while Sarvabad and Kamyaran are the least developed in agricultural sector indicators. Moreover, distribution infrastructure has positive skewness.

Land management leading to sustainable development requires reliable and update data on land cover/use and mapping its changes at various spatial and temporal scales. In this aspect, water resources management also needs to assess land use and its changes across the basin to maintain water quality for a variety of uses. Thus, the primary goal of this study is to evaluate the effectiveness of various spectral-based supervised classification methods of Operational Land Imager (OLI) data for mapping land use across the Kan and Karaj Rivers basin. At the Anderson Level 1 and 2, the basin’s land use was mapped in five and nine classes, respectively using a broad range of different supervised classification methods, including Parallelepiped, Minimum Distance, Mahalanobis Distance, Maximum Likelihood, Spectral Angle, Binary Encoding, Spectral Information Divergence, Neural Net and Support Vector Machine. All classification methods were verified using the Google Earth images and accurate ground control points, in which the Maximum Likelihood method of both levels with Kappa coefficient of 0.77 and 0.76 and overall accuracy of 84.94 and 80.70 percent, identified as the optimum method to map the land use at the local and regional scales respectively. In addition, following the named method, the Neural Net, Support Vector Machine and the Mahalanobis Distance methods also showed acceptable accuracy indicating that like the choice of classification method, precision in procedures and accuracy assessment of land use classification map is very important and could affect the results.

Analyzing and comparing the level of Facilities enjoyment and identifying inequalities and imbalances within different geographical districts , leading to find the weaknesses and the appropriate policy to solve them, are of great importance, especially in order to identify different regions in terms of development. In this regard, industrial ranking, which has been done by Management and Planning Organization and Ministry of Industry, Mine and Trade for years, is considered as a way to study changes in industrial development of country provinces. Using multi-criteria decision-making (TOPSIS and SAW), the current study aims to analyze and examine the development of industries in Chaharmahal and Bakhtiari Province. This research is a kind of descriptive-analytic one approaching applied study. The data of Statistical Yearbook of 1392(solar year) were used in the research. Statistical software of EXCEL was utilized to analyze the data. TOPSIS results indicate that Shahrekord Parish with score of (1), is recognized as the most developed area. In terms of industrial index and Bon with a score of (0.00), it is identified as the poorest area Province. SAW Results show that Shahrekord with (0.679) points, is the most developed city, and Bon with score of (0.00) is the most deprived city in the Province. Therefore, reviewing development plans of the province is required in the future.