بررسی و تحلیل توسعه‌ یافتگی و نابرابری‌های فضایی بخش کشاورزی استان کردستان طی سال ‌های 1375 و 1395

بررسی نابرابری و وجود آن در محدوده‌های جغرافیایی مختلف در سال‌های اخیر مورد توجّه برنامه‌ریزان و سیاستمداران قرار گرفته است. کشور ما در بسیاری موارد از نابرابری فضایی درون و بین منطقه‌ای رنج می‌برد؛ از این رو، توجّه به موضوع نابرابری فضایی در ابعاد و شاخص‌های مختلف کشور دارای ضرورت اساسی است. در این راستا، پژوهش حاضر با هدف سنجش وضعیّت توسعه‌یافتگی و نابرابری‌های فضایی بخش کشاورزی بین شهرستان‌های استان کردستان و تحلیل روند تحوّلات نابرابری آنها طی سال‌های 13951375 طرّاحی شده است؛ از آنجا که توسعه متعادل و متوازن فضاهای جغرافیایی، نیازمند بررسی دقیق و همه‌جانبه در ابعاد مختلف آن است، در این پژوهش، تعداد 26 شاخص در بخش کشاورزی، تعریف شده است. برای بررسی مسائل تحقیق و تجزیه و تحلیل داده‌ها از مدل تصمیم‌گیری چندمعیاره «حذف و انتخاب سازگار با واقعیّت (یک)» استفاده شده و وزن معیار هر یک از شاخص‌ها با روش «فرایند تحلیل شبکه‌ای» محاسبه شده است؛ همچنین برای بررسی نابرابری‌های فضایی شهرستان‌های استان کردستان، ضریب ویلیامسون به کار رفته است. بـه این منظور، جهت بررسی توزیع زیرساخت‌ها از ضریب چولگی پیرسونی استفاده شده است. نتایج یافته‌ها نشان می‌دهد که طی سال‌های 1375 تا 1395 به میزان توسعه‌یافتگی شهرستان‌های استان کردستان افزوده شده است؛ امّا همگرایی نسبی بین شهرستان‌ها حاصل نشده است. همچنین مشخّص شد که نظریّه غالب در توزیع زیرساخت‌های کشاورزی این استان بر اساس مدل مرکز پیرامون بوده است؛ به طوری که در هر دو دوره بررسی‌شده، شهرستان سنندج به عنوان توسعه‌یافته‌ترین و شهرستان‌های کامیاران و سروآباد به عنوان کم‌توسعه‌یافته‌ترین، از لحاظ شاخص‌های بخش کشاورزی، بوده و توزیع زیرساخت‌ها از نوع چولگی مثبت و به صورت نامتقارن بوده است.

Analysis the Degree of Development and Spatial Inequalities of Agricultural Sector in Kurdistan Province from 1996 to 2016

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 intraregional and betweenregional 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 descriptiveanalytic one which is performed in all cities of Kurdistan regarding politicaladministrative 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. Multicriteria decisionmaking 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 coreperiphery 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.Extended Abstract1IntroductionDue to the fact that agriculture plays a vital role in economy, nowadays some concerns have been created about the potential of this sector as a stable income todecrease poverty of farmers and food security in urban and rural areas. The reason for these concerns is that the agricultural environment and rural areas have faced unprecedented environment problems particularly during last two decades. In Iran, like in other developing countries, agriculture is one the most important parts of economy which encompasses a significant percentage of production and employment. Therefore, this research aimed at determining the level of development in agricultural sector of Kurdistan provinces’ cities and determining inequality of agriculture development of them (during two years 1996, 2016). In this study, some methods were used including: analytical network process for achieving weight of indicators, ELECTRE model for determining the development of agricultural sector, Williamson inequality method to study the spatial inequality and Pearson's Skewness factor for the distribution of agricultural indicators in the province. Therefore, the main subject of this study, according to 26 indicators surveyed in both periods, is “which cities of Kurdistan provinces’ are appropriate in terms of having agricultural development indicators and which of them are deprived. Besides, they are trying to find how the spatial inequality and the distribution of facilities and agricultural are infrastructure.2 Materials and MethodsIn this applied and descriptiveanalytical research, the required information and data related to the infrastructures of agricultural development in the cities of Kurdistan provinces was collected using the Census of Agriculture and Census of Kurdistan province. EXCEL software was used in order to make database for statistical operations. Afterward, the prosperity rate in any of Kurdistan cities was analyzed based on 26 agricultural indicators from 1996 and 2016. Then, the city ranks were determined using the “multicriteria decision making” method and the importante factor of infrastructural criteria was found using the “analytical network process”. Finally, the spatial inequality and distribution of agricultural infrastructures in cities were determined using the Pearson's Skewness factor.3 Results and Discussion As mentioned before,  agricultural indicators were analyzed in the Kurdistan province. Multicriteria decision making” method was used to analyze the indicators. Besides, the rate of citie development was determined. Based on specified results, after obtaining effective coordinated and uncoordinated matrixes, the general matrix was calculated and the final rank of cities was obtained based on the amount of losses and wins. Also, Table 1 shows that, in terms of agricultural indicators, Sanandaj Ranked 1 and Dehgolan and Sarvabad cities ranked 8 among 10 cities of Kurdistan in 1996 and 2016. The rate of spatial inequality was 39.42 in 1996 and 33.58 in 2016 according to the results of Williamson inequality method. Also, Pearson's Skewness factor was 0.3 in 1996 and 0.56 in 2016 that show the asymmetric distribution of agricultural infrastructures in both 1996 and 2016.Table1: the result of investigating agricultural indicators using ELECTRE model in 1996 and 2016BanehBijarDehgolanDivandarehSarvabadSaghezSanandajQorvehKamyarancity017175913Final amount1996548682147rank315496914Final amount2016658392147rank For, according to 26 surveyed indicators in both periods (75 and 95), some theories in the field of agriculture in Kurdistan cities should be discussed to survey the main enquires of this research:Despite the different methods and indicators, the results of previous researches coincide with the current research findings especially in developed and undeveloped provinces. Shahraki and Sardar Shahrahi (1393) have investigated the rate of development in Sistan and Baluchistan provinces’ cities with an emphasis on major agricultural indicators. The findings showed that Zabol, Zahedan, Saravan, Chabahar and Khash city are relatively developed cities in terms of agricultural indicators which is consistent with the current research findings because provincial capitals are the most prosperous in agricultural part.Also, in this research, analytical network process, in which internal comparison of indicators is possible, was used for indicators and ELECTRE model in which the review of qualitative and quantitative indicators is possible.4 Conclusion The present research aims to study and compare the spatial inequality and development of agriculture in Kurdistan province in 1996 and 2016. The findings show that:Answering the first question, the findings indicate that in terms of prosperity of agricultural development indicators, Sanandaj city has had a suitable condition in two years (1996 and 2016) while Kamyaran city in 1996 and  Dehgolan and Sarvabad cities in both years have had an unsuitable and unstable condition. Answering the second question, the rate of spatial inequality was 39.42 in 1996 and 33.58 in 2016 according to the results of Williamson inequality method. As it is clear, the rate of spatial inequality has declined in 2016 compared to 1996. Also Pearson's Skewness factor was 0.3 in 1996 and 0.56 in 2016 indicating the asymmetric distribution of agricultural infrastructures in both years.