Document Type : Original Article


1 Phd candidate of Agricultural Economics, University of Sistan and Baluchestan, Iran

2 Associate Professor of Agricultural Economics, University of Sistan and Baluchestan, Iran

3 Assistant Professor of Civil Engineering, University of Sistan and Baluchestan, Iran


Sistan region is one of the most important agricultural areas in the province of Sistan and Baluchistan. Therefore, given the heterogeneity in agriculture and recognizing these differences, the aim of this study was to obtain the level of development of agriculture in the Sistan region. To obtain this purpose two Fuzzy Analytical Hierarchy Process (FAHP) and the numerical taxonomy was used in a view of 20 indicators in the agricultural sector in the region. The required data was achieved by filling out the questionnaire certified experts and statistical yearbooks in the agricultural sector. Data analysis was used by Matlab and SPSS software. Results of numerical taxonomy showed that Markazi, Shibab and Poshteab sectors component parts were less developed. Also, Jazinak and Miyankangi are in the category sections were undeveloped. The results of Fuzzy Analytical Hierarchy Process (FAHP) model indicated that Markazi, Shibab and Poshteab sectors are in the first rank of development, in terms of agricultural indices in the region. Jazinak and Miyankangi are in the fourth and fifth ranking. Therefore, in general, it is clear that the level of development of agricultural in Sistan region isn’t in good condition. In this regard itis suggested that appropriate planning to promote agricultural development is on the agenda should be applied.


[1] Badri, A., Akbarian, S., &Javaheri, H. (2007). Demining the level of development in rural areas of Kamyaran city. Journal of Geographical Research, 2(82), 17-29.
[2] Chuntian, C. (1999). Fuzzy optimal model for the flood control system of the upper and middle reaches of the Yangtze River. Journal Hydrological sciences, 44(4),573-582.
[3] Ebrahimzadeh, A., & Eskandarisani, M. (2011).The location of factor analysis to explain the development environment and development. Journal of Geography & Development, 8(17), 7-28.
[4] Fu, G. (2008). A fuzzy optimization method for multi-criteria decision-making: An application to reservoir flood control operation. Expert Systems with Applications, 34(1), 145-149.
[5] General Censusof Population and HousingCensusof Iran, (2012).
[6] Khakpoor, B., & BavanPoori, A. (2009). Analysis of Mashhad city inequality in levels of development. Journal of Knowledge & Development, 16(27), 182-202.
[7] Malczewski, J. (1999). GIS and multi criteria decision analysis. USA and Canada, John Wiley & Sons.
[8] Mohammed, A. (1980). Regional Imbalances in Levels and Growth of Agricultural Productivity -A Case Study of Assam. The Geographer, Aligarh Geographical Society, Aligarh.
[9] Moradi, ZH., Mirakzadeh, A., Rostami, F., Karimi, F. (2015). Measuring of agricultural development levels in villages of Qaratureh Dehestan using TOPSIS technique. Journal of Research and Rural Planning, 4(2), 21-23.
[10] Peet, R. (1999). Theories of Development, Guilford, New York and London.
[11] Rafiee, R., Ataei, M., & Jalali, S.M.E. (2013). The optimum support selection by using fuzzy analytical hierarchy process method for Beheshtabad water transporting tunnel in Naien. Iranian Journal of Fuzzy Systems, 10(6), 39-51.
[12] Ramatu, M., & Xinshen, D. (2007). Regional disparities in Ghana: Policy option and public investment implications. International Food Policy Research Institute (IFPRI), Washington, discussion paper series, No. 693, 1-55.
[13] SardarShahraki, A., Karim, M.H., & SheikhTabar, M. (2014). Determine the level of economic development of agriculture and the rural sector in Iran. Journal of Rural Development, 16(1), 21-36.
[14] Sasikumar, K., & Mujumdar, P.P. (1998). Fuzzy optimization model for water quality management of a river system. Journal Water Resource Planning and Management, 124 (2), 79-80.
[15] ShafaiyanFard, D., KohiyanAfzal, F., & Yakhkeshi, M. (2015). Determine Superior options of water resources with the use WEAP model and Multi-criteria decision analysis (case study: Zaringhol basin). Journal of Watershed Management, 5(9), 29-45.
[16] Shafiee, M., Ketabi, S., & Shaker Ardakani, M. (2012). Optimum selection of integrated marketing communication tools with FAHP approach (a home appliances group case study). Journal of Operational Research and Its Applications (Journal of Applied Mathematics), 9(3), 13-26.
[17] Sharama, B. (2004). Regional Disparities in agricultural labor productivity in the Brahmaputra valley, International Journal of Interdisciplinary Social Sciences, 4(1), 43-56