Feasibility of Triticale (Tritico secale wittmack. X) Cropping in Agricultural Lands of Gorgan County by Spatial Analysis Tools

Selecting the most appropriate algorithm for land suitability assessment is important for current and future land use planning. Several approaches have been attempted to conduct land suitability assessment. Geographic Information System (GIS) technology is useful for integration of bio-climate, terrain and soil-resource-inventory information (Sarkar et al., 2008). The integration of Multi-Criteria Analysis (MCA) methods such as Analytical Hierarchy Process (AHP) with GIS is a trend in land suitability analysis. This combination could be useful in solving conflictive situations for individual or groups interested in spatial context and is also a powerful approach to land suitability assessments (Elsheikh et al., 2013). The present study was therefore carried out with the objective land suitability analysis for feasibility of triticale cropping in agricultural lands of Gorgan township by spatial analysis of geographic information system (GIS) and evaluation of environmental variables. Introduction It is essential to allocate crop to the most suitable land areas precisely for the best production since arable land has been decreased. Selecting the most appropriate algorithm for land suitability assessment is important for current and future land use planning. Several approaches have been attempted to conduct land suitability assessment. Geographic Information System (GIS) technology is a useful tool for integration of bio-climate, terrain and soil-resource-inventory information. The integration of Multi-Criteria Analysis (MCA) methods such as Analytical Hierarchy Process (AHP) by GIS is a trend in land suitability analysis. This combination could be useful in solving conflictive situations for individual or groups interested in spatial context and it is a powerful approach for land suitability assessments (Elsheikh et al., 2013). The present study was therefore carried out with the objective land suitability analysis for feasibility of triticale cropping in agricultural lands of Gorgan county by spatial analysis of GIS and evaluation of environmental variables. Material and Methods One of the most important areas for crop production in Golestan province located in north of Iran, is the Gorgan region. This area is located between latitude 54° 12.9' N and 54° 44.9' N and longitude 36° 30.6' E and 36° 58.8' E.Almost every farm in Gorgan region are rainfed. In order to spatial feasibility of triticale cropping in Gorgan county, agroecological requirements of triticale was identified and classified from scientific resources. Some environmental factors including, climatic variables such as precipitation and temperature in scale of annual, monthly and seasonal, topographic variables such as elevation, slope aspects and slops percent, and some soil characteristics as texture, EC, pH, fertility, K, P and organic matter were evaluated using geostatistics and classic methods and then thematic layers were produced in ArcGIS media. In multi-criteria assessment process, one of the most important steps is to determine each criteria weight. Generally, AHP is suitable to determine the weights of assessment factors. In this respect, the first step is to construct an AHP model consisting objectives, criteria, sub-criteria, and alternatives. Then these digital layers were classified based on ecological requirements table of triticale and they were overlaid and interpolated in GIS media and final layer were classified to four classes of high suitable, suitable, less suitable and non-suitable. The suitability analysis was based on matching between land qualities/characteristics and crop requirements. It was accomplished by weighted overlay technique (WOT) in GIS. Results and Discussion The results showed that 28.8 thousand ha (44.92%) of agricultural lands were located in the high suitable class (S1). This zone was observed occasionally in north and northwest parts of studied region. This zone had the high fertility, high organic matter percent (