Determination of land suitability for wheat and sunflower cultivation in Silisözü Basin using analytic hierarchy process and Geographic Information Systems (GIS)
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Abstract (EN)
This study utilzed the Analytic Hierarchy Process (AHP) and Multicriteria Decision Making (MCDM) processes to determine land suitability for wheat and sunflower cultivation in the Silisözü Basin. The research focused on a multicriteria decision-making process using soil and topography databases. The soil database comprised factors such as pH, EC, Organic Matter (OM), Texture, Lime, and Soil Fertility Index (SFI), while the topographic database included parameters like slope, aspect, and depth. In the AHP process, for wheat, the three most significant parameters were identified as depth (2.48), EC (1.98), and slope (1.58), while for sunflower, depth (3.65), slope (2.56), and EC (1.30) were found to be the most prominent parameters. According to the FAO land suitability classes, the Silisözü Basin exhibited the following distribution for wheat: highly suitable (S1) areas comprised 18.73%, moderately suitable (S2) areas comprised 41.49%, and less suitable (S3) areas comprised 39.76%. No class was determined as unsuitable for agricultural purposes for sunflower cultivation. For sunflower cultivation, the distribution of suitable agricultural classes was as follows: highly suitable (S1) areas covered 18.22%, moderately suitable (S2) areas covered 35.16%, and the most extensive coverage was the less suitable (S3) class, representing 46.60%. The results highlighted that soil depth, EC value, and terrain slope are critical factors for wheat and sunflower cultivation. These findings are crucial for identifying suitable agricultural regions and planning agricultural practices. Additionally, the study provided some recommendations based on the obtained results.
Author
Sema Çıtak
Institution
How to Cite
Sema Çıtak (Master Thesis). Determination of land suitability for wheat and sunflower cultivation in Silisözü Basin using analytic hierarchy process and Geographic Information Systems (GIS), 2024, Tokat Gaziosmanpaşa University.
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