Risk Analysis Using Geographic Information Systems by Determining the Factors Affecting Yield in Plant Production: A case study from Ankara, Turkey


TARIM BILIMLERI DERGISI, vol.28, no.4, pp.14-690, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 28 Issue: 4
  • Publication Date: 2022
  • Doi Number: 10.15832/ankutbd.900997
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, Food Science & Technology Abstracts, Veterinary Science Database, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.14-690
  • Keywords: Risk maps, Multi-Criteria decision Model (MCDM), Analytical hierarchy process (AHP), Fault tree analyses (FTA), Agricultural product risk maps
  • Gazi University Affiliated: Yes


Performing agricultural analysis is becoming much more effortless due to the rapid improvements in information technologies. Geographic Information Systems (GIS) provide more detailed data about climate, soil, topography, and irrigation values regarding agriculture; thus, allowing for performing detailed location analyses. These analyses cover agricultural investment maps, agricultural propriety areas, and plant pattern detections. The purpose of this study is to develop product-based agricultural risk analysis maps. Climate, soil, topography, and irrigation data are essential in the cultivation of agricultural products. With risk analysis, the risk values are determined for each risk factor. Applying the Analytical Hierarchy Process (AHP), which is one of the multi-criteria decision-making methods, the total risk value is calculated by prioritizing the risk factors. AHP is an efficient methodology developed to calculate scenario-based risk values by considering various possibilities. In this study, a model is generated by studying apricot, sour cherry, and almond farming in Ankara. As a result of the development of a GIS model for Ankara, the total risk values were mapped as "High-Risk Areas", "Medium-Risk Areas", "Low-Risk Areas" and "Strongly Not Recommended Areas" according to the points they received spatially. When the maps were examined in detail; it was determined that apricot crops in Ankara province are more sensitive to climate, soil, and topography conditions than other products. Since apricot is affected by late spring frosts, it is recommended that risk factors can be reduced by taking climatic measures in areas where soil structure is suitable. It has been determined that the sour cherry product is less sensitive to climatic and topographic conditions and is more affected by the risk factors from the soil layers; while the almond product is more affected by the climatic conditions, though it is more tolerant to soil conditions. According to these results, apricot can be grown in large areas with medium and high-risk levels, and in limited areas with low-risk levels. Almond with a very high-risk level can be grown in large areas compared to apricot, and sour cherry can be grown in similar-sized areas with apricot, but with a lower risk level than apricot.