Applying the Best–Worst Method for land evaluation: a case study for paddy cultivation in northwest Turkey
Künye
Everest, T., Sungur, A., & Özcan, H. (2022). Applying the Best–Worst method for land evaluation: A case study for paddy cultivation in northwest turkey. International Journal of Environmental Science and Technology, 19(4), 3233-3246. doi:10.1007/s13762-021-03373-4Özet
Several multi-criteria decision-making methods are used in land suitability analyses. The main objective of this study is to present the potential use of the Best–Worst Method to determine agricultural land suitability. Study was conducted in 6837.26 ha land in Canakkale northwest Turkey. Nine land characteristics (texture, electrical conductivity, drainage, pH, depth, cation exchange capacity, organic matter content, soil fertility index (N, P, K and Zn content) and CaCO3%) were used. Data obtained from the Best–Worst Method were compared with the results of Analytical Hierarchy Process, and Storie Index method. According to the Best–Worst Method, 5.76% of the land was highly suitable, 58.37% were moderately suitable, 31.93% were marginally suitable, and 3.94% were not suitable for paddy cultivation. To Analytical Hierarchy Process, 5.76% of the land was highly suitable, 61.42% were moderately suitable, 29.01% were marginally suitable, and 3.94% were not suitable and with respect to Storie Index method, 5.76% were highly suitable, 0.20% were moderately suitable, 57.78% were marginally suitable, and 36.26% were not suitable for paddy cultivation. There was a statistically positive correlation between the Best–Worst Method and Analytical Hierarchy Process (r =.997) and negative correlation between Storie Index. So, results showed that the data generated with the use of Best–Worst Method were consistent, reliable and complied with the data of Analytical Hierarchy Process. The advantage of the Best–Worst Method to other methods is to conduct less pairwise comparisons and has more practical and fast algorithm. So, the Best–Worst Method can reliably use in crop-based land suitability analyses.