Assessment of Land Suitability for Sugarcane Cultivation Using TOPSIS and Parametric Methods in Southwestern Iran
Abolfazl Azadi, S. Jalali, Mir Naser Navidi
Abstract
Parametric land suitability assessment (LSA) sometimes does not correspond to the reality of the region due to low index values. Thus, new multi-criteria decision-analysis approaches (MCDA) that consider the mutual effects of criteria, such as the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method, can be utilized. This study aimed to compare the efficiency of the TOPSIS approach and parametric methods in assessing land suitability for sugarcane cultivation in southwest Iran. Hence, 45 sugarcane fields were selected in sugarcane cultivation and industrial areas in the south of Khuzestan province. In each farm, one pedon was studied in detail. Soil samples were collected from different horizons and taken to the laboratory for the designated physicochemical analyses. Sugarcane yields over the past three years were also gathered for each farm in the study. Then, the land suitability index values were compared with the sugarcane yield in the studied units using Storie, square root, and TOPSIS methods. The results revealed that soil salinity (EC) exhibited the highest specific weight value for sugarcane farming followed by soil pH, calcium carbonate equivalent (CCE), and soil depth. Furthermore, the preferred value with the TOPSIS method for sugarcane cultivation ranged from 0.42 to 0.92. The explanation coefficient (R2) obtained by comparing the order of priority of 45 options with their observed performance using the Storie, square root, and TOPSIS methods was 0.62, 0.64, and 0.76, respectively. Our results revealed that TOPSIS outperformed the other two methods to determine land suitability for growing sugarcane. The multi-criteria method improved the land suitability class and resulted in a higher land suitability class than the traditional method, which is more consistent with the reality in the region. In conclusion, the results of this study demonstrated the high efficiency and potential of TOPSIS compared to other commonly used models. Overall, it can be concluded that agricultural land use can be better planned and managed with the TOPSIS method.