Land suitability classification for pit-seeding project using fuzzy multi-criteria decision making

Due to widespread degradation of rangelands, one of the most effective ways to recover rangelands is to utilize range improvement methods. Pit-seeding is one of the common methods of range rehabilitation which is difficult and time consuming. Determine of the most appropriate place for its successful execution is data demanding and needs numerous factors to be involved. Theats why, the use of fuzzy multi-criteria decision-making methods will be helpful. One of these methods is the Fuzzy Analytic Hierarchical Process. In this study, four ecological criteria i.e., vegetation, soil, physiography and climate were selected along with fourteen sub-criteria. Fuzzy pair comparison matrixes of criteria and sub-criteria were determined through fuzzy analytic hierarchical process; and using triangular fuzzy numbers, proportional importance of each one of them towards others was presented by getting the opinions of experts. Later with the help of Changchr('39')s extent analysis, weight of FAHP for criteria and sub-criteria were obtained. Then, the data layers of the sub-criteria were determined and weight of FAHP were applied on them. Finally, the weight-given data layers were created and ranked suitability of land for application of pit-seeding project in Maravehtappe watershed were achieved. The results showed that for the project, climate and vegetation with the weights of 0.559 and 0.190 and the sub-criteria of rainfall, plant composition and temperature with the weights 0.368, 0.162 and 0.093 are the most important ecological factors respectively. The results showed that 1.49% of the studied region is excellent for pit-seeding. The ecological results were validated threough field visit. Correctness of results for pit-seeding project was calculated as 86.94%. The results showed that using AHP and Fuzzy models, can simplify the complicated processes and removs uncertainties. Tus it is an appropriate tool for the managers in land improvement projectes.