Fuzzy Logic Model to Assess Desertification Intensity Based on Vulnerability Indices
Mohammad Hassan Sadeghiravesh, Hassan Khosravi, Azam Abolhasani, Marzieh Ghodsi, Amirhosein Mosavi
Abstract
Executive practices on desertification control should be based on recognizing the current desertification state and its severity. So, it is essential to assess the ways to give zoning based on logic, active principles, and theoretical foundation for the management of desert regions. For this aim, 30 useful indices on desertification were determined in two human and natural sections. The significance of indices relative to each other and each index's importance per work unit was determined using the Delphi method. The Bonissone method in the framework of the Fuzzy Multiple Attribute Decision Making (FMADM) method was used to combine indices and determine desertification intensity in each working unit. Then, data were converted to the Fuzzy layer using Chen and Wang method, and Fuzzy analysis was performed on data. Finally, Fuzzy data were changed to non-Fuzzy, and desertification intensity was estimated. The results showed that 9.35% of the study area was in a very high class regarding desertification intensity and 9.36% of the region was in relatively high class. Desertification with moderate intensity (50.64%) and a relatively moderate intensity (29.45%) had the most shares in the study area, respectively. The quantitative value of desertification potential in the whole area from all of the components was obtained as 0.083, relatively high. This study shows the efficiency and ease of Fuzzy logic application for assessing desertification intensity.