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Integration of interval rough AHP and fuzzy logic for assessment of food prone areas at the regional scale

Sepehri Mehdi, Malekinezhad Hossein, Jahanbakhshi Farshid, Ildoromi Ali Rerza, Chezgi Javad, Ghorbanzadeh Omid, Naghipour Elham

Acta Geophysica

2020

Vol. 68, no. 2

477--493

This study was conducted to prepare a food susceptibility map in northwest of Hamadan Province, Iran. For this purpose, six criteria related to food (i.e., distance to discharge channel, slope (%), elevation, soil texture and land use, topographic wet index, and check dams) were chosen. Then, based on the role of these criteria on degree of food susceptibility, were weighted both in the context of inter-weighting (fuzzy logic) and outer-criteria (Interval Rough Analytic Hierarchy Process). Finally, by combining these primary weights by weight overlay method in GIS, the food susceptibility mapping was prepared in the study area. The resulted map based on K-means clustering and Silhouette function was divided into 9 clusters, whereas the lower clusters show low susceptibility to food and vice versa. To assess the accuracy of the produced map, 102 food observation points were overlaid on the clustered food susceptibility map. The results showed that among these 102 food points, 66 points are located in the clusters 8 and 9 and 3 points are located on cluster 7. These values show that the produced food susceptibility mapping has a high accuracy.