Land suitability analysis of new urban areas using MIF-AHP and bivariate analysis methods in Latakia, Syria.

Urbanization is a common issue worldwide that increases the demand for new urban services and requires land for a new settlement. This study focuses on improving the Analytical Hierarchy Process pairwise matrix using bivariate analysis to identify suitable zones for new urban areas in Latakia, Syria. MIF was used to rank the input thematic maps. Chi-square test and Cramer's V value were used to allocate decision values into the pairwise matrix instead of expert opinions. Weighted overlay analysis was applied to create the final urban suitability map, which was classified into five classes: unsuitable, low, moderate, high, and very high suitability areas with 0.23, 14.33, 57.75, 27.6, and 0.1% of total area, respectively. The primary outcome of this study is that bivariate analysis improved decision matrix reliability as the values were generated statistically without involvement from experts. The proposed method can be extended to include more parameters, different applications, and implementations. [ABSTRACT FROM AUTHOR]