Application of Remote Sensing Technology, GIS and AHP-TOPSIS Model to Quantify Urban Landscape Vulnerability to Land Use Transformation

This study demonstrated the efficacy of remote sensing technology, GIS and AHP-TOPSIS model to quantify vulnerability of different segments of urban landscape to land use transformation. Six different factors such as Accommodating Index (AI), Mean Heterogeneity Index (MHI), Landscape Shape Index (LSI), Division Index (DI), Cohesion Index (CI), and Distance (D) were identified as inputs to the AHP-TOPSIS model. The Landsat 8 satellite data was classified using supervised classification to determine the aforementioned factors. The influencing factors may have varying intensity in triggering land use conversion. Therefore, the relative importance of the aforementioned factors was quantified using AHP. Furthermore the influence of factors can be either positive or negative on the phenomenon. Thus, Technique of Order of Preference for Similarity to Ideal Solution (TOPSIS) was employed in the present study. The results succeeded in handling the varying characteristics of the variables, and are very close to the actual field-scenario.