A qualitative approach for spatial multi-criteria evaluation of landslide susceptibility by normalised values of Analytical Hierarchical Process (AHP): a case study from Kalawana Administrative Division, Sri Lanka

The qualitative evaluation of large databases and determination of significance of multivariate databases is a prominent approach. Numerical methodologies of data evaluation has yet to uncover many exciting opportunities for application in disaster management. The evaluation of landslide susceptibility usually deals with various combinations of geographical data sets including slope forms, catchment hydrology, stream hydrology, precipitation potential or rainstorm, soil saturation, soil strength, saturation potential and various derived forms of geological data. The difficulties associated with introducing a large data integrated system are first, having a systematic evaluation methodology which is practical, and second, having a set of scientific auxiliary decision methods to evaluate total significance. The Analytical Hierarchical Process (AHP) is a convenient way for quantitative analysis in decision making under a probabilistic environment and it is also an effective method for scientists to objectively provide subjective judgment. The AHP improves qualitative approaches on mutually exclusive dependencies or interdependencies of data and evaluates the significance in the Weighted Average Analysis (WAA) approach on landslide susceptibility. This qualitative approach will be further used to calibrate the large databases on landslide susceptibility evaluation with more and more interacting sets of data. The overall accuracy of the WAA model approach always depends on the sensitivity of the GIS databases and calibration through physically known datasets of landslide occurrences.