Spatial analysis techniques for tsunami vulnerability and inundation mapping of Andaman region using remote sensing, GIS, AHP, and Fuzzy logic methods

The detailed inundation mapping and vulnerability assessment is an essential component of risk reduction and rehabilitation planning in tsunami-prone regions. Integrated spatial analyses through Analytical Hierarchy Process (AHP) and Fuzzy logic operation, mainly Fuzzy PRODUCT and Fuzzy GAMMA (0.9), are used to assess tsunami vulnerability and inundation mapping in the Andaman region, which experienced the 2004-Great Indian Ocean Tsunami. The thematic layers of elevation, slope, shoreline distance, and vegetation density are created using SRTM DEM and Landsat-8 OLI (~ 30 m spatial resolution). The tsunami wave heights are generated from TUNAMI-N2 Model using GEBCO bathymetry data. AHP evaluation process is applied to assign weights to the thematic layers, which are integrated using the weighted sum method. The input weight score of each thematic layer is transformed into a 0 to 1 scale using Fuzzy membership function to derive Fuzzy PRODUCT and Fuzzy GAMMA tsunami vulnerability classes, namely very low, low, medium, high, and very high, depending on correlation with tsunami run-up map. The weighted sum, Fuzzy PRODUCT, and Fuzzy GAMMA methods estimate ~ 1227 (26%), 225 (5%), and 844.33 (18%) km 2 areas as very high vulnerability. The Fuzzy GAMMA method closely compares with the observed-modeled inundation of ~ 14% in the Andaman region. The vulnerability is correlated with the inundation pattern and LULC changes to understand the change in vulnerability from 2004 to 2021. The results are discussed for the robustness of the observation and technique that can be used for tsunami disaster management and land-use planning.