A hybrid integration of analytical hierarchy process (AHP) and the multiobjective optimization on the basis of ratio analysis (MOORA) for landslide susceptibility zonation of Aizawl, India

Landslide susceptibility zonation mapping is important to identify the places susceptible to landslides according to the failure probability of slopes. Recently, several techniques for assessing the landslide susceptibility zone (LSZ) have been documented with a unique evaluation and validation strategy. Functionally, in LSZ mapping, susceptibility predictions are typically generated in terms of probabilities and likelihoods. The novelty of the current study is a hybrid integration of analytical hierarchy process (AHP) and multi objective optimization on the basis of ratio analysis (MOORA) multi-criteria decision-making to prepare landslide susceptibility zones of Aizawl district of the state of Mizoram, India. The region falls under the tectonically active belt of the Himalayas which makes it landslide prone. Eight morphometric indices, including terrain surface texture, topographic wetness index, slope steepness and length (LS) factor, terrain surface convexity, topographic openness, topographic ruggedness index, morphometric protection index, and stream power index, have been chosen for preparing LSZ after being examined by a multi-collinearity test using variance inflation factors and tolerances. As a result, AHP subjective weighting with an acceptable consistency ratio was used to solve the criteria weight selection problem, and MOORA for weighted overlay with inverse distance weighting interpolation was used. The landslide susceptibility raster was categorised into five landslide susceptibility zones by the natural breaking classification system. As a result, the district comprises a very high landslide susceptibility zone about 8.51%, a high landslide susceptibility zone about 28.30%, a moderate landslide susceptibility zone about 35.75%, a low landslide susceptibility zone about 23.29%, and a very low landslide susceptibility zone about 4.15%. The significance of the study is that integration of AHP and MOORA has shown very high accuracy at 0.981 and the same was evaluated using the ROC (receiver operating characteristics) curve. Overall, the use of the AHP approach in combination with certain other MCDM models, like a hybrid model to develop LSZs, is suggested as the fundamentals of participatory decision-making in AHP for land-use design and landslide hazard management.