Landslide susceptibility mapping by combining the analytical hierarchy process and weighted linear combination methods: a case study in the upper Lo River catchment (Vietnam)

The purpose of this study is to carry out a regional landslide susceptibility mapping for the upper Lo River catchment (ULRC) in northern Vietnam, where data on spatial distribution of historic landslides and environmental factors are very limited. Two methods, analytical hierarchy process (AHP) and weighted linear combination (WLC), were combined to create a landslide susceptibility map for the ULRC study area. In the first step, 216 existing landslides that occurred in the study area were mapped in field surveys in 2010 and 2011. A spatial database including six landslide factor maps related to elevation, slope gradient, drainage density, fault density, types of weathering crust, and types of land cover was constructed from various sources. To determine the relative importance of the six landslide factors and their classes within the landslide susceptibility analysis, weights of each factor and each factor class were defined by expert knowledge using the AHP method. To compute the landslide susceptibility, defined weights were assigned to all factor maps in raster format using the WLC method. The result is a landslide susceptibility index that is reclassified into four susceptible zones to produce a landslide susceptibility map. Finally, the landslide susceptibility zonation map was overlaid with the observed landslides in the inventory map to validate the produced map as well as the overall methodology. The results are in accordance with the occurrences of the observed landslides, in which 47.69 % of observed landslides are located in the two most susceptible zones (very-high-susceptibility zone and high-susceptibility zone) that cover 40.96 % of the total area. As the approach is able to integrate expert knowledge in the weighting of the input factors, the actual study shows that the combination of AHP and WLC methods is suitable for landslide susceptibility mapping in large mountainous areas at medium scales, particularly for areas lacking detailed input data.