Assessing classification system for landslide susceptibility using frequency ratio, analytical hierarchical process and geospatial technology mapping in Aizawl district, NE India

Abstract

Landslides are a severe geological hazard in northeastern India, particularly in Mizoram’s Aizawl district. To assess this hazard, we conducted a landslide susceptibility mapping study using the frequency ratio (FR) and analytical hierarchy process (AHP) methods. Twelve factors, including slope, elevation, aspect, curvature, topographic wetness index, topographic ruggedness index, rainfall erosivity factor, geology, land use land cover, normalized difference vegetation index (NDVI), and distance to road, were considered. The final susceptibility maps were created by combining these factors, each weighted according to its importance. Since no standard classification guidelines existed, we compared different systems like GIS-based geometric interval (GIC), natural breaks (NBC), and quantile interval (QIC) with mean-standard deviation (MSC). The area was divided into five susceptibility zones: very high, high, moderate, low, and very low. We evaluated the accuracy of these systems using success rate curve (SRC) and quality sum ratio (Qs) techniques. SRC results showed similar performance for GIC, NBC, QIC, and MSC classifications. The AHP method also yielded comparable results. After analyzing the AUC under SRC and Qs, we selected the MSC classification system as the optimal approach for landslide susceptibility mapping. Notably, the distance to roads factor had the highest predictive value, highlighting its importance in identifying slope instability for effective management strategies. As landslides pose significant risks in northeastern India, and our study using FR and AHP methods, along with MSC classification, provides valuable insights for mitigating this geological hazard.