A new GIS-based technique using an adaptive neuro-fuzzy inference system for land subsidence susceptibility mapping

Abstract

In this study, we evaluated the predictive performance of an adaptive neuro-fuzzy inference system (ANFIS) with six different membership functions (MFs). Using a geographic information system (GIS), we applied ANFIS to land subsidence susceptibility mapping (LSSM) in the study area of Amol County, northern Iran. As a novelty, we derived a land subsidence inventory from the differential synthetic aperture radar interferometry (DInSAR) of two Sentinel-1 images. We used 70% of surface subsidence deformation areas for training, while 30% were reserved for testing and validation. We then investigated regions that are susceptible to subsidence via the ANFIS method and evaluated the resulting predi..