Landslide Susceptibility Zoning Using Fuzzy Logic Algorithm & GIS: Study Case in Majene, West Sulawesi

Abstract

In this research, the application of regional zoning was conducted using fuzzy logic and GIS in the Majene Regency area. This study identifies the susceptibility level of landslides in 8 sub-districts and 82 villages within Majene Regency. The system consists of 24 rule components and adopts a Multi Input Single Output (MISO) system structure, with 6 inputs and one output. The input parameters utilized include rainfall, slope steepness, slope elevation, distance to the highway, land use, and soil type. Relevant data was transformed into raster format within the Geographic Information System (GIS) framework and employed as the dataset. A total of 65,534 data points were processed using fuzzy logic algorithms. Out of the 15 observed villages, seven exhibited very high vulnerability, three villages showed a high susceptibility level, three villages displayed moderate susceptibility, and two other villages demonstrated low susceptibility levels. This research visualizes susceptibility levels on a map based on longitude and latitude coordinates for risk mitigation planning. Measures such as land use regulation, slope reinforcement, and early warning systems are required to safeguard the community and environment from potential landslide disasters in the future. These actions also contribute to the sustainability and security of the region against serious natural disaster threats.

Access to Document

Other files and links

• Link to publication in Scopus

Fingerprint