Landslide Susceptibility Areas Mapping Using GIS and Remote Sensing Data in Palopo and North Luwu, South Sulawesi Province
Citra Aulian Chalik (a), Andi Fahdli Heriansyah (a), Muhammad Hardin Wakila (a), Sri Widodo(b), Nurliah Jafar (a), Sitti Ratmi Nurhawaisyah (a)

(a) Mining Engineering Department, Faculty of Industrial Technology, Universitas Muslim Indonesia 90231, Makassar
(b) Mining Engineering Department, Faculty of Engineering, Hasanuddin University 90245, Indonesia

Abstract

Indonesia has two hot and rainy seasons which can show quite extreme changes in weather, temperature and wind direction. Climate, topography, and rock conditions in Indonesia are relatively diverse, both physically and chemically. These conditions can cause adverse consequences such as floods, landslides, forest fires and droughts. Besides the influence of natural conditions, human activities can also cause environmental damage that will increase and often occur in many regions in Indonesia. The landslide disasters that occurred in Palopo City on 26 June 2020 and in North Luwu on 13 July 2020 are evidence of landslide-prone areas in South Sulawesi. The aim of this research is to map landslide susceptibility areas using GIS and Remote Sensing data. Remote sensing data used is the ASTER L1T and DEMNAS image data. ASTER L1T image processing and supervised classification is carried out to obtain a vegetation density map. DEMNAS data is processed to obtain a slope map. The vegetation density map and slope map will be overlaid with geological maps, rainfall maps and land use maps then scoring is done to get landslide prone areas. The research result is a map of landslide-prone areas with a landslide level classification consisting of high, medium and low potential areas. This map can be used as a reference in natural disaster mitigation as well as for recommendations in spatial planning.

Keywords: Landslide, Remote Sensing, ASTER, DEMNAS

Topic: Landfill