Methods of Landslide Detection using GIS and Remote Sensing Images

Abstract

The most challenging and damaging natural disaster is the landslides around the mountainous terrain especially in the western and northern regions of India. The landslides lead to several damages in terms of socio-economic impacts, thus it gains significant researcher's attention since from the last two decades to study and early prediction of landslides. The automatic and accurate landslide detection and localization become essential to suppress the socio-economic impacts with help using sensing remote images & Geographical Information System (GIS). Nowadays remote sensing images provide useful information combined with the GIS environment related to the spatial factors that are influencing the landslide occurrence. The fundamental prerequisite for the landslide prediction using GIS is landslide inventory. In India, the satellite images collected using remote sensors such as LANDSAT ETM+, ASTER, IRS P6, etc. to form the landslide information over the parameters like aspect, slope, drainage density, relative relief, etc. Thus using the remote sensing images, the monitoring of landslide introduced. The landslide prediction using the remote sensing images however suffered from the various challenges. This paper presents the systematic review of various landslide prediction and localization methods using the remote sensing images and GIS information regardless of the study areas. The comparative analysis and the current research challenges for designing the automated landslide detection framework discussed based on the literature review.