Spatial Analysis Model For Landslide Detection Using Relative Different NDVI (rdNDVI) Method Thought The Google Earth Engine Platform (Case Study: Sukajaya District, Bogor Regency)

Abstract

This research utilizes the Google Earth Engine platform to detect landslides with relatively different NDVI (rdNDVI) methods. The purpose of the research is to improve our understanding of landslide analysis and detection, particularly those that occurred in Sukajaya district, Bogor Regency, Indonesia, on January 1, 2020. This research identifies vegetation changes associated with landslide likelihood using Sentinel-2A satellite image data available on Google Earth Engine. The results show that the rdNDVI method is effective in detecting landslides and can be used to determine areas that may be affected by landslides. This research also evaluates the accuracy of landslide detection by determining the threshold value to determine which areas are affected by landslides, by applying different slope values, the slopes used are slope 10, 15, 20, and 25. Comparing each slope results in a slope of 10 percent and a slope of 15 percent with 90% accuracy making the best accuracy compared to other slopes. The results of this research are expected to help the Regional Disaster Management Agency (BPBD) of Bogor Regency in managing landslides by conducting a careful and accurate analysis of areas that may be affected by landslides.