Predicting landslide extent of satellite images based on image classification extraction

Abstract

Abstract Landslide is a common geological disaster and the most destructive natural disaster at home and abroad. Therefore, automatic interpretation of landslide high-risk areas and potential landslide areas through different models and methods is one of the basic ways to prevent and reduce possible disasters. In this study, we improve the NDWI method by using the multispectral image data from the French satellite SPOT 5. Combined with infrared band sensors, the Normalized Difference Water Index (NDWI) of large exposed landslides is extracted by improving the NDWI index method by utilizing the characteristics of near-infrared (NIR) and short-wave infrared (SWIR) bands and replacing the green-wave band or the mid-infrared (MIR) band with the short-wave infrared (SWIR) band, which can be applied to the water resources management of high-risk areas, potential landslide areas, and potential landslide areas, and the water environment monitoring of water resources and disaster emergency management. We calculate the 2014 satellite images with a total area of 11351.6 ha, and after the NDWI index, the dark blue color represents the high-risk landslide area of 1609.1 ha (14175%), the light blue color represents the potential landslide area of 3971.773 ha (34.989%), and the brown color represents the vegetation area of 5770.727 ha (50.836%).