Regional landslide disaster risk analysis based on big data

Abstract

Landslide is one of the world's most destructive natural disasters, in recent years, due to extreme weather and human engineering activities, such as shift caused by the landslide disaster events brought serious harm to the society, therefore, scientific prediction of landslide disaster in order to realize, disaster prevention and reduction is of great scientific significance, based on the guizhou pan city as research area, with the support of vast amounts of big data, The traffic road and residential building information were obtained by high resolution remote sensing image, and the landslide risk and disaster bearing body information were integrated, and regional landslide disaster risk analysis was realized by risk matrix. The results show that the landslide risk areas are mainly concentrated in urban areas, township streets and traffic areas with high economic value, covering an area of 214.2km2, accounting for 5.3% of the total area of the study area. The prediction results are consistent with the actual situation in the study area, providing technical support for disaster prevention and relief.