Sensitivity evaluation of landslide geological hazards based on Multi-source Remote Sensing Data

Abstract

The landslide geological disaster caused by heavy rainfall has the characteristics of sudden and rain and slide. Due to the limitations of weather, terrain and other conditions during the disaster period, the traditional manual survey is difficult to carry out at the first time and can not meet the needs of disaster relief. Multi source remote sensing data makes up for the defects of a single sensor. Relying on its advantages of large-scale, long time series and all-weather real-time imaging, using multi-source remote sensing data technology, various evaluation elements in the survey area can be quickly extracted to investigate the sensitivity evaluation of landslide geological hazards. Landslide is one of the natural disasters that cause great losses and casualties in the world. This is a serious geological disaster second only to earthquake, which poses a great threat to people's life, property safety and economic construction. Considering the serious situation of landslide disaster and the huge losses caused by it, effectively investigating and monitoring the distribution and activities of landslide, predicting and evaluating landslide are not only the urgent requirements of the affected areas, but also the mission of landslide scientists, so as to provide a scientific basis for the prevention and management of landslide disaster. This paper will study the landslide sensitivity evaluation, which is the central problem of landslide disaster research. Landslide sensitivity, also known as landslide susceptibility, belongs to the category of landslide spatial prediction. In this paper, GIS, RS, data mining and landslide sensitivity evaluation are combined to solve the problems of low efficiency, low precision, time and labor consumption in the previous landslide sensitivity evaluation, and realize the informatization and scientization of landslide geology.