Application of Multi–source Remote Sensing Technology on Investigation of Geological Disasters Induced by Rainfall in Mian County

Qinba Mountain Area in southern of Shaanxi province has characteristics of complex terrain and geomorphology, geological structure and climate conditions, and is prone to occurrence of landslide, debris flow and other geological disasters. Due to the large topographic elevation difference and high vegetation coverage in this area, the traditional artificial field investigation is difficult in the identification and investigation of geological disasters, and thus the advanced geological disaster monitoring and identification methods are needed. In this study, a variety of technical methods including optical remote sensing, InSAR and unmanned aerial vehicle photography are used to identify and analyze the hidden dangers of geological disasters induced by “8.22” heavy rainfall in Mian County, southern Shaanxi province, and to explore the identification ability and effectiveness of multi–source remote sensing technology for rainfall–induced geological disasters. The research shows that multi–source remote sensing technology can play an important role in the identification and emergency investigation of regionally geological disasters caused by heavy rainfall. Moreover, the multi–source remote sensing technology can greatly save the working time in field, and provide high–precision remote sensing results with virtue of all aspects, multi–angle and visuality. Optical remote sensing, InSAR, and unmanned aerial vehicle photography have their own advantages and identification categories. It is difficult to completely and effectively solve the problem in hazard identification only by means of a single technical approach. Establishing a multi–source remote sensing–based comprehensive identification system with characteristics of mutual integration and complementary advantage is an effective way to the rapid identification and evaluation of regional geological disasters under heavy rainfall conditions.