ISSN 1009-6248CN 61-1149/P 双月刊

主管单位:中国地质调查局

主办单位:中国地质调查局西安地质调查中心
中国地质学会

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    多源遥感技术在降雨诱发勉县地质灾害调查中的应用

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

    • 摘要: 陕南秦巴山区地形地貌、地质构造和气候条件复杂,易发和频发滑坡、泥石流等地质灾害。由于该区地形高差大且植被覆盖率高,传统的人工地面调查排查在地质灾害的调查识别中难度较大,需借助先进的地质灾害监测识别技术方法。笔者综合采用光学遥感、合成孔径雷达干涉测量(Interferometric Synthetic Aperture Radar, InSAR)和无人机航测等多种技术手段,对陕南勉县“8.22”强降雨诱发的地质灾害进行应急调查与识别分析,探索多源遥感技术对降雨诱发型地质灾害的识别能力与有效性。研究表明,多源遥感技术在强降雨诱发区域性地质灾害的识别和应急调查中能够发挥重要作用,可大大减少现场工作时间,并能提供全方位、多角度和可视化的高精度遥感成果;光学遥感、InSAR、无人机航测等技术具有各自的优势和识别范畴,仅靠单一的技术手段难以完全有效地解决灾害隐患识别问题,建立一套多源遥感技术相互融合、优势互补的综合调查识别体系,是强降雨条件下区域性地质灾害快速调查识别与评价的有效途径。

       

      Abstract: 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.

       

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