人民长江 ›› 2023, Vol. 54 ›› Issue (3): 130-137.doi: 10.16232/j.cnki.1001-4179.2023.03.020

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基于倾斜摄影测量与InSAR技术的库区滑坡识别

吴明堂;姚富潭;杨建元;陈建强;姚义振;董秀军;   

  • 出版日期:2023-03-28 发布日期:2023-04-03

Landslide identification in reservoir area based on oblique photogrammetry and InSAR technology

WU Mingtang YAO Futan YANG Jianyuan CHEN Jianqiang YAO Yizhen DONG Xiujun   

  • Online:2023-03-28 Published:2023-04-03

摘要: 随着水电站的建成蓄水,水位变动会影响库岸边坡稳定性,从而诱发一系列的库岸滑坡,危害水电工程及库区居民安全。为尽早识别潜在库岸滑坡,选取白鹤滩库区作为研究区,提出将无人机倾斜摄影测量技术与短基线集干涉测量技术(SBAS-InSAR)相结合的方法,识别白鹤滩水电站库区及其周边地区的滑坡隐患点,并绘制滑坡图、制定滑坡识别程序。首先运用InSAR技术对白鹤滩库区葫芦口-象鼻岭岸段约300 km2流域进行大范围识别,共圈定46处疑似滑坡隐患点。然后,选取了其中约50 km2区域进行基于倾斜摄影测量技术的滑坡隐患识别与精细化查证方法研究。除精细化查证了SBAS-InSAR技术探测到的5处存在形变特征的活动滑坡外,还利用三维实景模型、三维增强显示模型,基于灾害体的形态、微地貌特征,另外识别出了7处当前暂时处于稳定状态、形变迹象不明显的古滑坡体。实验结果经实地查证,该滑坡识别方法准确率较高,可为白鹤滩库区及类似工况地区的地质灾害防治提供重要参考。

关键词: 库区滑坡;早期识别;无人机倾斜摄影测量;SBAS-InSAR;白鹤滩水电站;

Abstract: With the completion and impoundment of the hydropower stations, the change of water level will affect the stability of the reservoir bank slope, leading to a series of reservoir bank landslides that endanger the safety of the hydroelectric project and the residents in the reservoir area.In order to identify potential reservoir bank landslides as early as possible, Baihetan Reservoir area was selected as the research area, and a method combining unmanned aerial vehicle(UAV) oblique photogrammetry technology with short baseline set interferometric measurement technology(SBAS-InSAR) was proposed to identify hidden landslide hazard points in the Baihetan Reservoir area and its surrounding areas.Based on the identification results, we drew a landslide map and developed a landslide identification procedure.Firstly, the InSAR technology was used to identify a large area of about 300 km2 in the Hulukou-Xiangbiling section of the Baihetan Reservoir area, with a total of 46 suspected landslide hidden danger points identified.Then, an area of about 50 km2 was selected for the landslide hidden danger identification and detailed verification method research based on the UAV oblique photography measurement technology.In addition to the verification of 5 active landslides with deformation features detected by the SBAS-InSAR technology, 7 ancient landslide bodies that were currently temporarily stable and had unclear deformation signs were also identified based on the morphology and micro-geomorphic features of the disaster bodies using three-dimensional realistic models and three-dimensional enhanced display models.The experimental results were verified on site, and the landslide identification method was found to have a high accuracy, which can provide important reference for geological disaster prevention and control in the Baihetan Reservoir area and similar working conditions.

Key words: landslide; early identification; SBAS-InSAR; UAV oblique photogrammetry; Baihetan Hydropower Station;